Spatial Optimization and Reconstruction of Old Communities under the Background of Aging

As aging becomes increasingly serious,how to make the life of the elderly more convenient and comfortable has become one of the social problems to be solved urgently.Old residential areas are one of spaces where the elderly gather.In this paper,the prominent problems in the community space of existing old residential areas that are not conducive to the life of the elderly were analyzed,and corresponding countermeasures to transform the community space were put forward.It is hoped that public space can play its due value and make old residential areas glow with new vitality.

A CHARACTERISTIC OF RIEMANNIAN SPACES ADMITTING QUASI-CONCIRCULAR TRANSFORMATION

In this paper, we have considered some properties of quasi-umbilical hypersurfaces of a Riemannian space and obtained a characteristic of Riemannian spaces admitting quasi-concircular transformation.

User space transformation in deep learning based recommendation

Deep learning based recommendation methods, such as the recurrent neural network based recommendation method(RNNRec) and the gated recurrent unit(GRU) based recommendation method(GRURec), are proposed to solve the problem of time heterogeneous feedback recommendation. These methods out-perform several state-of-the-art methods. However, in RNNRec and GRURec, action vectors and item vectors are shared among users. The different meanings of the same action for different users are not considered. Similarly, different user preference for the same item is also ignored. To address this problem, the models of RNNRec and GRURec are modified in this paper. In the proposed methods, action vectors and item vectors are transformed into the user space for each user firstly, and then the transformed vectors are fed into the original neural networks of RNNRec and GRURec. The transformed action vectors and item vectors represent the user specified meaning of actions and the preference for items, which makes the proposed method obtain more accurate recommendation results. The experimental results on two real-life datasets indicate that the proposed method outperforms RNNRec and GRURec as well as other state-of-the-art approaches in most cases.

Research on the Reconstruction and Renewal of the Landscape Space of Industrial Sites in Post-industrial Era:A Case Study of Guangzhou Zilintang Art Town

With the rapid development of urbanization,traditional old industrial areas can not cope with the impact of the new wave of urbanization and have been abandoned,demolished and remodeled.Solving the pollution problem of industrial wasteland has become an important part of urban renewal research.Based on the development of industrial sites,the paper discusses the design principles and methods of industrial sites.Through the case analysis of the industrial site of Guangzhou Zilintang Art Town,the paper excavates the deep cultural deposits in the post-industrial era and analyzes the renewal,utilization,transformation and regeneration of the landscape space of industrial sites.

Study on Tri-Stimulus Transformation

To decrease number of samples for the implementation of color space transformation, a method for modeling the chromatic characterization of video cameras was proposed. An additional transformation was required to predict output RGB values for an input color. This additional transformation was based on spectral reflectance relationship. The transformed color coordinates were taken as inputs of a multilayer neural network. Based on network outputs, the RGB values to be predicted were calculated. Experimental results were given to illustrate the performance of the method. Even though much less number of training samples are used, this method can also perform well on this color space transformation.

Neural Network Method for Colorimetry Calibration of Video Cameras

To transfer the color data from a device (video camera) dependent color space into a device? independent color space, a multilayer feedforward network with the error backpropagation (BP) learning rule, was regarded as a nonlinear transformer realizing the mapping from the RGB color space to CIELAB color space. A variety of mapping accuracy were obtained with different network structures. BP neural networks can provide a satisfactory mapping accuracy in the field of color space transformation for video cameras.

Shadow Detection and Compensation for Color Aerial Images

A method for shadow detection and compensation for color aerial images is presented. It is considered that the intensity value of each image pixel is the product of illumination function and ground object reflection, and the shadowed regions on the image are mainly caused by the short of illumination, so the information compensation for the shadowed regions should concentrate on the illumination adjustment of concerned area on the basis of the analysis of whole image. The shadow detection and compensation procedure proposed by this paper consists of four steps.

LANE MARKING DETECTION IN CLUTTERED ENVIRONMENT

Objective To determine the positions of marking in the presence of distracting shadows, highlight, pavement cracks, etc. Methods RGB color space is transformed into I 1 I 2 I 3 color space and I 2 component was used to form a new image with less effect of the clutter. Using an improved edge detection operator, an edge strength map was produced, and binarilized by adaptive thresholds. The binary image was labeled and circularity of all connected components is calculated. The Self Organizing Mapping is adopted to extract regions which imply potential marking. Finally the position of marking was obtained by curve fitting. Results Color information was utilized fully, all thresholds were set adaptively and lane marking could be detected in challenging images with shadows, highlight or other cars. Conclusion The method based on circularity of connected components shows its outstanding robustness to lane marking detection and has a wide variety of applications in the areas of vehicle autonomous navigation and driver assistance system.

