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.

Space Transformation-Based Interdependency Modelling for Probabilistic Load Flow Analysis of Power Systems

Dependence among random input variables affects importantly the results of probabilistic load flow(PLF),system economic operation,and system security.To solve this problem,the main objectiveness of the paper is to analyze the performance of several schemes for simulating correlated variables combined with the point estimate method(PEM).Unlike the existing works that considering one single scheme combined with Monte Carlo simulation(MCS) or PEM,by neglecting the correlation among random input variables,four schemes were presented for disposing the dependence of correlated random variables,including Nataf transformation /polynomial normal transformation(PINT) combined with orthogonal transformation(OT) / elementary transformation(ET).Combining with the 2m+1 approach of PEM,a space transformation-based formulation was proposed and adopted for solving the PLF.The proposed approach is applied in the modified IEEE 30-bus system while considering correlated wind generations and load demands.Numerical results show the effectiveness of the proposed approach compared with those obtained from the MCS.Results also show that the scheme of combining Nataf transformation and ET with PEM provides the best performance.

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.

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.

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.

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.

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 ）.

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.

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.

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.

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.