Existing runway residual life prediction models need to be modified using the historical data of evaluated airports during evaluation and management for civil airports in China. If the data measured in the field and the historical data used for model calibration do not represent the actual historical performance of the evaluated airport, the predicted performance of the revised model might be poor

The ability to obtain accurate torque information and detect collision information is the key demand for collaborative robots. Given the highly integrated modular joint, the joint torque-sensing system is disturbed by other elements during online measurement, affecting the accuracy of measurement. For example, the torque ripple caused by the periodic deformation of the flexspline of the harmonic driver

In this paper, we study some state-specific one-sided exit probabilities in a Markov-modulated risk process including the probability that ruin occurs without or with the surplus visiting certain states; the probability that ruin occurs without or with a claim occurring in certain states; the probability that the surplus attains a target level without or with visiting certain states; and the probability

To study the mechanism of hydraulic fracturing with pulse injection theoretically, in this paper, the transient flow model of fracturing fluid in the pipe string was established, and it was solved by method of characteristics and finite difference method, respectively. Furthermore, the elastodynamic model of reservoir was also established. Based on the finite element method, the dynamic stress distribution

In this paper, a new geometric structure of projective invariants is proposed. Compared with the traditional invariant calculation method based on 3D reconstruction, this method is comparable in the reliability of invariant calculation. According to this method, the only thing needed to find out is the geometric relationship between 3D points and 2D points, and the invariant can be obtained by using

In this paper, a discrete Markov-modulated risk model with delayed claims, random premium income, and a constant dividend barrier is proposed. It is assumed that the random premium income and individual claims are affected by a Markov chain with finite state space. The model proposed is an extension of the discrete semi-Markov risk model with random premium income and delayed claims. Explicit expressions

In this paper, a novel chaotic new three-dimensional system has been studied by Zhang et al. in 2012. In the system, there are three control parameters and three different nonlinear terms which governed equations. Zhang et al. studied elementary (preliminary) dynamic properties of the chaotic new three-dimensional system by means of bifurcation diagram, maximum Lyapunov exponent, phase portraits, dynamics

Financial flexibility is an important research issue in corporate finance. This paper utilizes the Spatial Durbin Model (SDM) to analyze the impact of financial flexibility on the investment of Convention and Exhibition companies listed on the New Third Board from 2014 to 2016. The empirical results show the following. Firstly, the greater the financial flexibility, the more investment the firm will

The problem of position estimation has always been widely discussed in the field of wireless communication. In recent years, deep learning technology is rapidly developing and attracting numerous applications. The high-dimension modeling capability of deep learning makes it possible to solve the localization problems under many nonideal scenarios which are hard to handle by classical models. Consequently

Virtual Synchronous Generators (VSGs) can reduce the frequency and power oscillation in the grid. For parallel multi-VSGs in island microgrid, the differences of equivalent output impedance and line impedance affect the orderly sharing of reactive power and restraining of circulating current greatly. The power sharing and circulating current characteristics of VSGs are analyzed in this paper. To solve

The recent empirical studies showed that money center networks in interbank markets are more robust and stable. Therefore, the research on layered financial networks is a key part of the systemic risk management. Various methods have been proposed in prior studies to find optimal partitioning of interbank networks into core and periphery subsets. However, these methods that have been adopted with approximation

For a connected graph J, a subset is termed as a locating-total dominating set if for , and for . The number of elements in a smallest such subset is termed as the locating-total domination number of J. In this paper, the locating-total domination number of unicyclic graphs and bicyclic graphs are studied and their bounds are presented. Then, by using these bounds, an upper bound for cacti graphs in

As the important data basis of surrounding rock classification, rock mass structural information obtained by traditional image processing and feature extraction algorithms could not be quantitatively analyzed because of the uncertainty and geometric randomness of structural planes. In this paper, based on straight line detection, intelligent scissors, and morphological edge detection algorithms, the

A new three-term conjugate gradient method is proposed in this article. The new method was able to solve unconstrained optimization problems, image restoration problems, and compressed sensing problems. The method is the convex combination of the steepest descent method and the classical LS method. Without any linear search, the new method has sufficient descent property and trust region property.