Transformation of Industrial Heritage from the Perspective of Urban Memory:A Case Study of Taoxichuan Creative Square

Urban memory is the soul of a city. With the rapid development of the city, the phenomena of“large-scale demolition and construction” and “a thousand cities having the same pattern” are becoming more and more serious, and the urban characteristics containing rich historical information are gradually lost. As an important witness of the historical development of urban industry, industrial heritage contains precious historical and cultural values. Starting urban memory, and taking Taoxichuan Square as the example,through field research and memory interview, the continuation manner of urban memory in industrial heritage space is studied, and the transformation strategy of industrial heritage is put forward from the perspective of urban memory, making industrial heritage have a unique life cycle and cultural precipitation,inherit the urban context and promote the harmonious development of society.

Matrix transformations of l^q(X) to l^p(Y )

Let X and Y be Banach spaces, 0 〈 q 〈 ＋∞, i ≤ p 〈 ＋∞. In this paper, we characterize matrix transformations of lq （ X ） to lp （ Y ）.

Method to generate training samples for neural network used in target recognition

Training neural network to recognize targets needs a lot of samples.People usually get these samples in a non-systematic way,which can miss or overemphasize some target information.To improve this situation,a new method based on virtual model and invariant moments was proposed to generate training samples.The method was composed of the following steps：use computer and simulation software to build target object＇s virtual model and then simulate the environment,light condition,camera parameter,etc.;rotate the model by spin and nutation of inclination to get the image sequence by virtual camera;preprocess each image and transfer them into binary image;calculate the invariant moments for each image and get a vectors＇ sequence.The vectors＇ sequence which was proved to be complete became the training samples together with the target outputs.The simulated results showed that the proposed method could be used to recognize the real targets and improve the accuracy of target recognition effectively when the sampling interval was short enough and the circumstance simulation was close enough.

Improvement, Comparison, and Application of Field Measurement Methods for Grassland Vegetation Fractional Coverage

As one of the important vegetation parameters, vegetation fractional coverage （VFC） is more difficult to measure accurately among a good many parameters of plant communities. The temperate typical steppe in the north of China was chosen for investigation in the present study and a digital camera was used to measure herb community coverage in the field, adopting methods of ocular estimation, gridding measurement, visual interpretation, supervised classification, and information extraction of color spatial transformation to calculate the VFC of images captured by the digital camera. In addition VFC calculated by various methods was analyzed and compared VFC, enabling us to propose an effective method for measuring VFC using a digital camera. The results of the present study indicate that： （i） as two common useful and effective methods of measuring VFC with a digital camera, not only does the error of estimated values of visual estimation and supervised classification vary considerably, but the degree of automatization is very low and depends, to a great extent, on the manipulator; （ii） although the method of visual interpretation may assure the precision of the calculated VFC and enable the precision of results obtained using other methods to be determined, as far as large quantities of data are concerned, this method has the disadvantages of wasting time and energy, and the applications of this method are limited; （iii） the precision and stability of VFC calculated using the grid and node method are superior to those of visual estimation and supervised classification and inferior to those of visual interpretation, but, as for visual interpretation and supervised classification, gridding measurements are difficult to apply in practice because they are not time efficient; and （iv） in terms of the precision of calculation of the VFC, an information-extracting model based on an intensity, hue, saturation （IHS） color space-multi-component series segmentation strategy is superior to methods of ocular estimation, gridding measurement, and supervised classification. In terms of practical efficiency, the information-extracting model is superior to visual interpretation, supervised classification, and gridding measurement. It has been proven that estimating the VFC of the north temperate typical steppe using this model is feasible. This is very fundamental research work in grassland ecology.

Path Integral Solution for an Angle-Dependent Anharmonic Oscillator

We have given a straightforward method to solve the problem of noncentral anharmonic oscillator in three dimensions. The relative propagator is presented by means of path integrals in spherical coordinates. By making an adequate change of time we are able to separate the angular motion from the radial one. The relative propagator is then exactly calculated. The energy spectrum and the corresponding wave functions are obtained.

Trabecular spacing estimation based on quadratic transformation algorithm

The quadratic transformation method is proposed to estimate the trabecular spac- ing （Tb.Sp）, an important index for osteoporosis diagnosis. The performance of this algorithm was investigated by scatter model, two-dimension finite difference time domain （2D-FDTD） simulation and in vitro experiments of bovine cancellous bone specimens. Comparing with the other four methods autoregressive cepstrum （AR）, adaptive filter- autoregressive cepstral （AFAR）, inverse filter-autoregressive eepstrum （InvAR）, and simplified inverse filter tracking （SIFT）, quadratic transformation is much more stable and accurate. The results demonstrated that quadratic transformation is a great algorithm for Tb.SD estimation.

New Exact Solutions for the Wick-Type Stochastic Kudryashov–Sinelshchikov Equation

In this article, exact solutions of Wick-type stochastic Kudryashov–Sinelshchikov equation have been obtained by using improved Sub-equation method. We have used Hermite transform for transforming the Wick-type stochastic Kudryashov–Sinelshchikov equation to deterministic partial differential equation. Also we have applied inverse Hermite transform for obtaining a set of stochastic solutions in the white noise space.