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One of the pandemics that have caused many deaths is the Coronavirus disease 2019 (COVID-19). It first appeared in late 2019, and many deaths are increasing day by day until now. Therefore, the early diagnosis of COVID-19 has become a salient issue. Additionally, the current diagnosis methods have several demerits, and a new investigation is required to enhance the diagnosis performance. In this paper, a set of phases are performed, such as collecting data, filtering and augmenting images, extracting features, and classifying ECG images. The data were obtained from two publicly available ECG image datasets, and one of them contained COVID ECG reports. A set of preprocessing methods are applied to the ECG images, and data augmentation is performed to balance the ECG images based on the classes. A deep learning approach based on a convolutional neural network (CNN) is performed for feature extraction. Four different pre-trained models are applied, such as Vgg16, Vgg19, ResNet-101, and Xception. Moreover, an ensemble of Xception and the temporary convolutional network (TCN), which is named ECGConvnet, is proposed. Finally, the results obtained from the former models are fed to four main classifiers. These classifiers are softmax, random forest (RF), multilayer perception (MLP), and support vector machine (SVM). The former classifiers are used to evaluate the diagnosis ability of the proposed methods. The classification scenario is based on fivefold cross-validation. Seven experiments are presented to evaluate the performance of the ECGConvnet. Three of them are multi-class, and the remaining are binary class diagnosing. Six out of seven experiments diagnose COVID-19 patients. The aforementioned experimental results indicated that ECGConvnet has the highest performance over other pre-trained models, and the SVM classifier showed higher accuracy in comparison with the other classifiers. The resulting accuracies from ECGConvnet based on SVM are (99.74%, 98.6%, 99.1% on the multi-class diagnosis tasks) and (99.8% on one of the binary-class diagnoses, while the remaining achieved 100%). It is possible to develop an automatic diagnosis system for COVID based on deep learning using ECG data.

Very recently Jain et al. (J. Inequal. Appl. 2022:73, 2022) introduced the concept of multivalued F-contraction with altering distance function and investigated the existence of best proximity points for this class of mappings. In this article we prove that the existence of best proximity points for multivalued F-contraction non-self mappings can be obtained from the corresponding fixed point result for multivalued F-contraction self mappings, and so the main conclusion due to Jain et al. is not a real generalization of fixed point theory.

This work describes the log-MAP (BCJR) algorithm implementation of a close to capacity dirty paper coding CODEC. The CODEC consists of eight deep pipeline processors. It decodes blocks of 975 bits in 26.9 ms using less than 9.7% of low-cost FPGA (and no DSP blocks). Two pipelines, for alpha and beta, calculate the values of gamma (of the BCJR) to reduce the storage requirements. The final log-likelihood ratio (LLR) is calculated together with alpha, reusing intermediate results. The number of bits used by the different signals of the processor is easily configurable. It was set to six bits to the channel measure signals and eight bits to log of probability signals like alpha, beta, and others. The CODEC clock was 100 MHz. The achieved bit rate is 36.2 Kbps per CODEC, but multiple CODECs can be fit into a single chip. The CODEC is 3.49 dB from the channel capacity.

Necessary optimality conditions for a bilevel optimization problem are given in the paper by Kohli (J Optim Theory Appl 152: 632–651, 2012). Recently, the same author corrected his results in the note (J Optim Theory Appl 181:706–707, 2019). In this work, we have pointed out that some of the new modifications are wrong. We correct the flaws and present an alternative proof for the main result.

Educational evaluation helps to improve the learning and teaching process. The learning process can be assessed by the examination system. In the examination system, the learners have to answer a set of questions. The learning assessment ensures improved performance in the educational system. The success of the learning assessment is highly dependent on the listening and understanding ability of each student. The assessment of the question paper can be at two levels—cognitive level assessment and difficulty level. The cognitive level assessment is purely based on Bloom’s Taxonomy and the difficulty level assessment is purely based on the examination marks of each student. This article presents a technical method called Question Paper’s Difficulty Level (QPDL) that helps to identify the difficulty level of each question in the question paper. The QPDL method is incorporate in the implementation of ‘QAUDIT’ web application to assess the difficulty level of the question paper systematically. The systematic analysis to identify the difficulty level of the question paper is made for 239 question papers. Each question paper can be recognized based on three difficulty levels such as High, Moderate and Low.