Let be a -dimensional bifractional Brownian motion and be the bifractional Bessel process with the index . The Itô formula for the bifractional Brownian motion leads to the equation . In the Brownian motion case and , is a Brownian motion by Lévy’s characterization theorem. In this paper, we prove that process is not a bifractional Brownian motion unless and . We also study some other properties and

Fire is one of the most dangerous phenomena causing major casualties and financial losses in hospitals and healthcare settings. In order to prevent and control the fire sources, first risk assessment should be conducted. Failure Mode and Effect Analysis (FMEA) is one of the techniques widely used for risk assessment. However, Risk Priority Number (RPN) in this technique does not take into account the

Crack plays a critical role in the field of evaluating the quality of concrete structures, which affects the safety, applicability, and durability of the structure. Due to its excellent performance in image processing, the convolutional neural network is becoming the mainstream choice to replace manual crack detection. In this paper, we improve the EfficientNetB0 to realize the detection of concrete

By this work, our aim is to study oscillatory behaviour of solutions to 4th-order differential equation of neutral type where . By using the comparison method with first-order differential inequality, we find new oscillation conditions for this equation.

Network virtualization is considered as a key technology for the future network. The emergence of software-defined network (SDN) provides a platform for the research and development of network virtualization. One of the key challenges in network virtualization is virtual network embedding (VNE). Some of the previous VNE algorithms perform virtual node embedding, which combines the nodes’ resource attributes

The projection of future hydropower generation is extremely important for the sustainable development of any country, which utilizes hydropower as one of the major sources of energy to plan the country’s power management system. Hydropower generation, on the other hand, is mostly dependent on the weather and climate dynamics of the local area. In this paper, we aim to study the impact of climate change

The paper aims are to present a method to solve the multiple-attribute decision-making (MADM) problems under the hesitant fuzzy set environment. In MADM problems, the information collection, aggregation, and the measure phases are crucial to direct the problem. However, to handle the uncertainties in the collection data, a hesitant fuzzy number is one of the most prominent ways to express uncertain

In this paper, we propose a Markov chain model to price basket credit default swap (BCDS) and basket credit-linked note (BCLN) with counterparty and contagion risks. Suppose that the default intensity processes of reference entities and the counterparty are driven by a common external shock as well as defaults of other names in the contracts. The stochastic intensity of the external shock is a Cox

In order to effectively enhance the low detection rates of dim and small targets caused by dynamic backgrounds, this paper proposes a detection algorithm for dim and small targets in sequence images based on spatiotemporal motion characteristics. With regard to the spatial domain, this paper proposes an improved anisotropic background filtering algorithm that makes full use of the gradient differences

In this article, we consider the analytic solutions of the uncertain fractional backward difference equations in the sense of Riemann–Liouville fractional operators which are solved by using the Picard successive iteration method. Also, we consider the existence and uniqueness theorem of the solution to an uncertain fractional backward difference equation via the Banach contraction fixed-point theorem

Human parsing, which aims at resolving human body and clothes into semantic part regions from an human image, is a fundamental task in human-centric analysis. Recently, the approaches for human parsing based on deep convolutional neural networks (DCNNs) have made significant progress. However, hierarchically exploiting multiscale and spatial contexts as convolutional features is still a hurdle to overcome

The goal is to explore the impact of motivation of participation, involvement, and satisfaction rate of sports App on physical and mental health and analyze the current status of development and trend of sports App. Six hundred and eighty valid questionnaires were analyzed using test statistic, descriptive statistics, and Pearson Product-Moment correlation followed by semistructured interviews to gather

Studies on the role of renewable energy consumption and other environmental factors in carbon emission have got considerable attention recently, and they are predicted to get exaggerated in the coming decades. Energy usage increases economic growth and development of a country and backs to global warming and carbon emission which affect the local environment. For the prosperity of a country, it is

The process of CEO incentive and supervision, in which the special committee plays an important role, has always been a hard problem to solve in modern corporate governance. Considering the conflicts of interest between the compensation committee, audit committee, and the CEO, this paper constructed a game model of incentive and supervision within the board of directors and analysed the strategic choices

Based on the cellular automaton model, the risk of modernization of traditional sports culture is evaluated and measured by using the methods of documentary, interview, and simulation experiments. The results of simulation experiment show that, in the complex system of the modernization of traditional sports culture, the mutation factors will lead to the sudden decline of the survival suitability of

The conversion from conventional to new driving forces and their time-varying characteristics are of great importance to China’s economic transformation. In this paper, we attempt to investigate the economic growth driving force conversion in China and the time-varying characteristics of driving forces by constructing a time-varying coefficient panel data model during the period of 1998–2015. The empirical

A barrier function method based on the fmincon optimization function in MATLAB was used to determine the function to map a tunnel boundary to the unit circle in the complex plane, and a structural failure criterion of the mapping convergence was established based on the reliability theory of underground engineering. The joints were approximated as cracks around the tunnel, the anisotropy of the stress

