An Optimization Sizing Model for Solar Photovoltaic Power Generation System with Pumped Storage

AbstractIn this study, a novel sizing model for the solar photovoltaic system with pumped storage is proposed, to optimize the capacity of the PV generator and pumped storage system for power supply in remote areas. The genetic algorithm is then employed to optimize sizing system with respect to the system total cost. The variables considered in the optimization process include PV module number, upper reservoir size and water pump size. With the developed model, a technically and economically feasible power supply solution can be achieved easily. The proposed model is finally applied to a case study on renewable energy power generation system for an island, and the optimization performance has been demonstrated

Theoretical study on hydrogen storage capacity of expanded h-BN systems

In this work, the hydrogen storage capacity of the expanded hexagonal Boron Nitride (eh-BN) systems has been presented. We have employed a new equation of state (EOS) for hydrogen gas to figure out the hydrogen density distribution profiles in the eh-BN systems. In this regard, the environmental conditions (i.e., temperature and pressure) are considered in the prediction procedure using DFT single point calculations. The eh-BN systems with different layer spacings are studied by PBE method with consideration of the long range dispersion corrections. On account of the in-plane polar bonds, a series of adsorption positions are considered. Additionally, the adsorption energy and hydrogen density profiles are reported. Furthermore, the relation between uptakes and the interlayer spacings with the effects of the environmental conditions are also provided. The limit of the physical hydrogen storage capacity in a perfect eh-BN system at 243 K and 10 MPa is founded to be 2.96 wt.%.--//--eng Fu, Jing Wang, Ran Jia, Shamsa Bibi, Roberts I. Eglitis, Hong-Xing Zhang, Theoretical study on hydrogen storage capacity of expanded h-BN systems, Computational Materials Science, Volume 139, 2017, Pages 335-340, ISSN 0927-0256, https://doi.org/10.1016/j.commatsci.2017.08.015 published under the CC BY licence.Institute of Solid State Physics, University of Latvia as the Center of Excellence has received funding from the European Union’s Horizon 2020 Framework Programme H2020-WIDESPREAD-01-2016-2017 TeamingPhase2 under grant agreement No. 739508, project CAMART2

Crop pest image classification based on improved densely connected convolutional network

IntroductionCrop pests have a great impact on the quality and yield of crops. The use of deep learning for the identification of crop pests is important for crop precise management.MethodsTo address the lack of data set and poor classification accuracy in current pest research, a large-scale pest data set named HQIP102 is built and the pest identification model named MADN is proposed. There are some problems with the IP102 large crop pest dataset, such as some pest categories are wrong and pest subjects are missing from the images. In this study, the IP102 data set was carefully filtered to obtain the HQIP102 data set, which contains 47,393 images of 102 pest classes on eight crops. The MADN model improves the representation capability of DenseNet in three aspects. Firstly, the Selective Kernel unit is introduced into the DenseNet model, which can adaptively adjust the size of the receptive field according to the input and capture target objects of different sizes more effectively. Secondly, in order to make the features obey a stable distribution, the Representative Batch Normalization module is used in the DenseNet model. In addition, adaptive selection of whether to activate neurons can improve the performance of the network, for which the ACON activation function is used in the DenseNet model. Finally, the MADN model is constituted by ensemble learning.ResultsExperimental results show that MADN achieved an accuracy and F1Score of 75.28% and 65.46% on the HQIP102 data set, an improvement of 5.17 percentage points and 5.20 percentage points compared to the pre-improvement DenseNet-121. Compared with ResNet-101, the accuracy and F1Score of MADN model improved by 10.48 percentage points and 10.56 percentage points, while the parameters size decreased by 35.37%. Deploying models to cloud servers with mobile application provides help in securing crop yield and quality

I/Q Imbalance and Imperfect SIC on Two-way Relay NOMA Systems

Abstract: Non-orthogonal multiple access (NOMA) system can meet the demands of ultra-high data rate, ultra-low latency, ultra-high reliability and massive connectivity of user devices (UE). However, the performance of the NOMA system may be deteriorated by the hardware impairments. In this paper, the joint effects of in-phase and quadrature-phase imbalance (IQI) and imperfect successive interference cancellation (ipSIC) on the performance of two-way relay cooperative NOMA (TWR C-NOMA) networks over the Rician fading channels are studied, where two users exchange information via a decode-and-forward (DF) relay. In order to evaluate the performance of the considered network, analytical expressions for the outage probability of the two users, as well as the overall system throughput are derived. To obtain more insights, the asymptotic outage performance in the high signal-to-noise ratio (SNR) region and the diversity order are analysed and discussed. Throughout the paper, Monte Carlo simulations are provided to verify the accuracy of our analysis. The results show that IQI and ipSIC have significant deleterious effects on the outage performance. It is also demonstrated that the outage behaviours of the conventional OMA approach are worse than those of NOMA. In addition, it is found that residual interference signals (IS) can result in error floors for the outage probability and zero diversity orders. Finally, the system throughput can be limited by IQI and ipSIC, and the system throughput converges to a fixed constant in the high SNR region

