Design Strategies for Landscape Transformation of Abandoned Railways in Urban Centers

The railways have significantly contributed to the economic development of the city.However,with the evolution of the city and adjustments in the industrial structure,the relocation and rerouting of major railway trunk lines have resulted in the abandonment of numerous urban railways.The abandoned railways,resulting from inadequate management,have transformed into sites for waste disposal and are particularly vulnerable to environmental issues,including land pollution,degradation of vegetation cover,and a decline in ecological diversity.Abandoned railways in urban centers significantly hinder transportation connectivity and adversely influence the aesthetic appeal of the city.The landscape transformation of these abandoned railways is of paramount importance in the context of urban renewal.These railway sites possess significant potential for stock utilization as specialized,underutilized spaces.Through the processes of re-planning,integration,and renewal,previously underutilized spaces can be revitalized and incorporated into the urban landscape in innovative ways.This approach not only enhances the availability of green leisure areas for residents but also contributes to the realization of sustainable urban development.

Refuting the Misconception:Li Bai as an Impolite Person

This essay endeavors to dispel the lingering misconception that Li Bai,the celebrated Tang Dynasty poet,was a man devoid of propriety.Through a meticulous examination of historical records,literary works,and contemporary interpretations,this study presents a nuanced portrait of Li Bai as a poet who,despite his eccentricities and wanderlust,possessed a profound sense of etiquette and respect for societal norms.This essay argues that his unique personality in life and free expression in poetry are all driven by the need for artistic creation,rather than challenging for ancient propriety.

Parameter-Free Shifted Laplacian Reconstruction for Multiple Kernel Clustering

Dear Editor,This letter proposes a parameter-free multiple kernel clustering(MKC)method by using shifted Laplacian reconstruction.Traditional MKC can effectively cluster nonlinear data,but it faces two main challenges:1)As an unsupervised method,it is up against parameter problems which makes the parameters intractable to tune and is unfeasible in real-life applications;2)Only considers the clustering information,but ignores the interference of noise within Laplacian.

An Analysis on the Blended Teaching Mode of College English

This paper explores blended teaching in college English from five aspects:the connotation,theoretical basis,design principles,advantages,and challenges of blended teaching and blended teaching models.The purpose is to attract more foreign language practitioners and learners to pay attention to this model and put it into practice.

Design of Wuzhou Arcade Naturalist City Display Based on 3D Panoramic Technology

This paper taking Wuzhou arcade naturalist city as design sight spot, made a on location shoot on the streetscape of arcade naturalist city. then synthesized them by software in panoramic way. to create a multimedia virtual exhibition platform. This paper has explored the used digital software and forms of artistic expression in this system, summed up the experience in the production of shooting, image stitching, and image post-processing as well ss art design, and finally combined with the Lingnan culture features to design the arcade naturalist city show platform.

Air Pollution, Global Warming and Difficulties to Replace Fossil Fuel with Renewable Energy

Since the Industrial Revolution, greenhouse gas (GHG) emissions have greatly increased with the increased use of fossil fuels, leading to air pollution and global warming. We present the researches on air pollution and the use of fossil fuels in north China, the economic zone of Changsha-Zhuzhou-Xiangtan and the economic zone of the Pearl River Delta region. Researches indicate that the use of fossil fuels has been the main source of air pollution in the three regions. We present researches on global mean surface temperature (GMST) with the rise of carbon dioxide concentration (CDC) and global fossil fuel consumption (GFFC);researches indicate that the rise in CDC can account for 91% of the rise in GMST, and GFFC can account for 90% of the rise in GMST. We analyse the factors that bring about air pollution and temperature rise, they are the use of fossil fuels and deforestation. It is critically important to replace fossil fuels with clean energy, but renewable energy has also disadvantages. The world faces difficulties in solving air pollution and global warming, so governments of the world should cooperate to solve the technologies of clean energy, and preserve the forests and the natural environment.

