A Multi Input Multi Output Converter for Hybrid Energy Systems

Multi input and multi output converters are becoming popular because they are cost effective and compact. This paper proposes a multi input multi output converter for Grid-Solar power integration for uninterrupted power supply. The proposed converter uses four winding transformer with two primary windings and two secondary windings. The grid supply is connected to the first winding of transformer through rectifier-inverter for controlled power transfer. The solar energy is inverted and applied to the second winding of primary. Two output ports are considered. The circuit is designed to get zero current switching during turn-off and zero voltage switching during turn-on to alleviate the switching losses. The simulation results for the proposed configuration are presented in this paper.

Walsh Spectral Characteristics and the Auto-Correlation Function Characteristics of Forming Orthomorphic Permutations of Multi-Output Functions

Orthomorphic permutations have good characteristics in cryptosystems. In this paper, by using of knowledge about relation between orthomorphic permutations and multi-output functions, and conceptions of the generalized Walsh spectrum of multi-output functions and the auto-correlation function of multi-output functions to investigate the Walsh spectral characteristics and the auto-correlation function characteristics of orthormophic permutations, several results are obtained.

Application of multi-outputs LSSVR by PSO to the aero-engine model

Considering the modeling errors of on-board self-tuning model in the fault diagnosis of aero-engine, a new mechanism for compensating the model outputs is proposed. A discrete series predictor based on multi-outputs least square support vector regression （LSSVR） is applied to the compensation of on-board self-tuning model of aero-engine, and particle swarm optimization （PSO） is used to the kernels selection of multi-outputs LSSVR. The method need not reconstruct the model of aero-engine because of the differences in the individuals of the same type engines and engine degradation after use. The concrete steps for the application of the method are given, and the simulation results show the effectiveness of the algorithm.

Cloud removal of remote sensing image based on multi-output support vector regression

Removal of cloud cover on the satellite remote sensing image can effectively improve the availability of remote sensing images. For thin cloud cover, support vector value contourlet transform is used to achieve multi-scale decomposition of the area of thin cloud cover on remote sensing images. Through enhancing coefficients of high frequency and suppressing coefficients of low frequency, the thin cloud is removed. For thick cloud cover, if the areas of thick cloud cover on multi-source or multi-temporal remote sensing images do not overlap, the multi-output support vector regression learning method is used to remove this kind of thick clouds. If the thick cloud cover areas overlap, by using the multi-output learning of the surrounding areas to predict the surface features of the overlapped thick cloud cover areas, this kind of thick cloud is removed. Experimental results show that the proposed cloud removal method can effectively solve the problems of the cloud overlapping and radiation difference among multi-source images. The cloud removal image is clear and smooth.

Relationship between Multi-Output Partially Bent Functions and Multi-Output Bent Functions

In this paper, the definition of multl-output partially Bent functions is presented and some properties are discussed. Then the relationship between multi-output partially Bent functions and multi-output Bent functions is given in Theorem 4, which includes Walsh spectrum expression and function expression. This shows that multi-output partially Bent functions and multi-output Bent functions can define each other in principle. So we obtain the general method to construct multi-output partially Bent functions from multi-output Bent functions.

Correlation Degree and Correlation Coefficient of Multi-Output Functions

We present definitions of the correlation degree and correlation coefficient of multi-output functions. Two relationships about the correlation degree of multi-output functions are proved. One is between the correlation degree and independency, the other is between the correlation degree and balance. Especially the paper discusses the correlation degree of affine multioutput functions. We demonstrate properties of the correlation coefficient of multi-output functions. One is the value range of the correlation coefficient, one is the relationship between the correlation coefficient and independency, and another is the sufficient and necessary condition that two multi-output functions are equivalent to each other.

Robust Leader-Following Output Regulation of Uncertain Multi-Agent Systems With Time-Varying Delay

In this paper, the robust analysis and design of leader-following output regulation for multi-agent systems described by general linear models is given in presence of timevarying delay and model uncertainty. To this aim, a new regulation protocol for the closed-loop multi-agent system under a directed graph is proposed. An important specification of the proposed protocol is to guarantee the leader-following output regulation for uncertain multi-agent systems with both stable and unstable agents. Since many signals can be approximated by a combination of the stationary and ramp signals, the presented results work for adequate variety of the leaders. The analysis and design conditions are presented in terms of certain matrix inequalities. The method proposed can be used for both stationary and ramp leaders. Simulation results are presented to show the effectiveness of the proposed method.

IMPROVEMENT OF THE ALGORITHM PRINCIPLES FOR MINIMIZATION OF MULTI-OUTPUT FUNCTIONS

In this paper,the application of extraction principle for logic function minimiza-tion to multi-output case is studied.A defect in original algorithm in dealing with multi-outputextrema is made up,and on this base,three kinds of less-than terms in different conditions aredefined.In addition,three kinds of generalized definition of less-than terms are given,so as to findout more efficiently the covers with minimal number of terms and irredundant function outputs.This work makes the multi-output extraction principle closer to perfection.An algorithm basedon the work is presented.

