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Analysis of flows in crowd videos is a remarkable topic with practical implementations in many different areas. In this paper, we present a wide overview of this topic along with our own approach to this problem. Our approach treats the difficulty of crowd flow analysis by distinguishing single versus multiple flows in a scene. Spatiotemporal features of two consecutive frames are extracted by optical flows to create a three-dimensional tensor, which retains appearance and velocity information. Tensor’s upper left minor matrix captures intensity structure. A normalized continuous rank-increase measure for each frame is calculated by a generalized interlacing property of the eigenvalues of these matrices. In essence, measure values put through the knowledge of existing flows. Yet they do not go into effect desirably due to optical flow estimation error and some other factors. A proper set of the degree of polynomial fitting functions decodes their existence. But how can we estimate that set? Its detailed study is performed. Zero flow, single flow, multiple flows, and interesting events are detected as frame basis using thresholds on the polynomial fitting measure values. Plausible mean outputs of recall rate (88.9%), precision rate (86.7%), area under the receiver operating characteristic curve (98.9%), and accuracy (92.9%) reported from conducted experiments on PETS2009 and UMN benchmark datasets make clear and visible that our method gains high-quality results to detect flows and events in crowd videos in terms of both robustness and potency.

Over the last 40 years, the design of $n$-dimensional hyperchaotic systems with a maximum number ($n-2$) of positive Lyapunov exponents has been an open problem for research. Nowadays it is not difficult to design $n$-dimensional hyperchaotic systems with less than ($n-2$) positive Lyapunov exponents, but it is still extremely difficult to design an $n$-dimensional hyperchaotic system with the maximum number ($n-2$) of positive Lyapunov exponents. This paper aims to resolve this challenging problem by developing a chaotification approach using average eigenvalue criteria. The approach consists of four steps: (i) a globally bounded controlled system is designed based on an asymptotically stable nominal system with a uniformly bounded controller; (ii) a closed-loop pole assignment technique is utilized to ensure that the numbers of eigenvalues with positive real parts of the controlled system be equal to ($n-1$) and ($n-2$), respectively, at two saddle-focus equilibrium points; (iii) the number of average eigenvalues with positive real parts is ensured to be equal to ($n-2$) for the controlled system over a given control period; (iv) the smallest value of the positive real parts of the average eigenvalues is ensured to be greater than a given threshold value. Finally, the paper is closed with some typical examples which illustrate the feasibility and performance of the proposed design methodology.

To enhance the efficiency of malicious intrusion detection of network communication, a malicious intrusion detection model for the network communication in cloud data center is designed. Firstly, the data preprocessing includes three parts: normal sample data modeling, standard data membership calculation and standard data membership calculation. Then, the characteristic value collection stage is completed. Finally, the intrusion detection classification and trust value calculation are completed to conclude the malicious intrusion detection of the network communication in cloud data center. Exploratory findings show that the malicious intrusion detection model for the network communication in cloud data center improves the intrusion detection rate, and reduces the detection time and false alarm rate.

Our objective is to describe the speech production system from a non-linear physiological system perspective and reconstruct the attractor from the experimental speech data. Mutual information method is utilized to find out the time delay for embedding. The False Nearest Neighbour (FNN) method and Principal Component Analysis (PCA) method are used for optimizing the embedding dimension of time series. The time series obtained from the typical non-linear systems, Lorenz system and Rössler system, is used to standardize the methods and the Malayalam speech vowel time series of both genders of different age groups, sampled at three sampling frequencies (16kHz, 32kHz, 44.1kHz), are taken for analysis. It was observed that time delay varies from sample to sample and, it ought to be better to figure out the time delay with the embedding dimension analysis. The embedding dimension is shown to be independent of gender, age and sampling frequency and can be projected as five. Hence a five-dimensional hyperspace will probably be adequate for reconstructing attractor of speech time series.

This paper deals with the linear stability analysis of sandwich plates modeled as thin plates resting on elastic media. To compute the elastic buckling coefficient of sandwich plates, equations have been presented in the literature by using a coefficient R, which relates the rigidity of facing to the core. In the finite element analysis, if the sandwich plates are to be modeled as plates supported by Winkler elastic springs, the relative rigidity R cannot be directly used to represent the stiffness of the Winkler springs. Instead, the stiffness of the core has to be expressed as a modulus of subgrade/core reaction. Furthermore, the R value cannot be directly used in a finite element postbuckling analysis of sandwich plates. In this study, an empirical relation between modulus of core reaction and the R value is established. This is then used in the finite element computation of buckling loads of sandwich panels. This modulus of core reaction can be directly used in the linear buckling analysis of sandwich plates as well as the postbuckling analysis using finite elements.

This paper investigates the prebuckling dynamics of transversely isotropic thin cylinder shells in the context of propagation and reflection of axial stress waves. By constructing the Hamiltonian system of the governing equation, the symplectic eigenvalues and eigenfunctions are obtained directly and rationally without the need for any trial shape functions, such as the classical semi-inverse method. The critical loads and buckling models are reduced to the problem of eigenvalues and eigensolutions, in which zero-eigenvalue solutions and nonzero-eigenvalue solutions correspond to axisymmetric buckling and nonaxisymmetric buckling, respectively. Numerical results reveal that energy is concentrated at the unconstrained free ends of the shell and the buckling modes have bigger bell-mouthed shapes at these positions.

This paper presents a topology optimization method for dynamic problems with an improved bi-directional evolutionary structural optimization (BESO) technique. The sensitivity derivation for the frequency optimization problem in the case of multiple eigenvalues and for the stiffness–frequency optimization problem is proposed. Algorithms for a filter scheme, sensitivity history-averaging, and sensitivity global-ranking are used in the present method. Techniques for adaptively removing alternative elements and eliminating singular and single-hinged elements are proposed. Solution-convergence and localized modes are discussed through numerical examples. Results show that the improved BESO method is capable of solving the frequency optimization problem and the multi-objective optimization problem for stiffness and frequency effectively.

The variation of the instantaneous frequencies of bridges under moving vehicles is a problem not well studied in the literature. A theoretical framework is presented for the problem, considering the variation in frequencies for both the bridge and moving vehicle. First, the equations of motion are written for the two sub-systems. By solving the eigenvalue problem, analytical solutions in closed-form are derived from the frequencies of the vehicle and bridge that are coupled with each other. Based on this, the variation pattern, range, and dominating factors involved are studied, along with the special cases of moving mass and moving load. The results reveal that, if a moving vehicle is to be used as a tool for measuring the bridge frequencies or for detecting the bridge damages, the frequency variation caused by moving vehicles should be taken into account. Such an effect will be crucial when the vehicle mass is not negligible compared with the bridge mass or when the resonance condition is approached.

Eigenvalues and eigenvectors are widely used in various applications. Particularly, these concepts underlie analysis of consistency of a decision maker’s (DMs) preference knowledge. In real-world problems, DMs knowledge is inherently associated with imprecision and partial reliability. This involves combination of fuzzy and probabilistic information. The concept of a Z-number is a formal construct to describe such kind of information. In this study, we formulate the concepts of Z-number valued eigenvalue and eigenvector for matrices components of which are Z-numbers. A formal statement of the problem and a solution method for computation of Z-number valued eigensolutions are proposed. Numerical examples and an application devoted to foreign market selection problem are provided to show the usefulness of the proposed approach.