Anthropogenic Climate Change, Deforestation and Renewable Energy

Since the Industrial Revolution, greenhouse gas (GHG) emission, especially global CO2 emission (GCE) has greatly increased with the growth of global human population (GHP), which has caused climate change. Both GCE and GHP are positively related with the rise of global mean surface temperature (GMST). Our empirical research shows that the impact from GCE on GMST is 7.72 times of that from TSI, and the impact from GHP on GMST is 7.9 times of that from TSI. The growth rate of global surface temperature was slower from 1998 to 2012, which was mainly caused by the decadal cooling of the tropical Pacific Ocean-La Niña. Deforestation and vegetation degradation affect climate change, feedback radiation between the atmosphere and the biosphere account for 30% of the variation in global surface radiation and precipitation. The share of renewable energy remains small in primary energy consumption due to their disadvantages.

Oscillation of Third-order Delay Dynamic Equations on Time Scales

This paper is concerned with the oscillatory behavior of a class of third-order noonlinear variable delay neutral functional dynamic equations on time scale. By using the generalized Riccati transformation and inequality technique, we establish some new oscilla- tion criteria for the equations. Our results extend and improve some known results, but also unify the oscillation of third-order nonlinear variable delay functional differential equations and functional difference equations with a nonlinear neutral term. Some examples are given to illustrate the importance of our results.

Performance Analysis of NOMA-Based Cooperative Networks with Relay Selection

Non-orthogonal multiple access(NOMA)technique is an expert on channel differences exploiting.In this paper,a dual-hop NOMA-based cooperative relaying network where a best relay is selected as an active node to accomplish the communication between a source and a destination is discussed.We assume that both decode-and-forward(DF)and amplify-and-forward(AF)protocols are applied to the selected relay.The metrics that ergodic sum-rate and outage probability are investigated,and the closed-form expressions of the latter for DF and AF protocols are derived.Numerical and simulation results are conducted to verify the validity of the theoretical analysis,in which we can see that the NOMA based DF relaying is better than the NOMA based AF relaying and other existing NOMA-based cooperative communication schemes.

A Lightweight Model of VGG-U-Net for Remote Sensing Image Classification

Remote sensing image analysis is a basic and practical research hotspot in remote sensing science.Remote sensing images contain abundant ground object information and it can be used in urban planning,agricultural monitoring,ecological services,geological exploration and other aspects.In this paper,we propose a lightweight model combining vgg-16 and u-net network.By combining two convolutional neural networks,we classify scenes of remote sensing images.While ensuring the accuracy of the model,try to reduce the memory of themodel.According to the experimental results of this paper,we have improved the accuracy of the model to 98%.The memory size of the model is 3.4 MB.At the same time,The classification and convergence speed of the model are greatly improved.We simultaneously take the remote sensing scene image of 64×64 as input into the designed model.As the accuracy of the model is 97%,it is proved that the model designed in this paper is also suitable for remote sensing images with few target feature points and low accuracy.Therefore,the model has a good application prospect in the classification of remote sensing images with few target feature points and low pixels.

Researches On The Design And Application Of DSP Multi- motor Collaborative Control System

As an important branch in the field of servo control, multi-motor coordination motion control applications are increasingly widespread.For open CNC system requirement, taking DSP as master core, combing with specific integrated stepper motor driver chip LMDI8201T, this designed a serial communication-based new collaborative multi-motor control system, which has characters of highly integrated, good stability, real-time, convenient man-machine interface.The test results show that the system fully meet performance requirements and achieved the motion control functions.

Crystal Structure, Characterization and Enhanced Solubility of Ibuprofen by 2-Methylimidazolium Salt

Novel crystalline forms of ibuprofen(IBU) with 2-methylimidazole(2 MI) in a 1:1 molar ratio was synthesized by liquid-assisted grinding technique and characterized by single-crystal X-ray diffraction, infrared spectral(IR), powder X-ray diffraction(PXRD),differential scanning calormetry(DSC) and Hirshfeld surface analysis. The structure of IBU-2 MI salt is assembled via N(1)–H(1)+···O1 and N(2)–H(2)+···O(2) hydrogen bonds to form the zigzag-like 1 D chain structure. The original purpose was to solve the pH-dependent solubility defect of ibuprofen, and the result of pH dependent solubility experiments showed that the IBU-2 MI salt had a better solubility at the wide range of pH 4.00 to 9.18. Furthermore, the solubility of IBU-2 MI salt exhibits a dramatic increase(30-fold) in aqueous mediums.

