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Artificial intelligence (AI) is enabling the automated analysis of large amounts of image/video data, boosting the speed of multimedia data processing remarkably. Meanwhile, Image Quality Assessment (IQA) plays an important role in developing automatic analysis methods. To ensure the effectiveness of AI, images in multimedia applications should be considered for visual examination by both human and machine. Therefore, it is significant to understand the differences between human's and AI's perception of semantic distortion. However, little work has been done due to the lack of data from human on the semantic level. In this paper, we first propose a semantic database (SID) based on the surveillance scenarios, by collecting subjective average recognition rates of 3 semantic targets (face, pedestrian, license plate) with 3 types of distortion (JPEG Compression, BPG Compression, Motion Blur). Then, we present a detailed analysis of how human and AI perceive semantic distortion differently. Experimental results show that AI is stronger in tolerance to distortion than human beings on average, while weaker at generalization and stability. It is also implied in the experiments that existing IQA methods are not effective enough at judging the semantic distortion.

Semantic information is important in video encryption. However, existing image quality assessment (IQA) methods, such as the peak signal to noise ratio (PSNR), are still widely applied to measure the encryption security. Generally, these traditional IQA methods aim to evaluate the image quality from the perspective of visual signal rather than semantic information. In this paper, we propose a novel semantic-level full-reference image quality assessment (FR-IQA) method named Semantic Distortion Measurement (SDM) to measure the degree of semantic distortion for video encryption. Then, based on a semantic saliency dataset, we verify that the proposed SDM method outperforms state-of-the-art algorithms. Furthermore, we construct a Region Of Semantic Saliency (ROSS) video encryption system to demonstrate the effectiveness of our proposed SDM method in the practical application.

In order to obtain the remaining recoverable reserves of refract ring well, based on grey system theory, we applied the forward and backward difference to the white differential equation of the grey model and introduced a parameter. Then an improved grey model was established, accordingly, the original expression of the background value with the introduced parameter was derived. On this basis, the particle swarm optimization algorithm was applied to search the best parameter. Ultimately, we used the improved grey model and combined with the daily oil production of the oil well before refract ring to forecast the remaining recoverable reserves. The prediction result indicated that the modified grey model was much more accurate than the unimproved grey model. In addition, it was simple to calculate and demands just a few raw data. Therefore, it could be used as another prediction method apart from material balance method.

Until now, there is little literature on the study of Retailing Revolution based on the theory of Sectoral Innovation. Revelant studies on Retailing Innovation mostly focus on the analysis of retail format and case studies on successful enterprises. In the meantime, retailing changes business model initiated by technological innovation, and industrial structure corres ponding market environment and industry s pecialties. Firstly, this essay put forward the cencept model of Chinese Sectoral Innovation System of Retailing, analyses the characteristics and mode of the innovation based on the theory of Evolutionary Economics. Finally, this essay illustrates the retailing revolution by using the Value Chain analysis.

The characteristics of retail market directly constraint and affect the performance of businesses innovation and the effectivity of the national policy of expanding domestic demand. This article systematically researches and summarizes the main characteristics of China retail market from the perspective of international comparison with five representative indices as the size, growth, consumption rate, consumption structure, concentration of China retail market. The conclusion is that the size of China retail market is large and the growing trend is strong, however, the rate of consumption and the degree of concentration are in a low level, and the structure of consumption is imbalanced.

Online retailing contains enterprises with highly innovative characteristics. In this paper, taking the online retail business of Alibaba China as the case study sample, the global value chain (GVC) innovation theory is used to research the innovative practices of Alibaba's online retail business based on the literature research regarding the online retail business innovation theory. Through selection of major innovation events about online retail business of Alibaba Taobao, we carry out content analysis according to the GVC innovation theory, and deeply analyze the innovation system of Taobao from five perspectives which includes innovation goals, process innovation, product innovation, functional innovation and chain innovation.

Global financial crisis has produced a direct and significant impact on retailers. This paper made a case study on the innovation strategy of Hangzhou Tower Shopping Center in the context of global economic crisis based on retail innovation and global value chain theories. The article proposed: under the background of global financial crisis, an importance strategy which retailers should take is to set up and carry out global value chain innovation strategy system, in order to promote the position in the global value chain and strengthen its global value chain words power and control power.

Taking Target Corporation U.S. as a case, this paper researches its innovation system based on the theory of global value chain innovation. Considered as an innovative retailer, Target tries to innovate, in order to establish its own empire in the highly competitive retail industry in USA. This paper classifies and analyses the innovation events of Target, then comprehensively analyses the innovation system of Target from five aspects: innovation goal, process innovation, product innovation, functional innovation and chain innovation. Target's successful innovations are helpful to Chinese retailers in retail innovation.

Retailing running to high-value-added-end is a more visible trend, which attracts lots of attention from researchers or practitioners. This paper tries to explain this with the theory of Global Value Chains(GVCs). After literature review on GVCs and innovation strategy, this paper analyzes the global value chains of 7–11, IKEA, Wal-Mart and PPR separately. Then some comparisons is done to analyze the respective characteristics of the global value chain model of the four from ten angles, so as to build retailer's innovation strategy on GVCs. As a result, some advices are given to Chinese retailers for their developing.