This work is chiefly concerned with the stability behavior and the appearance of Hopf bifurcation of fractional-order delayed Cohen–Grossberg neural networks. Firstly, we study the stability and the appearance of Hopf bifurcation of the involved neural networks with identical delay . Secondly, the sufficient criterion to guarantee the stability and the emergence of Hopf bifurcation for given neural

Recent development of artificial intelligence (AI) technology enquires the traditional power grid system involving additional information and connectivity of all devices for the smooth transit to the next generation of smart grid system. In an AI-enhanced power grid system, each device has its unique name, function, property, location, and many more. A large number of power grid devices can form a

The load capacity of the permanent magnet synchronous motor is limited by the rotor temperature, and the excessive temperature of the rotor will bring potential thermal safety problems of the system. Therefore, the accurate prediction of the rotor temperature of the permanent magnet synchronous motor for the electric vehicle is crucial to improve the motor performance and system operation safety. This

How to qualitatively and quantitatively evaluate the ability of the whole subway system to maintain the maximum normal operation has become a noteworthy topic. In this study, the hypergraph space structure of Nanjing subway network is used for research. This study uses the method of time-space evolution mechanism to dynamically and quantitatively analyze the gradual change characteristics of Nanjing

Traditional tolerance analysis is mostly restricted to static analysis. However, tolerances of different components also affect the movement accuracy in a mechanism. In this paper, the idea of kinematic tolerance analysis is advanced. In the interest of achieving movement precision considering tolerance, a kinematic Jacobian model is established on the basis of a traditional dimensional chain and an

The seismic ahead-prospecting method is useful to detect anomalous zones in front of the tunnel face. However, most existing seismic detection method is designed for drilling and blasting tunnel. The detection method should be improved to satisfy the rapid tunneling of Tunnel Boring Machines (TBMs). This study focuses on reducing the time spent on seismic data processing and result analysis. Therefore

Production optimization of coalbed methane (CBM) is a complex constrained nonlinear programming problem. Finding an optimal decision is challenging since the coal seams are generally heterogeneous with widespread cleats, fractures, and matrix pores, and the stress sensitivities are extremely strong; the production of CBM wells needs to be adjusted dynamically within a reasonable range to fit the complex

Aiming at the problems of low search efficiency and inaccurate optimization of existing service composition optimization methods, a new multiobjective optimization model of cloud manufacturing service composition was constructed, which took service matching degree, composition synergy degree, cloud entropy, execution time, and execution cost as optimization objectives, and an improved particle swarm

With the development of autonomous systems, the operational use of loitering munition is shifting from the following of a preplanned fixed route without communication to smart decision-making and collaborative cooperation with sharing information. In this paper, we study the autonomous decision-making and cooperative control strategy of online patrolling for a swarm of loitering munitions using communication

This study deals with the containership stowage problem, determining how to stow containers to the containership slots. To improve the containership operational efficiency and meet the containership seaworthy requirements, a basic model is proposed for the simplified containership stowage problem. And then, it is extended by incorporating more practical considerations, which are progressively embedded

Environmental protection is a fundamental policy in many countries, where the vehicle emission pollution turns to be outstanding as a main component of pollutions in environmental monitoring. Remote sensing technology has been widely used on vehicle emission detection recently and this is mainly due to the fast speed, reality, and large scale of the detection data retrieved from remote sensing methods

Time series data are an extremely important type of data in the real world. Time series data gradually accumulate over time. Due to the dynamic growth in time series data, they tend to have higher dimensions and large data scales. When performing cluster analysis on this type of data, there are shortcomings in using traditional feature extraction methods for processing. To improve the clustering performance

Massive sport, such as unmanned aerial vehicle performance, often needs fast and efficient calculation of formation morphing and individual path planning. This paper introduces a novel fast formation control method of a crowd. First, we get the agents’ location in a 2D polygon with centroidal Voronoi tessellation and L-BFGS techniques. Then, we transform crowd formation shapes with a global shortest

Aiming at the problem of matching logistics service supply and demand, this paper proposes a two-sided matching decision model of logistics service supply and demand based on the uncertain preference ordinal. In this model, the uncertain preference ordinal information is first expressed by the interval numbers of the logistics service supply and demand, and it is converted into the satisfaction degree

Teaching reflection based on videos is the main method in teacher education and professional development. However, it takes a long time to analyse videos, and teachers are easy to fall into the state of information overload. With the development of “AI + education,” automatic recognition of teacher behavior to support teaching reflection has become an important research topic. In this paper, taking

