Calligraphy appreciation is widely considered to require sequence restoration, while the sequence restoration of painting is ignored in long time. Moreover, the detail feature of brush strokes is considered to enhance the perception of sequentiality. In order to quantify the sequentiality perception and to explore the influence of detail features of strokes on sequentiality perception, a sequentiality perception quantization method based on Markov chain entropy rate was proposed. Firstly, the perceived sequentiality of an individual to the markers on the artwork was modeled as a Markov chain. Then, the entropy rate of the Markov model was calculated to measure the uncertainty of the perceived sequentiality. Finally, the negentropy was used to measure the order of the perceived sequentiality and was normalized to obtain the measurement index:sequentiality perception. The feasibility of this method was verified through the actual measurement of the sequentiality perception of a group of artworks. And based on the proposed sequentiality measurement, the effect of graph transformation on the sequentiality perception of artworks was studied. Experimental results show that the sequentiality consistency keeps high level when rotation or mirror transformation is performed to the original image, while the correctness varies significantly. This means that the feature of brush strokes is not the primary factor in forming the sequentiality experience, and the viewer's own experience of order of strokes is more important in the formation, but this conclusion needs to be further verified.

Current research generally focuses on the application of gamification to improve the engagement of learning. However, the research on gamification in specific fields such as color education is not sufficient, and there is a lack of analysis on the gamification elements and influence factors of learning effects. For these problems, a game model for training color recognition was designed. Firstly, two different ways of playing were designed with same core gameplay but different interaction modes. Then, the same virtual reward was added in both playing ways. Finally, the effects of two playing ways on learning effect with or without virtual reward were compared, and the effect of virtual reward in the same playing way were compared. The results show that gameplay design mainly affects learning efficiency, and virtual reward mainly affects engagement.

For physical-layer network coding over time-varying bi-directional relay channels, a joint channel coding and non-coherent physical-layer network coded modulation and detection scheme without channel state information was designed in multiple-antenna environment. Firstly, the spatial modulation matrix at the source was designed to achieve physical-layer network coding. Then, a differential spatial modulation was combined with physical-layer network coding and maximum a posteriori probability of superimposed signal was derived at the relay. Moreover, considering the constellation of the superimposed signal, a mapping function to map superimposed signal to broadcasting signal was designed. Lastly, taking advantage of the linear structure of channel coding, and combining bit interleaving, channel decoding and soft-input soft-output detection algorithm, an iterative detection approach for joint channel differential physical-layer network coding was obtained. Simulation results show that the proposed scheme can achieve non-coherent transmission and detection used to physical-layer network coding for two-way relay channels and can effectively enhance the throughput and spectral efficiency of the system.

To solve the problem of low efficiency for fast deduplicating the same image in massive images, a parallel deduplication technology for massive images based on image features was proposed. Firstly, the image color, texture, shape and other features were extracted to fully represent images. Secondly, the metric was used to calculate the distance between images. Finally, according to these distances, the same image could be fast located and deduplicated by the thought that the two points might be the same point if they had same distance to any other point. It has been analyzed and verified in combination with the experimental data that this technology is accurate in deduplicating images, besides, it just needs 10 minutes to deal with 5 million images by one computer with i5 processor. Compared with one by one calculation, the technology improves the efficiency of massive image deduplication and can shorten the calculation time.

In order to create novel artistic effects, a period-dynamic-image model was proposed, in which each element is a periodic function. Instead of using an array of color pixels to represent a digital image, a Fourier model was used to represent a periodic dynamic image as an array of functional pixels, and the output of each pixel was computed by a Fourier synthesis process. Then three applications with three rendering styles were put forward, including dynamic painting, dynamic distortion effects and dynamic speech balloons, to visually display the periodic dynamic images. A prototype system was constructed and a series of experiments were performed. The results demonstrate that the proposed method can effectively explore the novel artistic effects of periodic dynamic images, and it can be used as a new art media.

Considering the problem of the low inference accuracy of the extended Belief Rule Base (BRB) which was proposed by Liu, etc (LIU J, MARTINEZ L, CALZADA A, et al. A novel belief rule base representation, generation and its inference methodology. Knowledge-Based Systems, 2013, 53: 129-141), an improved method of rule-base construction and inference was proposed. This approach was based on the method of Liu's rule-base construction, and a new generation method of rule antecedents and a new calculation method of rule weights were provided. Subsequently, in order to avoid activating so many unnecessary rules, the 80/20 rule was introduced to improve the strategy of rule activation. Then an integrated construction and inference methodology of belief rule-base was formed. Finally, in order to validate the accuracy and efficiency of the new approach, the case study in pipeline leak detection was provided. The experimental results show that the proposed approach not only can keep lower time-consumption, but also can make the Mean Absolute Error (MAE) of system be reduced to 0.17342. This proves that the new approach has high accuracy and efficiency.

In order to adapt to the dynamic changes of business requirements of collaborative enterprise in the operation course of collaborative platform, a form configuration model for Software as a Service (SaaS) platform was established. The storage and dynamical load of form configuration model were supported by mapping form structure and form elements with XML document. The method of online dynamic allocation operating authority of the form content was presented. Form online dynamic update technology was realized based on form configuration file access interface. The proposed technology was applied to a SaaS platform industrial chain, which shows that the flexibility is improved and the enterprises have more initiative and control over the management of information systems.