To support the safe operation of the novel three-element mixed insulation oil (TEMO) transformer, gas generation behaviors of the TEMO oil–paper insulation system under overheating faults and discharge faults were investigated. Results show that that the content of H2 and C2H6 generated by TEMO–paper insulation system is much higher than that in conventional mineral oil (MO)–paper insulation system under different overheating temperatures. Under partial discharge fault, the content of H2 dissolved in oil changes distinctly, while the content of C2H2 also increases with the discharge time. Under surface flashover breakdown, AC breakdown and lightning impulse breakdown fault, the content of H2 and C2H2 changes greatly compared to other gases, while the concentration of total hydrocarbon gases in TEMO–paper insulation system is smaller than that in MO–paper insulating system after the same breakdown times. The diagnosis model of overheating and discharge faults for the TEMO–paper insulation system was proposed based on the oil dissolved gas analysis, while H2, C2H2 and C2H4 were chosen as the characteristic gases and the boundary settings were determined. The verified result for the low-temperature overheating, lightning impulse and surface flashover fault for the TEMO–paper insulation system presents that the new diagnosis model is effective.

Establishing and optimizing a distributed parameter thermal path model for transformer windings is an important means to analyze the hot-spot temperature of the windings; furthermore, in the process of improving the thermal path model of transformers and improving the accuracy of their models, the thermal characteristics of the insulation paper are extremely important. A microscopic thermal contact resistance model was established for the contact interface of insulation paper and copper, according to the microscopic morphology parameters of copper and insulation paper observed by atomic force microscopy, the thermal contact resistance under different temperatures was calculated. A dual heat flow test platform was built to test the heat transfer behavior of four different thickness insulation papers under four temperatures, and the thermal contact resistance and thermal bulk resistance with temperature were analyzed. The results show that as the temperature increases, the thermal resistance of the insulation paper becomes larger and the thermal conductivity decreases. The average error between the experimental and theoretical values of the thermal contact resistance under four temperature points in the study is 6.6%. The results provide a data support for establishing and optimizing transformer heat generation and heat transfer models.

This is a corrigendum to our paper, “On a class of prime entire functions”, published in Acta Math. Sin., Engl. Ser., 25, 1647–1652 (2009).

The Rock-Paper-Scissors (RPS) game is a classic non-cooperative game widely studied in terms of its theoretical analysis as well as in its applications, ranging from sociology and biology to economics. Many experimental results of the RPS game indicate that this game is better modelled by the discretized best-response dynamics rather than continuous time dynamics. In this work we show that the attractor of the discrete time best-response dynamics of the RPS game is finite and periodic. Moreover we also describe the bifurcations of the attractor and determine the exact number, period and location of the periodic strategies., 24 pages, 9 figures

Droplet impact and penetration into the paper-like medium are essential physical phenomena in variety of natural and industrial processes. The lattice Boltzmann model coupled with random-walk-based stochastic scheme is presented to calculate the interactions between inertial dominated droplet and fibrous medium. Results show that the droplet spreading regime is independent of surface wettability, volume fraction, and Ohnesorge number at very early impact stage. For fibrous medium with volume fraction ~ 50% and wettability 85°, three stages of penetration process are observed. Whereas for low-volume-fraction fibrous medium, the phases of droplet spreading and penetration are coupled which results in a small spreading width for hydrophilic wettability. It is found that the spaces of spreading width and penetration rate are divided by the curve of $$ Oh = 0.038 $$ and $$ Re = 144 $$ . The effects of Ohnesorge and Reynolds numbers largely influence the behaviors of droplet spreading and penetration process. The in-depth insight of inkjet droplet impact onto the paper-like fibrous medium is beneficial for improving printed products in Paper Electronics.

In this work, we improve and correct some results in the paper by Proinov (J Fixed Point Theory Appl 22:1–27, 2020).

We examine the role of count conservation when derived network matrices are obtained from linked network matrices using an outer product decomposition. It is seen that a full counting operation conserves the count of pathways between nodal variables while a fractional counting operation conserves the count of the nodal variable. We use the cases of co-referencing (bibliographic coupling) and co-citation with a simple citation network to illustrate the ideas.

This paper is concerned with some stochastic properties of a novel rock–paper–scissors model. Firstly, the global existence of an unique positive solution of the stochastic model is obtained. Then we demonstrate the positive solution of the model is stochastically bounded. Besides, some sufficient conditions for population to be stochastically permanent and extinct are derived with the use of some appropriate Lyapunov functions. At last, some numerical simulations are carried out to illustrate our theoretical analysis results.

