Activation of how and where arithmetic operations are displayed in the brain has been observed in various number-processing tasks. However, it remains poorly understood whether stabilized memory of Boolean rules are associated with background knowledge. The present study reviewed behavioral and imaging evidence demonstrating that Boolean problem-solving abilities depend on the core systems of number-processing. The core systems account for a mathematical cultural background, and serve as the foundation for sophisticated mathematical knowledge. The Ebbinghaus paradigm was used to investigate learning-induced changes by functional magnetic resonance imaging (fMRI) in a retrieval task of Boolean rules.

In this paper, we have studied the operation modes of satellite communication system. They include that signal transmission mode, signal processing mode and signal exchanging mode. We have especially studied the multiplex mode, modulation mode, coding mode, multiple-address connection, and channel distribution and exchanging system. All we have studied are important to the satellite communication station’s changing and signal processing.

Objectives: To find out the inner outer risks and its influence on social pooling fund under diseases score settlement (DSS).Methods: To Use step multiple linear regression analysis, the risk factors of the fund have been screened out. The selected risk factors have been taken into BP artificial neural network (BPANN). Results: In 12,724 insured inpatients, chronic diseases accounted for 24.89%.The average medical expense per inpatient was 11,950.88RMB and per hospitalization expenditure of social pooling fund was 7,665.81RMB. The 10 variables such as age, sex, unit type, hospital level, individual pays,medicine fee, medical fee, operation fee, nurse expense, bed fee and other expense were statistically significant. Conclusion: The growing aging population, changes in disease spectrum, increasing medical costs are all risks of non-controllable running outside the system. Moral hazard and the defective design of the system belong to the system controllable risks. The results from BPANN were compatible with multiple linear regression analysis.
The payment system plays an important role in health insurance [1]. Good payment can control the hospitalization expenditures in a reasonable scope, while an imperfect one can throw a monkey-wrench into the system.The diseases score settlement (DSS) is payment system of Huai’an in China. This article develops two simple models (step multiple linear regression analysis and back-propagation artificial neural network(BPANN)) to illustrate the risks both inside and outside DSS and explore the risk control function of DSS.
BPANN are the most widely used networks and are considered to be the workhorse of ANNs because of its simplicity and its power to extract useful information from samples [2].Due to its strong learning ability and generalization capability, BP networks have been successfully used in forecasting some financial problems, for example, predicting stock market returns [3], loan risk warning [4] and forecasting bankruptcy firms [5].

A data analysis system for the general commodity sales information is researched on and further designed. The key problems of designing this system are that, it should enable the system to adjust to user-data with different structures, enable users to define or change data structures as well as retrieval methods. Through the research on the general structure and retrieval method of the commodity sales data, the system realizes users' customization of the database, thus is applicable to sales data with different structures. This paper focuses on the structure of the database, the creation method and process of the database by the user, the structure of the data dictionary and data exchange between database and software, with case examples in the final illustration.

Virtual Private Database (VPD) ensures the privacy of information and prevents direct data leakage through computer terminals by providing Fine-grained Access Control (FGAC). This paper firstly introduces the security requirements of the test database management system and based on which, further analyzes the existing shortcomings in access control technology. Through a brief introduction of VPD, the security design of the test database management system is then described, in which both the security and flexibility of the system are increased and the information leaks and other security related problems of the system are solved.

In order to represent complex graph drawing in the course of 3-dimensional dynamic simulating flexible objects such as fabric、garment、rope、netting yarn and rubber band, we designed a new mathematic model named operator cube. Any graph formed on the basis of the point information. In a word, if each point has enough geometry information, the graph can be drawn and rendered. Operator cube model came into being just because of that idea. The paper mainly discussed the theory of operator cube model. The model can transform a complex graph into a simple representation effectively and in real time, especially in the course of topology structure varying flexible object simulation. What’s more, the model can accurately express the simulation results. The model converted between the world coordinate system space and device coordinate system space. And the model and the conversion involved some profound mathematic theorems and our conclusions which were proved strictly.

A novel spiking cortical model based switching mean filter for removing impulse noise is presented. In the proposed filter, the noise detector using spiking cortical model is first adopted to identify the pixels that are likely to be corrupted by impulse noise. Then the detected impulses are removed by the weighted mean filter while the noise-free pixels are left unaltered. Extensive simulations show that the proposed filter outperforms a number of existing decision-based filters due to its excellent performance in terms of effectiveness in image restoration. Because of its outstanding restoration performance, the proposed filter can be used for noise removal in numerous consumer electronics products such as digital camera and digital television.

Proteins are amino acid chains that acquire their biological and biochemical properties by folding into unique 3-dimensional structures. The biological function of a protein is dependent on the protein folding into the correct, or "native", state. At present, there are so many ideas to predict the structure of the protein folding. This paper first present the concept of protein folding and how is significant to study protein fold prediction. In this paper we join the simulated annealing factor into Parallel Genetic Algorithm and use this hybrid Parallel GA to predict the structure of protein fold. The revised algorithm is more efficient than traditional Genetic Algorithm and simulated annealing algorithm.

Service oriented architects (SOA) is considered as an extensible, robust and platform independent web application architect. However, problems in security guard for service access remains unresolved especially for the measurable one. we proposed a novel access control model, which we called SACM: Service Access Control Model, specially for SOA. Our model is mainly based on the role access policy, extended with trust authority transition and integration mechanism, to fulfill an extensive and measurable access control modeling approach with Crypto-CCS.

Lung cancer has become one of the leading causes of death in the world. Clear evidence shows that early discovery, early diagnosis and early treatment of lung cancer can significantly increase the chance of survival for patients. Lung Computer-Aided Diagnosis (CAD) is a potential method to accomplish a range of quantitative tasks such as early cancer and disease detection, In computer-aided diagnosis of lung disease, accurate and fast pulmonary parenchyma segmentation is the core step. Watershed algorithm is used in this paper to segment and extract lung parenchyma. To reduce over-segmentation, an improved watershed segmentation method which marks foreground and background is proposed. This method is based on watershed algorithm using “Sobel” operator on edge detection and then using mathematical morphology opening and closing operations and morphological reconstruction to mark the foreground. Extracting the local maximum associated with object will constitute the binary marker image. By testing different types of images, it proposes that the algorithm in this paper can be consistent with human visual characteristics and get more accurate, continuous object boundary. Compared with other watershed improvement methods, this proposed one requires less computational complexity, more simple parameters, and can effectively reduce over-segmentation.

In the vision technique and the wide visual seeing surveillance system; it always happened to actualize multiple images, non-slot merging. Phase Correlation Algorithm (PCA) is widely used as image matching method. Based on lots of simulation of phase correlation algorithm, it makes the image mosaics improve in the computing speed and accuracy.

Effectiveness of local binary pattern (LBP) for face recognition has been proven. But the weight of weighted LBP is difficult to determine. In this paper, we proposed a biologically plausible approach to set the weight automatically. Combining LBP and visual attention, a weight map can be constructed by summing over the saliency map. The weight map outlines salient information in the image and helpful for recognition. Experimental results show that the presented method is efficient and effective.