Precise and seamless positioning is becoming a basic requirement for the Internet of Things (IoT). However, there is a gap for precise positioning in Global Navigation Satellite System- (GNSS-) denied indoor areas. Thus, a multisensor integration system based on ultrawide-band (UWB), inertial navigation system (INS), nonholonomic constraints (NHCs), and Rauch–Tung–Striebel (RTS) smoother is proposed

Aiming at solving the problem that the parameters of a fault detection model are difficult to be optimized, the paper proposes the fault detection of the wind turbine variable pitch system based on large margin distribution machine (LDM) which is optimized by the state transition algorithm (STA). By setting the three parameters of the LDM model as a three-dimensional vector which was searched by STA

Multicopters are well suited for executing fast maneuvers with high velocity, but they are still affected by the external atmospheric environment because attitude and position cannot be independently controlled. In this paper, we present a novel hexacopter which improves the wind resistance and strong coupling between attitude control and position control. The copter is designed such that the rotor

Iterative algorithms based on saved data have been researched for strapdown inertial navigation system to make the best use of sensor data, and different alignment algorithms can be carried out during the iterative process to fulfil initial alignment. This paper firstly analysed two interactive processes. The forward-backward process needs to change the normal system model in the backward process and

In this paper, the valuation of the discrete barrier options on the condition that the underlying asset price process follows the GARCH volatility and double exponential jump is studied. We derived an analytical approximation of the characteristic function for the underlying log-asset price. Then, a quasianalytical approximate formula of the price of the discrete barrier option is obtained based the

We propose a constrained linear curvature image registration model to explicitly control the deformation according to the transformed Jacobian matrix determinant using point-by-point inequality constraints in this paper. In addition, an effective numerical method is proposed to solve the resulting inequality constrained optimization model. Finally, some numerical examples are given to prove the obvious

Surcharge slopes are more vulnerable to instability under the effects of earthquake ground shaking, especially considering the tensile stress. In order to account for the adverse factors of seismic forces and tensile stress, the theory of soil with tensile strength cut-off is deduced and analyzed using the upper bound limit analysis method in this paper. Combined with the quasistatic analysis, the

This paper deals with the global asymptotic robust stability (GARS) of neural networks (NNs) with constant time delay via Frobenius norm. The Frobenius norm result has been utilized to find a new sufficient condition for the existence, uniqueness, and GARS of equilibrium point of the NNs. Some suitable Lyapunov functional and the slope bounded functions have been employed to find the new sufficient

Based on the Gurtin-Murdoch surface/interface model and complex potential theory, by constructing a new conformal mapping, the electrically permeable boundary condition with surface effect is established, and the antiplane fracture problem of three nanocracks emanating from a hexagonal nanohole in one-dimensional hexagonal piezoelectric quasicrystals with surface effect is studied. The exact solutions

The combinatorial auction is one of the important methods used for multi-item auctions, and the solution to the winner determination problem (WDP) is the key factor in the widespread application of combinatorial auctions. This paper explores the use of the cross-entropy method to solve the WDP, which is an NP problem. The performance of the proposed approach is evaluated on the basis of two well-known

In this study, the main aim is to improve performance of the voting feature intervals (VFIs), which is one of the most effective machine learning models, using two robust ensemble techniques, namely, AdaBoost and MultiBoost for landslide susceptibility assessment and prediction. For this, two hybrid models, namely, AdaBoost-based Voting Feature Intervals (ABVFIs) and MultiBoost-based Voting Feature

This paper presents a multiple time-step solver based on a time-domain explicit integration algorithm for improving the computational speed of high-voltage transmission line electromagnetic transient (EMT) simulation. For weakly rigid EMT models of high-voltage transmission lines, the previous precise Runge-Kutta integration method with a small time step is adopted; for strongly rigid nonlinear EMT

Milling stability is a function of the tool point frequency response functions (FRFs), which vary with the movements of the moving parts within the whole machine tool work volume. The position-dependent tool point FRFs result in uncertain prediction of the stability lobe diagram (SLD) for chatter-free machining parameter selection. Taking the variations of modal parameters to represent the variations

The optimal control of automatic transmission plays an important role in the shifting smoothness and fuel economy of heavy-duty mining trucks. In this paper, a dynamic model of the powertrain system is built to study the clutch pressure control during the shifting process. A linear-quadratic optimal regulator is used to achieve the optimum control pressure of clutches, where shifting jerk and clutch