We correct some mistakes in the paper “A mass formula for negacyclic codes of length 2k and some good negacyclic codes over $\mathbb {Z}_{4}+u\mathbb {Z}_{4}$ ” (Bandi et al. Cryptogr. Commun. 9, 241–272, 2017).

Inter-turn insulation plays a major role in the dielectric integrity of any transformer. Though the inter-turn insulation thickness is designed based on standard lightning impulse (LI) voltage distribution, the insulation fails due to various types of overvoltages from switching impulse (SI) to very fast transient overvoltages (VFTO). Moreover, the insulation gets degraded due to many factors such as service ageing, exposure to repeated applications of overvoltages due to various reasons, etc. The effect of the repeated impulses is characterized using the voltage–number (V–N) characteristics recommended by CIGRE Working group C4.302. Based on the design and rating of the transformer, the thickness of the inter-turn insulation is normally changed. To quantify and compare the impulse breakdown strength and degradation due to repeated impulses under SI, LI and VFTO, different thicknesses of oil impregnated paper, ranging from 0.25 to 0.75 mm are considered. Experiments are carried out to obtain the V–N characteristics for all the cases. V–N characteristics are mathematically modeled by enhancing the existing exponential model to incorporate the thickness of insulation and are then validated experimentally. Based on the model parameters, the effect of the various waveshapes and the degradation due to repeated impulses are quantified and compared with the standard LI.

In this work, some counterexamples are given to refute some results reported in the paper by Guo and Li [8] (J Optim Theory Appl 162,(2014), 821-844). We correct the faulty in some of their theorems and we present alternative proofs. Moreover, we extend the definition of approximately pseudo-dissipative in the setting of metrizable topological vector spaces.

In this work, a counterexample is given to refute a result in the paper by Younis et al. (J Fixed Point Theory Appl 21:1–33, 2019). Furthermore, applying this counterexample, we give negative answers to some of the open problems in their paper. Recently, Baradol et al. give a new theorem to rectify the result of Younis et al. However, we find that there are some gaps in the proofs of their results. Finally, we introduce a fundamental lemma and fill these gaps.

This Forum Note concerns the question of necessary optimality conditions in optimal control problems subject to state constraints. Some critical remarks about a recently published paper are made.

The confluence of significant computational power and inexpensive sensors provides the opportunity to reliably collect large volumes of information from the world and extract humanly useful information resources. This paper reviews a coherent body of work over the last 20+ years focused on development of advanced bio-inspired computing techniques, and their applications primarily for human related data in behaviour and human centered computing. We close with a synthesis proposing an experiment analysis methodology combining these tools.

In this note, we make two revisions of the paper [2]. The first one is the asymptotic behavior of the energy functional as $$t\rightarrow T$$ (see [2, Theorem 1.6]), where T is the blow-up time. The second one is the equivalent conditions for the solutions blowing up in finite time or existing globally (see [2, Theorem 1.8]).

In this short paper, we look into a conclusion drawn by Alzalg (J Optim Theory Appl 169:32---49, 2016). We think the conclusion drawn in the paper is incorrect by pointing out three things. First, we provide a counterexample that the proposed inner product does not satisfy bilinearity. Secondly, we offer an argument why a pth-order cone cannot be self-dual under any reasonable inner product structure on $$\mathbb {R}^n$$Rn. Thirdly, even under the assumption that all elements operator commute, the inner product becomes an official inner product and the arbitrary-order cone can be shown as a symmetric cone, we think this condition is still unreasonable and very stringent so that the result can only be applied to very few cases.

This work contains largely afterthoughts, relating to the paper immediately preceding it. We correlate and interpret our contributions in that paper, relative to those of an earlier publication by Aspley, He and McCuan. We propose specific laboratory experiments, suggested by formal predictions of those two papers.

In this paper we consider, discuss and slightly complement recent fixed point results for mappings in b-metric spaces established by Sintunavarat (J Fixed Point Theory Appl 18:397–416, 2016). Thus, all our results are with shorter proofs. In addition, an application to integral equations is given to illustrate the usability of our approach.

