Research on Landscape Design of Building Information Model in Ecological Restoration Projects of Cities along the Yangtze River

The urban landscape pattern, process and function have three-dimensional characteristics, and the three-dimensional analysis of urban landscape elements is one of the important trends in the development of urban landscape research. However, the current research on the visualization of urban landscape in three dimensions and the application of related models still needs to strengthen. Based on the research of the ecological restoration process, this paper combines the current situation of urban landscape construction along the Yangtze River in China and deduces the development trend of urban landscape planning. Based on Building information model (BIM), this article combines Revit software to design landscape construction drawings, and summarizes the specific design process and the current unsolvable problems. As an experimental building information model (BIM) software construction drawing design attempt, this article explores the urban ecological water conservancy landscape planning and design path, and demonstrates it in combination with specific cases. Therefore, this paper conducts modeling based on three-dimensional virtual landscape, which conducts virtual landscape design and provides technical ideas for the development of this technology

The Multi-object Optimal Pass Design based on MOGA

AbstractThe optimal pass design is based on Multi-Object Genetic Algorithm (GA) with the objective of the least of total energy consumption and loads balance on bar mill. By optimization, in condition of normal rolling, the less total energy consumption and relative balanced bar mill loads. Genetic Algorithm Toolbox with Matlab software is adopted to search optimum parameters, which is a new method for the multi-object optimal pass design

A Class of Semiparametric Models with Homogeneous Structure for Panel Data Analysis

Stimulated by the analysis of a dataset from China about Covid-19, we propose a class of semiparametric models for panel data analysis. The proposed models account for both homogeneity and heterogeneity among the individuals of a panel data. They strike a nice balance between parsimony and risk of misspecification. Although stimulated by the analysis of a particular dataset, the proposed models apply to very broad range of panel data analysis, they are powerful in exploring nonlinear dynamic patterns of impacts of covariates or transformed covariates. An estimation procedure is presented, and its asymptotic properties are established. Intensive simulation studies are also conducted to demonstrate how well the estimation procedure works and the risk of ignoring homogeneity or heterogeneity among individuals in panel data analysis. Finally, we apply the proposed models and estimation procedure to the Covid-19 data from China, and reveal some interesting dynamic patterns of the impacts of some important factors

A green intelligent routing algorithm supporting flexible QoS for many-to-many multicast

The tremendous energy consumption attributed to the Information and Communication Technology (ICT) field has become a persistent concern during the last few years, attracting significant academic and industrial efforts. Networks have begun to be improved towards being “green”. Considering Quality of Service (QoS) and power consumption for green Internet, a Green Intelligent flexible QoS many-to-many Multicast routing algorithm (GIQM) is presented in this paper. In the proposed algorithm, a Rendezvous Point Confirming Stage (RPCS) is first carried out to obtain a rendezvous point and the candidate Many-to-many Multicast Sharing Tree (M2ST); then an Optimal Solution Identifying Stage (OSIS) is performed to generate a modified M2ST rooted at the rendezvous point, and an optimal M2ST is obtained by comparing the original M2ST and the modified M2ST. The network topology of Cernet2, GéANT and Internet2 were considered for the simulation of GIQM. The results from a series of experiments demonstrate the good performance and outstanding power-saving potential of the proposed GIQM with QoS satisfied

Time Domain Equalizer Design Using Bit Error Rate Minimization for UWB Systems

Ultra-wideband (UWB) communication systems occupy huge bandwidths with very low power spectral densities. This feature makes the UWB channels highly rich in resolvable multipaths. To exploit the temporal diversity, the receiver is commonly implemented through a Rake. The aim to capture enough signal energy to maintain an acceptable output signal-to-noise ratio (SNR) dictates a very complicated Rake structure with a large number of fingers. Channel shortening or time domain equalizer (TEQ) can simplify the Rake receiver design by reducing the number of significant taps in the effective channel. In this paper, we first derive the bit error rate (BER) of a multiuser and multipath UWB system in the presence of a TEQ at the receiver front end. This BER is then written in a form suitable for traditional optimization. We then present a TEQ design which minimizes the BER of the system to perform efficient channel shortening. The performance of the proposed algorithm is compared with some generic TEQ designs and other Rake structures in UWB channels. It is shown that the proposed algorithm maintains a lower BER along with efficiently shortening the channel