Realization of Embedded Multimedia System Based On Dual-Core Processor OMAP5910

This paper focuses on the realization of a complete embedded system using the dual-core processor OMAP5910. Detailed description of how to compose the hardware system is presented with a description of the software system on our platform. Tasks communication between the two cores is realized using the DSP driver. The system bootloader and the DSP bootloader are described in detail. The implementation of the MPEG-4 video decoder has been realized on the presented system. Higher speed can be achieved and less power is needed for MPEG-4 video processing on the dual-core platform. This dual-core system can be applied to 3G wireless communication, robot control and vision systems

A Unified Framework for HS-UAV NOMA Networks: Performance Analysis and Location Optimization

In this paper, we propose a unified framework for hybrid satellite/unmanned aerial vehicle (HS-UAV) terrestrial non-orthogonal multiple access (NOMA) networks, where satellite aims to communicate with ground users with the aid of a decode-forward (DF) UAV relay by using NOMA protocol. All users are randomly deployed to follow a homogeneous Poisson point process (PPP), which is modeled by the stochastic geometry approach. To reap the benefits of satellite and UAV, the links of both satellite-to-UAV and UAV-to-ground user are assumed to experience Rician fading. More practically, we assume that perfect channel state information (CSI) is infeasible at the receiver, as well as the distance-determined path-loss. To characterize the performance of the proposed framework, we derive analytical approximate closed-form expressions of the outage probability (OP) for the far user and the near user under the condition of imperfect CSI. Also, the system throughput under delay-limited transmission mode is evaluated and discussed. In order to obtain more insights, the asymptotic behavior is explored in the high signal-to-noise ratio (SNR) region and the diversity orders are obtained and discussed. To further improve the system performance, based on the derived approximations, we optimize the location of the UAV to maximize the sum rate by minimizing the average distance between the UAV and users. The simulated numerical results show that: i) there are error floors for the far and the near users due to the channel estimation error; ii) the outage probability decreases as the Rician factor K increasing, and iii) the outage performance and system throughput performance can be further improved considerably by carefully selecting the location of the UAV

An Efficient Spectral Element Model with Electric DOFs for the Static and Dynamic Analysis of a Piezoelectric Bimorph

An efficient spectral element (SE) model for static and dynamic analysis of a piezoelectric bimorph is proposed. It combines an equivalent single layer (ESL) model for the mechanical displacement field with a sublayer approximation for the electric potential. The 2D Gauss-Lobatto-Legendre (GLL) shape functions are used to discretize the displacements and then the governing equation of motion is derived following the standard SE method procedure. It is shown numerically that the present SE model can well predict both the global and local responses such as mechanical displacements, natural frequencies, and the electric potentials across the bimorph thickness. In the case of bimorph sensor application, it is revealed that the distribution of the induced electric potential across the thickness does not affect the global natural frequencies much. Furthermore, the effects of the order of Legendre polynomial and the mesh size on the convergence rate are investigated. Comparison of the present results for a bimorph sensor with those from 3D finite element (FE) simulations establishes that the present SE model is accurate, robust, and computationally efficient

COVERT COMMUNICATION FOR COOPERATIVE NOMA WITH TWO PHASES DETECTION

This paper investigates the covert communication of cooperative non-orthogonal multiple access (NOMA) systems, where the near user serves as a decode-and-forward (DF) relay and the far user receives the covert information from both the source and the near user. To improve the covertness performance, cooperative jamming and power randomness are adopted. Specifically, we derive detection error probability (DEP) of Willie and the minimum detection error probability (MDEP) at the optimal decision threshold for each phase. In addition, the reliability of the proposed system is investigated by deriving closed-form expressions for the outage probability (OP) of the two users. Under the covertness and reliability constraints, an optimization algorithm to maximize the effective covert rate is designed. Simulation results have confirmed the correctness of the theoretical analysis, and the proposed scheme can achieve a better covert communication