Polyoxometalate-Based Porous Metal-Organic Gel for High-Efficiency Ultrasound-Assisted Oxidative Desulfurization of Model Fuel

A novel heterogeneous catalyst for ultrasound-assisted oxidative desulfurization(UAODS)was designed and synthesized by confining polyoxometalates(POMs)clusters within porous metal-organic gel.The catalyst microstructures were characterized by XRD,SEM-EDX,FT-IR,N_(2)adsorption-desorption,and XPS.Effects of POM loading,catalyst dosage,and ultrasonic power were also investigated.Results indicate that 60%-PMA@MOX(Al)exhibits optimal catalytic activity,with a sulfur removal rate of 98.61%and excellent reusability.Moreover,a kinetic study of different desulfurization approaches demonstrates that the unique thermal and cavitation effects of ultrasound can effectively improve the efficiency of oxidative desulfurization.

Sika Deer Behavior Recognition Based on Machine Vision

With the increasing intensive and large-scale development of the sika deer breeding industry,it is crucial to assess the health status of the sika deer by monitoring their behaviours.A machine vision-based method for the behaviour recognition of sika deer is proposed in this paper.Google Inception Net(GoogLeNet)is used to optimise the model in this paper.First,the number of layers and size of the model were reduced.Then,the 5×5 convolution was changed to two 3×3 convolutions,which reduced the parameters and increased the nonlinearity of the model.A 5×5 convolution kernel was used to replace the original convolution for extracting coarse-grained features and improving the model’s extraction ability.A multi-scale module was added to the model to enhance the multi-faceted feature extraction capability of the model.Simultaneously,the Squeeze-and-Excitation Networks(SE-Net)module was included to increase the channel’s attention and improve the model’s accuracy.The dataset’s images were rotated to reduce overfitting.For image rotation,the angle wasmultiplied by 30°to obtain the dataset enhanced by rotation operations of 30°,60°,90°,120°and 150°.The experimental results showed that the recognition rate of this model in the behaviour of sika deer was 98.92%.Therefore,the model presented in this paper can be applied to the behaviour recognition of sika deer.The results will play an essential role in promoting animal behaviour recognition technology and animal health monitoring management.

Sika Deer Facial Recognition Model Based on SE-ResNet

The scale of deer breeding has gradually increased in recent years and better information management is necessary,which requires the identification of individual deer.In this paper,a deer face dataset is produced using face images obtained from different angles,and an improved residual neural network(ResNet)-based recognition model is proposed to extract the features of deer faces,which have high similarity.The model is based on ResNet-50,which reduces the depth of the model,and the network depth is only 29 layers;the model connects Squeeze-and-Excitation(SE)modules at each of the four layers where the channel changes to improve the quality of features by compressing the feature information extracted through the entire layer.A maximum pooling layer is used in the ResBlock shortcut connection to reduce the information loss caused by messages passing through the ResBlock.The Rectified Linear Unit(ReLU)activation function in the network is replaced by the Exponential Linear Unit(ELU)activation function to reduce information loss during forward propagation of the network.The preprocessed 6864 sika deer face dataset was used to train the recognition model based on SEResnet,which is demonstrated to identify individuals accurately.By setting up comparative experiments under different structures,the model reduces the amount of parameters,ensures the accuracy of the model,and improves the calculation speed of the model.Using the improved method in this paper to compare with the classical model and facial recognition models of different animals,the results show that the recognition effect of this research method is the best,with an average recognition accuracy of 97.48%.The sika deer face recognition model proposed in this study is effective.The results contribute to the practical application of animal facial recognition technology in the breeding of sika deer and other animals with few distinct facial features.

Researches On The Robot Obstacle Avoidance Based On Fuzzy Control

With the continuous development of modem sensor technology, coupled with the integration of artificial intelligence and a variety of emerging computer technology, it makes robots more intelligent and diverse.So the ability of the robot to complete the task is also valued and widely used.In this paper, the whole covered area of the local path planning uses a fuzzy control algorithm,which uses the robustness and an action of perception based on the biological behavior of the fuzzy control algorithm combined with itself.For obstacle avoidance system of mobile robots,we put forward the avoidance strategy of fully contacting the obstacles.And we have conducted a deep study about the theory and implementation methods.