Spectral Characteristics of the Best Affine Approach of Multi-Output m-Valued Logical Functions

This paper discusses the best affine approach （BAA） of multi-output m-valued logical functions. First, it gives the spectra of rate of accordance between multi-output m-valued logical functions and their affine functions, then analyzes the BAA of multi-output m-valued logical functions and finally gives the spectral characteristics of BAA of multi-output m-valued logical functions.

Analysis on Output Power for Multi-direction Piezoelectric Vibration Energy Harvester

To predict the performance of multi-direction piezoelectric vibration energy harvester,an equation for calculating its output power is obtained based on elastic mechanics theory and piezoelectricity theory.Experiments are performed to verify theoretical analysis.When the excitation direction is along Y direction,a maximal output power about 0.139 mW can be harvested at a resistive load of 65kΩ and an excitation frequency of 136 Hz.Theoretical analysis agrees well with experimental results.Furthermore,the performance of multi-direction vibration energy harvester is experimentally tested.The results show that the multi-direction vibration energy harvester can harvest perfect energy as the excitation direction changes in XY plane,YZ plane,XZ plane and body diagonal plane of the harvester.

APPLICATION OF FRF ESTIMATOR BASED ON ERRORS-IN-VARIABLES MODEL IN MULTI-INPUT MULTI-OUTPUT VIBRATION CONTROL SYSTEM

The FRF estimator based on the errors-in-variables （EV） model of multi-input multi-output （MIMO） system is presented to reduce the bias error of FRF HI estimator. The FRF HI estimator is influenced by the noises in the inputs of the system and generates an under-estimation of the true FRF. The FRF estimator based on the EV model takes into account the errors in both the inputs and outputs of the system and would lead to more accurate FRF estimation. The FRF estimator based on the EV model is applied to the waveform replication on the 6-DOF （degree-of-freedom） hydraulic vibration table. The result shows that it is favorable to improve the control precision of the MIMO vibration control system.

Performance Improvement of Multi-User Multiple-Input Multiple-Output Protocol for WLAN

The increase in the number of devices with a massive revolution in mobile technology leads to increase the capacity of the wireless communications net-works. Multi-user Multiple-Input Multiple-Output is an advanced procedure of Multiple-Input Multiple-Output, which improves the performance of Wireless Local Area Networks. Moreover, Multi-user Multiple-Input Multiple-Output leads the Wireless Local Area Networks toward covering more areas. Due to the growth of the number of clients and requirements, researchers try to improve the performance of the Medium Access Control protocol of Multi-user Multiple-Input Multiple-Output technology to serve the user better, by supporting different data sizes, and reducing the waiting time to be able to transmit data quickly. In this paper, we propose a Clustering Multi-user Multiple-Input Multiple-Output protocol, which is an improved Medium Access Control protocol for Multi-user Multiple-Input Multiple-Out-put based on MIMOMate clustering technique and Padovan Backoff Algorithm. Utilizing MIMOMMate focuses on the signal power which only serves the user in that cluster, minimizes the energy consumption and increases the capacity. The implementation of Clustering Multi-user Multiple-Input Multiple-Output performs on the Network Simulator (NS2.34) platform. The results show that Clustering Multi-user Multiple-Input Multiple-Output protocol improves the throughput by 89.8%, and reduces the latency of wireless communication by 43.9% in scenarios with contention. As a result, the overall performances of the network are improved.

Resilient Fixed-Order Distributed Dynamic Output Feedback Load Frequency Control Design for Interconnected Multi-Area Power Systems

The paper proposes a novel H∞ load frequency control(LFC) design method for multi-area power systems based on an integral-based non-fragile distributed fixed-order dynamic output feedback(DOF) tracking-regulator control scheme. To this end, we consider a nonlinear interconnected model for multiarea power systems which also include uncertainties and timevarying communication delays. The design procedure is formulated using semi-definite programming and linear matrix inequality(LMI) method. The solution of the proposed LMIs returns necessary parameters for the tracking controllers such that the impact of model uncertainty and load disturbances are minimized. The proposed controllers are capable of receiving all or part of subsystems information, whereas the outputs of each controller are local. These controllers are designed such that the resilient stability of the overall closed-loop system is guaranteed. Simulation results are provided to verify the effectiveness of the proposed scheme. Simulation results quantify that the distributed(and decentralized) controlled system behaves well in presence of large parameter perturbations and random disturbances on the power system.

