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The recognition rate of some face recognition methods that require a certain number of samples will be significantly reduced in case only one sample is available for training. Aim at this situation, a new feature extraction method, HOG–LDB (histogram of oriented gradients–local difference binary), is proposed. Then, we combined this method with SVDL (sparse variation dictionary learning) to recognize the probe images with different facial variations (e.g., illuminations, poses, expressions and disguises). The descriptor of HOG–LDB can extract the edge features and local pattern features of the image. After the feature extraction, SVDL is employed in the generic training set and the generic variation dictionary is obtained. Then, the dictionary is used for predicting the subjects of the probe images with different facial variations. Finally, experimental results on the AR dataset, the Yale dataset, the Extended Yale B dataset and the CMU-PIE dataset proved the validity of the proposed method.

Face Recognition plays a very important role in numerous occasions based on visual security in recent days. The current methods of face recognition are to extract the different features of different faces to distinguish from others, so feature extraction has become a vital step in face recognition. For this reason, this paper presents a new fusion of local difference binary (LDB) and histogram of oriented gradients (HOG) for face recognition. We use LDB descriptor to extract the local pattern features of a face image. At the same time, the edge features of the original image are extracted by using HOG descriptor. The proposed new fusion of features improves the shortcomings of the low accuracy and avoids the problems that the dimension of the general fusion of features is too high. The experimental results on ORL and Yale face database verify the validity of the proposed fusion of features.

The Chinese government has been active in trying to cool the alleged bubbles in its housing markets, especially in urban areas. This paper argues that the high housing prices are partly caused by some real factors, including the policy of restricting land uses, in particular the maintenance of a minimum overall agricultural acreage. A simple model of three sectors (housing, agriculture, and others) is constructed to examine the effects of the artificial constraint. The role of increasing returns in the non-agricultural sectors in exacerbating the policy biases is also examined. The model is then calibrated to estimate the effects of land use control policy on housing prices in China.

This paper investigates how the trade-off between organization costs, transaction costs and economies of specialization may affect the way public goods are provided. In doing so, it considers two ways of providing a public good. One is collective provision where users organize themselves to jointly finance the public good which is produced by a specialized firm. The other is market provision with bundling where a firm produces the public good and a private good and sells them as a bundle. Both methods of public goods provision deal with the problem of non-excludability. The first method involves organization costs, but can take advantage of specialization economies; the second method avoids organization costs, but may incur some transaction costs and forgoes the benefit of specialization economies. Which method is superior depends on the relative magnitudes of organization costs, transaction costs, specialization economies as well as other features of the economy such as population size.

This paper applies the inframarginal analysis, which is a combination of marginal and total cost-benefit analysis, to investigate the relationship between division of labor, the extent of the market, productivity and inequality of income distribution. The model with transaction costs and exogenous and endogenous comparative advantages shows that as trading efficiency is improved the general equilibrium discontinuously jumps from autarky to partial division of labor with a dual structure, then to the complete division of labor where dual structure disappears. In this process different groups of individuals with different trading efficiency become involved in a certain level of division of labor at different stages of development. As the leading group becomes involved in a higher level of division of labor leaving others behind, a dual structure emerges and inequality increases. As latecomers catch up dual structure disappears and inequality declines. When the leader goes to an even higher level of specialization, dual structure occurs and inequality increases again. Inequality decreases again as the latecomers catch up. Hence, the equilibrium degree of inequality fluctuates in this development process. The relationship between inequality and productivity is neither monotonically positive nor monotonically negative. It might not be an inverted U-curve. The key driving force of economic development and trade is improvement in trading efficiency.

This paper develops two models to study the impact of trade in intermediate goods on wage inequality between skilled and unskilled labor in a developed country and a developing country. The first model assumes symmetric production technologies in the intermediate good. It predicts that trade in the intermediate good will increase wage inequality in the developed country, but decrease wage inequality in the developing country. The second model assumes asymmetric technologies in the intermediate good. It predicts that trade in the intermediate good can lead to an increase in wage inequality in both the developed country and the developing country.