Researches On The Optimal Design Of Intersection Signal Lights Fuzzy Control

Fuzzy control is an important branch of intelligent control, and this paper describes the application of fuzzy pattern study in intelligent control, begins with a brief overview introduction for development of intelligent control, and then describes the main components of the fuzzy model and its characteristics and fuzzy pattern control system.Fuzzy pattern applications in the intersection signal intelligent control showed fuzzy mode control can effectively reduce the single intersection average vehicle delay time, making the intersection more unobstructed to pass.

Segmentation of Remote Sensing Images Based on U-Net Multi-Task Learning

In order to accurately segment architectural features in highresolution remote sensing images,a semantic segmentation method based on U-net network multi-task learning is proposed.First,a boundary distance map was generated based on the remote sensing image of the ground truth map of the building.The remote sensing image and its truth map were used as the input in the U-net network,followed by the addition of the building ground prediction layer at the end of the U-net network.Based on the ResNet network,a multi-task network with the boundary distance prediction layer was built.Experiments involving the ISPRS aerial remote sensing image building and feature annotation data set show that compared with the full convolutional network combined with the multi-layer perceptron method,the intersection ratio of VGG16 network,VGG16+boundary prediction,ResNet50 and the method in this paper were increased by 5.15%,6.946%,6.41%and 7.86%.The accuracy of the networks was increased to 94.71%,95.39%,95.30%and 96.10%respectively,which resulted in high-precision extraction of building features.

Multi-Task Visual Semantic Embedding Network for Image-Text Retrieval

Image-text retrieval aims to capture the semantic correspondence between images and texts,which serves as a foundation and crucial component in multi-modal recommendations,search systems,and online shopping.Existing mainstream methods primarily focus on modeling the association of image-text pairs while neglecting the advantageous impact of multi-task learning on image-text retrieval.To this end,a multi-task visual semantic embedding network(MVSEN)is proposed for image-text retrieval.Specifically,we design two auxiliary tasks,including text-text matching and multi-label classification,for semantic constraints to improve the generalization and robustness of visual semantic embedding from a training perspective.Besides,we present an intra-and inter-modality interaction scheme to learn discriminative visual and textual feature representations by facilitating information flow within and between modalities.Subsequently,we utilize multi-layer graph convolutional networks in a cascading manner to infer the correlation of image-text pairs.Experimental results show that MVSEN outperforms state-of-the-art methods on two publicly available datasets,Flickr30K and MSCOCO,with rSum improvements of 8.2%and 3.0%,respectively.

Experimental research on affecting factors of the cutting quality of sugarcane harvesters under complicated excitations

The sugarcane field excitation,cutting forces and the engine excitation constitute complicated excitations acting on sugarcane harvesters.In this study,the sugarcane cutting mechanism under complicated excitations was analyzed.The dynamics and the mathematical models of sugarcane harvesters were established and simulated.Based on theoretical analysis,sugarcane cutting experiments were done on a self-built sugarcane harvester test platform(SHTP),designed as single-factor and the orthogonal experiments.Effects of the sugarcane field excitation characterized by the sugarcane field excitation device(SFED)output frequency,the engine excitation characterized by the actuating engine output frequency,the cutter rotating speed,the sugarcane harvester travelling speed simulated through the sugarcane transporting speed of the SHTP and the cutter inclination angle on the cutting quality of sugarcane harvesters were studied.Effects of the axial cutter vibration on three-directional cutting forces and the sugarcane cutting quality(SCQ)as well as effects of three-directional cutting forces on the SCQ were further studied.It is shown that the sugarcane field excitation,the axial cutter vibration amplitude and frequency as well as the three-directional cutting forces have significantly negative monotonic correlated effects on the SCQ while the cutter rotating speed,the sugarcane harvester travelling speed and the cutter inclination angle have significantly positive monotonic correlated effects on the SCQ.Significance levels of effects on three-directional cutting forces and the SCQ form high to low are as follow,the axial cutter vibration,the sugarcane field excitation,the cutter rotating speed,the engine excitation,the cutter inclination angle,the sugarcane harvester travelling speed.The theoretical analysis results were verified through experiment and an optimal combination was obtained with the cutter rotating speed of 700 r/min,sugarcane harvester travelling speed of 0.6 m/s and cutter inclination angle of 8º.This study can provide a reference for setting cutting parameters of sugarcane harvesters with a good SCQ.