Evaluation of Linear Precoding Schemes for Cooperative Multi-Cell MU MIMO in Future Mobile Communication Systems

In Mobile Communication Systems, inter-cell interference becomes one of the challenges that degrade the system’s performance, especially in the region with massive mobile users. The linear precoding schemes were proposed to mitigate interferences between the base stations (inter-cell). These schemes are categorized into linear and non-linear;this study focused on linear precoding schemes, which are grounded into three types, namely Zero Forcing (ZF), Block Diagonalization (BD), and Signal Leakage Noise Ratio (SLNR). The study included the Cooperative Multi-cell Multi Input Multi Output (MIMO) System, whereby each Base Station serves more than one mobile station and all Base Stations on the system are assisted by each other by shared the Channel State Information (CSI). Based on the Multi-Cell Multiuser MIMO system, each Base Station on the cell is intended to maximize the data transmission rate by its mobile users by increasing the Signal Interference to Noise Ratio after the interference has been mitigated due to the usefully of linear precoding schemes on the transmitter. Moreover, these schemes used different approaches to mitigate interference. This study mainly concentrates on evaluating the performance of these schemes through the channel distribution models such as Ray-leigh and Rician included in the presence of noise errors. The results show that the SLNR scheme outperforms ZF and BD schemes overall scenario. This implied that when the value of SNR increased the performance of SLNR increased by 21.4% and 45.7% for ZF and BD respectively.

A multi-input and multi-output design on automotive engine management system

Lookup table is widely used in automotive industry for the design of engine control units(ECU).Together with a proportional-integral controller,a feed-forward and feedback control scheme is often adopted for automotive engine management system(EMS).Usually,an ECU has a structure of multi-input and single-output(MISO).Therefore,if there are multiple objectives proposed in EMS,there would be corresponding numbers of ECUs that need to be designed.In this situation,huge efforts and time were spent on calibration.In this work,a multi-input and multi-out(MIMO) approach based on model predictive control(MPC) was presented for the automatic cruise system of automotive engine.The results show that the tracking of engine speed command and the regulation of air/fuel ratio(AFR) can be achieved simultaneously under the new scheme.The mean absolute error(MAE) for engine speed control is 0.037,and the MAE for air fuel ratio is 0.069.

Input and output efficiency of urban agglomerations in China using DEA multi-stage model

In this study, we apply the data envelopment analysis(DEA) model to quantitatively measure the input and output efficiency of 19 urban agglomerations in China from 2011 to 2016. The results show that the input and output efficiency of urban agglomerations is relatively not high, only a small number of that reach the optimal DEA efficiency. It is clearly revealed that there are the regions from the east that presents the better performance, followed by regions from the central and the west. The peer counts show that Zhusanjiao is taken into account 12 times which shows the importance here of the Zhusanjiao model.Considering the values for radial movements and the slack movements, respective urban agglomeration has their improving orientation towards the capital slack, the labor slack or the land slack. It offers a scientific decision-making of for healthy urbanization and high quality development.

Embedded Programmable Single Point Multiple Output Intelligent Data Acquisition and Transmission System

To effectively solve the problems of inconsistent communication protocols in automatic monitoring equipment,and limited data acquisition transmission and monitoring equipment,this paper developed programmable single point multiple output intelligent data acquisition and transmission system. It made an in-depth elaboration of the data acquisition and transmission system from hardware design,software architecture and principle,main functions and technical parameters. Finally,it came up with four innovation points:(i) intelligent(automatic)matching a variety of communication protocols for environmental monitoring equipment,(ii) realizing multi-protocol and multi-target parallel data transmission,(iii) realizing remote dynamic input of control instructions through wired or wireless network,and(iv) supporting configuration(process) simulation of field equipment DCS operating conditions.

数字经济对国民经济的引领作用研究——基于多区域投入产出表

为探究数字经济对国民经济发展的作用效果,编制中国数字经济多区域投入产出表,将产业关联系数的计算拓展到多地区多部门情形,并通过定义溢出效应来区分各地区数字经济发展对地区内外经济拉动和推动的差异化效果。研究发现:数字经济对国民经济发展的拉动效应强于推动效应。东部地区已经实现服务业拉动转向数字产业拉动的动力转换,中西部地区则展现了由工业拉动直接转向数字产业拉动经济发展的演变模式;各地区数字经济发展主要拉动和推动本地区经济增长,但数字经济对拉动和推动城市群内部经济协调发展效果显著,如长三角和珠三角等区域;经济发展水平较高地区的数字产业属于“消费依赖型”产业;而工业发达地区和欠发达地区数字经济发展更依赖于投资。研究数字经济与实体经济融合发展具有重要的理论价值与现实意义,据此提出推动数字经济发展的政策参考。

深层特征提取与多输出增强融合的建筑物分割

针对高分辨率遥感影像建筑物语义分割中存在单体建筑部分漏分与纹理相近的非建筑物错分的问题,提出深度特征提取与多输出增强建筑物语义分割网络。首先,在编码与解码交替处设计并行连续空洞空间注意力金字塔模块,对建筑物高维特征实现深层提取;然后,在网络解码阶段设计多输出增强融合模块,提升不同尺度建筑物特征对输出结果的有效参与度。选取U-Net、DeeplabV3+、MA-FCN、BRRNet同类算法进行对比,在Massachusetts和WHU公共数据集上测试,OA、precision、recall、IoU、F1指标分别达到98.87%、94.53%、95.40%、90.41%、94.96%,与同类算法相比,除precision之外其他4项指标更高,与U-Net相比,依次高出0.25%、1.12%、1.14%、2.02%、1.12%。