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  • Performance Analysis of Intelligent CR-NOMA Model for Industrial IoT Communications
  • Abstract Aiming for ultra-reliable low-latency wireless communications required in industrial internet of things (IIoT) applications, this paper studies a simple cognitive radio non-orthogonal multiple access (CR-NOMA) downlink system. This system consists of two secondary users (SUs) dynamically interfered by the primary user (PU), and its performance is characterized by the outage probability of the SU communications. This outage probability is calculated under two conditions where, a) the transmission of PU starts after the channel state information (CSI) is acquired, so the base station (BS) is oblivious of the interference, and b) when the BS is aware of the PU interference, and…
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  • Exploring the Abnormal Brain Regions and Abnormal Functional Connections in SZ by Multiple Hypothesis Testing Techniques
  • Abstract Schizophrenia (SZ) is one of the most common mental diseases. Its main characteristics are abnormal social behavior and inability to correctly understand real things. In recent years, the magnetic resonance imaging (MRI) technique has been popularly utilized to study SZ. However, it is still a great challenge to reveal the essential information contained in the MRI data. In this paper, we proposed a biomarker selection approach based on the multiple hypothesis testing techniques to explore the difference between SZ and healthy controls by using both functional and structural MRI data, in which biomarkers represent both abnormal brain functional connectivity and…
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  • A Novel Binary Firey Algorithm for the Minimum Labeling Spanning Tree Problem
  • Abstract Given a connected undirected graph G whose edges are labeled, the minimum labeling spanning tree (MLST) problem is to find a spanning tree of G with the smallest number of different labels. The MLST is an NP-hard combinatorial optimization problem, which is widely applied in communication networks, multimodal transportation networks, and data compression. Some approximation algorithms and heuristics algorithms have been proposed for the problem. Firey algorithm is a new meta-heuristic algorithm. Because of its simplicity and easy implementation, it has been successfully applied in various fields. However, the basic firefly algorithm for the MLST problem is proposed in this…
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  • Short-Term Traffic Flow Prediction Based on LSTM-XGBoost Combination Model
  • Abstract According to the time series characteristics of the trajectory history data, we predicted and analyzed the traffic flow. This paper proposed a LSTMXGBoost model based urban road short-term traffic flow prediction in order to analyze and solve the problems of periodicity, stationary and abnormality of time series. It can improve the traffic flow prediction effect, achieve efficient traffic guidance and traffic control. The model combined the characteristics of LSTM (Long Short-Term Memory) network and XGBoost (Extreme Gradient Boosting) algorithms. First, we used the LSTM model that increases dropout layer to train the data set after preprocessing. Second, we replaced the…
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  • Ziegler–Nichols Customization for Quadrotor Attitude Control under Empty and Full Loading Conditions
  • Abstract An aircraft quadrotor is a complex control system that allows for great flexibility in flight. Controlling multirotor aerial systems such as quadrotors is complex because the variables involved are not always available, known, and accurate. The inclusion of payload changes the dynamic characteristics of the aircraft, making it necessary to adapt the control system for this situation. Among the various control methods that have been investigated, proportional-integralderivative (PID) control offers good results and simplicity of application; however, achieving stability and high performance is challenging, with the most critical task being tuning the controller gains. The Ziegler–Nichols (ZN) theory was used…
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  • The Efficient Finite Element Methods for Time-Fractional Oldroyd-B Fluid Model Involving Two Caputo Derivatives
  • Abstract In this paper, we consider the numerical schemes for a timefractional Oldroyd-B fluid model involving the Caputo derivative. We propose two efficient finite element methods by applying the convolution quadrature in time generated by the backward Euler and the second-order backward difference methods. Error estimates in terms of data regularity are established for both the semidiscrete and fully discrete schemes. Numerical examples for two-dimensional problems further confirm the robustness of the schemes with first- and second-order accurate in time.
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  • Simulation Analysis on Mechanical Property Characterization of Carbon Nanotubes Reinforced Epoxy Composites
  • Abstract Carbon nanotube (CNT)-reinforced composites have ultra-high elastic moduli, low densities, and fibrous structures. This paper presents the multi-scale finite element modeling of CNT-reinforced polymer composites from micro- to macro-scales. The nanocomposites were modeled using representative volume elements (RVEs), and finite element code was written to simulate the modeling and loading procedure and obtain equivalent mechanical properties of the RVEs with various volume fractions of CNTs, which can be used directly in the follow-up simulation studies on the macroscopic model of CNT-reinforced nanocomposites. When using the programming to simulate the deformation and fracture process of the CNT-reinforced epoxy composites, the mechanical…
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  • Deep Residual Network Based on Image Priors for Single Image Super Resolution in FFA Images
  • Abstract Diabetic retinopathy, aged macular degeneration, glaucoma etc. are widely prevalent ocular pathologies which are irreversible at advanced stages. Machine learning based automated detection of these pathologies facilitate timely clinical interventions, preventing adverse outcomes. Ophthalmologists screen these pathologies with fundus Fluorescein Angiography Images (FFA) which capture retinal components featuring diverse morphologies such as retinal vasculature, macula, optical disk etc. However, these images have low resolutions, hindering the accurate detection of ocular disorders. Construction of high resolution images from these images, by super resolution approaches expedites the diagnosis of pathologies with better accuracy. This paper presents a deep learning network for Single…
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  • Prediction of Intrinsically Disordered Proteins with a Low Computational Complexity Method
  • Abstract The prediction of intrinsically disordered proteins is a hot research area in bio-information. Due to the high cost of experimental methods to evaluate disordered regions of protein sequences, it is becoming increasingly important to predict those regions through computational methods. In this paper, we developed a novel scheme by employing sequence complexity to calculate six features for each residue of a protein sequence, which includes the Shannon entropy, the topological entropy, the sample entropy and three amino acid preferences including Remark 465, Deleage/Roux, and Bfactor(2STD). Particularly, we introduced the sample entropy for calculating time series complexity by mapping the amino…
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  • Periodic Lattice Porous Structure Produced by Selective Laser Melting: Process, Experiment and Numerical Simulation Analysis
  • Abstract To accurately perform the coupled simulation of temperature field and stress field of complex parts and porous structures under the optimal manufacturing process parameters, three kinds of porous structures with different complexity were designed in this paper. Firstly, ANSYS additive software was used to conduct the stress/deformation simulation of the whole structure under different scanning strategies. Secondly, the optimal scanning strategy for different porous structures was determined, then the experimental preparation was performed, and mechanical properties of compression were tested and studied. The results show that the elastic modulus and yield strength increase with the increase of pole diameter/wall thickness.…
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