Based on stability theory of linear fractional order systems and stability theory of linear integer order systems, the problem of coexistence of various types of synchronization between different dimensional fractional chaotic systems is investigated in this paper. Numerical and simulation results have clearly shown the effectiveness of the novel approach developed herein. © 2018, Springer International Publishing AG.

The integration of biometric recognition with smartphones is necessary to increase security, especially in financial transactions such as online payments. Vein recognition of the dorsal hand is superior to other methods such as palm, finger, and wrist, as it has a wide area to be captured and does not have any wrinkles. Most current systems that depend on dorsal hand vein recognition do not work in real-time and have poor results. In this paper, a dorsal hand recognition system working in real-time is proposed to achieve good results with a high frame rate. A contactless device consists of a

Purpose: Tagged and cine magnetic resonance imaging (tMRI and cMRI) techniques are used for evaluating regional and global heart function, respectively. Measuring global function parameters directly from tMRI is challenging due to the obstruction of the anatomical structure by the tagging pattern. The purpose of this study was to develop a method for processing the tMRI images to improve the myocardium-blood contrast in order to estimate global function parameters from the processed images. Materials and methods: The developed method consists of two stages: (1) removing the tagging pattern

In this paper, we study a wireless powered cellular network (WPCN) supported with network coding capability. In particular, we consider a network consisting of k cellular users (CUs) served by a hybrid access point (HAP) that takes over energy transfer to the users on top of information transmission over both the uplink (UL) and downlink (DL). Each CU has k+1 states representing its communication behavior, and collectively are referred to as the user demand profile. Opportunistically, when the CUs have information to be exchanged through the HAP, it broadcasts this information in coded format

This study targets an order fulfillment problem in a freight forwarding company. Some applicable solutions are implemented such as supplier performance evaluation, suppliers' selection, and location analytics. The objective of the study is to reduce the number of unfulfilled orders by supply planning. Some of the tools used to achieve this are Excel (VBA and Pivot tables) to perform drivers' scoring, analytic hierarchy process (AHP), and ArcGIS software to visualize locations. The results showed that the company can implement the suggested solutions to reduce the number of order cancellations

Objectives: This study sought to evaluate the diagnostic accuracy of strain-encoded cardiac magnetic resonance (SENC) for the detection of inducible ischemia during intermediate stress. Background: High-dose dobutamine stress cardiac magnetic resonance (DS-CMR) is a well-established modality for the noninvasive detection of coronary artery disease (CAD). However, the assessment of cine scans relies on the visual interpretation of wall motion, which is subjective, and modalities that can objectively and quantitatively assess the time course of myocardial strain response during stress are

In this research, an approximation symbolic algorithm is suggested to obtain an approximate solution of multipantograph system of type delay differential equations (DDEs) using a combination of Laplace transform and variational iteration algorithm (VIA). The corresponding convergence results are acquired, and an efficient algorithm for choosing a feasible Lagrange multiplier is designed in the solving process. The application of the Laplace variational iteration algorithm (LVIA) for the problems is clarified. With graphics and tables, LVIA approximates to a high degree of accuracy with a few

The Internet of Things (IoT) is an Internet revolution that is increasingly used in business, industry, medicine, the economy and other modern information society. IoT, particularly transport, industrial robots and automation systems are supported by artificial intelligence in a wide range of daily implementations with dominant industrial applications. IoT is an interconnected network of physical objects, which enables them to gather and share information, using software, sensor units and network connectivity. In industries; IoT brought about a new revolution in industries. In the field of IoT

Semantic segmentation of 3D point cloud data is essential for enhanced high-level perception in autonomous platforms. Furthermore, given the increasing deployment of LiDAR sensors onboard of cars and drones, a special emphasis is also placed on non-computationally intensive algorithms that operate on mobile GPUs. Previous efficient state-of-the-art methods relied on 2D spherical projection of point clouds as input for 2D fully convolutional neural networks to balance the accuracy-speed trade-off. This paper introduces a novel approach for 3D point cloud semantic segmentation that exploits

Pseudo-random number generator (PRNG) are a key component in the design of modern cryptographic mechanisms and are regarded as a backbone element of many modern cryptographic applications. However and in spite of their robustness, quantum computers could crack down PNGR-based systems. Quantum walks, a universal model of quantum computation, have nonlinear properties that make them a robust candidate to produce PRNG. In this paper, we utilize controlled alternate quantum walk (CAQW) to create PRNG. Moreover, we use the presented PRNG mechanism as a component of a new quantum color image