This paper proposes a novel fractional-order delayed Ross-Macdonald model for malaria transmission. This paper aims to systematically investigate the effect of both the incubation periods of Plasmodium and the order on the dynamic behavior of diseases. Utilizing inequality techniques, contraction mapping theory, fractional linear stability theorem, and bifurcation theory, several sufficient conditions for the existence and uniqueness of solutions, the local stability of the positive equilibrium point, and the existence of fractional-order Hopf bifurcation are obtained under different time delays cases. The results show that time delay can change the stability of system. System becomes unstable and generates a Hopf bifurcation when the delay increases to a certain value. Besides, the value of order influences the stability interval size. Thus, incubation periods and the order have a major effect on the dynamic behavior of the model. The effectiveness of the theoretical results is shown through numerical simulations.

The results of a voltage-current characteristics study of sensors made of graphite paper with multiwall nanotubes are presented. It has been found experimentally that these samples are usable as gas sensors for the detection of NH3, H2, and Cl2 in air.

Support of artificial intelligence, renewable energy and sustainability is currently increasing through the main policies of developed countries, e.g., the White Paper of the European Union. Wind energy is one of the most important renewable sources, growing in both onshore and offshore types. This paper studies the most remarkable artificial intelligence techniques employed in wind turbines monitoring systems. The principal techniques are analysed individually and together: Artificial Neural Networks; Fuzzy Logic; Genetic Algorithms; Particle Swarm Optimization; Decision Making Techniques; and Statistical Methods. The main applications for wind turbines maintenance management are also analysed, e.g., economic, farm location, non-destructive testing, environmental conditions, schedules, operator decisions, power production, remaining useful life, etc. Finally, the paper discusses the main findings of the literature in the conclusions.

This note tries to answer issues raised in Bhardwaj and Kumar (J Optim Theory Appl 163(2): 685---696, 2014). The research summarizes that the results obtained in Khan et al. (J Optim Theory Appl 159: 536---546, 2013) are sound and correct and it fulfills all the necessary requirements of its scope and objectives.

A criteria due to Toivo Nieminen concerning selfadjoint linear operators in complex Hilbert spaces is extended to the case of linear relations.

This paper investigates the guaranteed cost positive consensus for linear multi-agent systems (MASs) with multiple time-varying delays and switching topologies. First, necessary and sufficient conditions for the positivity of the focused system are given. The positive consensus criterion and switching signals are derived by combining multiple Lyapunov-Krasovskii functionals with mode-dependent average dwell time approaches. Then, the guaranteed cost positive consensus is studied via the state errors among neighbouring agents and control inputs. It realizes a trade-off between the consensus regulation performance and the control energy consumption of MASs. Particularly, the determined upper bound of the cost function depends merely on the initial conditions of the agents and is independent of the switching movements. Finally, simulation results are given to validate the proposed control scheme.

COVID-19 is a public health emergency for human beings and brings some very harmful consequences in social and economic fields. In order to model COVID-19 and develop the effective control measures, this paper proposes an SEIR-type epidemic model with the contacting distance between the healthy individuals and the asymptomatic or symptomatic infected individuals, and the immigration rate of the healthy individuals since the contacting distance and the immigration rate are two critical factors which determine the transmission of COVID-19. Firstly, the threshold values of the contacting distance and the immigration rate are obtained to analyze the presented model. Secondly, based on the data from January 10, 2020, to March 18, 2020, for Wuhan city, all parameters are estimated. Finally, based on the estimated parameters, the sensitivity analysis and the numerical study are conducted. The results show that the contacting distance and the immigration rate play an important role in controlling COVID-19. Meanwhile, the extinct lag decreases as the contacting distance increases and/or the immigration rate decreases. Our study could give some reasonable suggestions for the health officials and the public and provide a theoretical issue for globally controlling the COVID-19 pandemic.

In this paper, we consider a stochastic SIR epidemic model with general disease incidence rate and perturbation caused by nonlinear white noise and L\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$\acute{e}$$\end{document}e´vy jumps. First of all, we study the existence and uniqueness of the global positive solution of the model. Then, we establish a threshold \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$\lambda $$\end{document}λ by investigating the one-dimensional model to determine the extinction and persistence of the disease. To verify the model has an ergodic stationary distribution, we adopt a new method which can obtain the sufficient and almost necessary conditions for the extinction and persistence of the disease. Finally, some numerical simulations are carried out to illustrate our theoretical results.

In this note, we give affirmative answers to two open problems posed by Agarwal et al. in the paper (J Optim Theory Appl 163(2):482---490, 2014).