New mixed adaptive detection algorithm for moving target with big data

Aiming at the troubles (such as complex background, illumination changes, shadows and others on traditional methods) for detecting of a walking person, we put forward a new adaptive detection algorithm through mixing Gaussian Mixture Model (GMM), edge detection algorithm and continuous frame difference algorithm in this paper. In time domain, the new algorithm uses GMM to model and updates the background. In spatial domain, it uses the hybrid detection algorithm which mixes the edge detection algorithm, continuous frame difference algorithm and GMM to get the initial contour of moving target with big data, and gets the ultimate moving target with big data. This algorithm not only can adapt to the illumination gradients and background disturbance occurred on scene, but also can solve some problems such as inaccurate target detection, incomplete edge detection, cavitation and ghost which usually appears in traditional algorithm. As experimental result showing, this algorithm holds better real-time and robustness. It is not only easily implemented, but also can accurately detect the moving target with big data

Novel fusion computing method for bio-medical image of WSN based on spherical coordinate

In bio-medical field, embedded numerous sensing nodes can be used to monitor and interact with physical world based on signal analysis and processing. Data from many different sources can be collected into massive data sets via localized sensor networks. Understanding the environment requires collecting and analyzing data from thousands of sensors monitoring, this is big data environment. The application of bio-medical image fusion for big-data computing has strong development momentum, big-data bio-medical image fusion is one of key problems, so the fusion method study is a hot topic in the field of signal analysis and processing. The existing methods have many limitations, such as large delay, data redundancy, more energy cost, low quality, so novel fusion computing method based on spherical coordinate for big-data bio-medical image of WSN is proposed in this paper. In this method, the three high-frequency coefficients in wavelet domain of bio-medical image are pre-processed. This pre-processing strategy can reduce the redundant ratio of big-data bio-medical image. Firstly, the high-frequency coefficients are transformed to the spherical coordinate domain to reduce the correlation in the same scale. Then, a multi-scale model product (MSMP) is used to control the shrinkage function so as to make the small wavelet coefficients and some noise removed. The high-frequency parts in spherical coordinate domain are coded by improved SPIHT algorithm. Finally, based on multi-scale edge of bio-medical image, it can be fused and reconstructed. Experimental results indicate the novel method is effective and very useful for transmission of big-data bio-medical image, which can solve the problem of data redundancy, more energy cost and low quality

Solving Solar Neutrino Puzzle via LMA MSW Conversion

We analyze the existing solar neutrino experiment data and show the allowed regions. The result from SNO's salt phase itself restricts quite a lot the allowed region's area. Reactor neutrinos play an important role in determining oscillation parameters. KamLAND gives decisive conclusion on the solution to the solar neutrino puzzle, in particular, the spectral distortion in the 766.3 Ty KamLAND data gives another new improvement in the constraint of solar MSW-LMA solutions. We confirm that at 99.73% C.L. the high-LMA solution is excluded.Comment: 6 eps figure

Bihamiltonian Cohomologies and Integrable Hierarchies I: A Special Case

We present some general results on properties of the bihamiltonian cohomologies associated to bihamiltonian structures of hydrodynamic type, and compute the third cohomology for the bihamiltonian structure of the dispersionless KdV hierarchy. The result of the computation enables us to prove the existence of bihamiltonian deformations of the dispersionless KdV hierarchy starting from any of its infinitesimal deformations.Comment: 43 pages. V2: the accepted version, to appear in Comm. Math. Phy

糖尿病培训手册在培养糖尿病护士的应用

Objective: To explore the nursing service mode for specialized nurses in diabetes and its application effect. Methods:In view of the actual situation of our hospital, a special training manual named with Diabetes training manual was prior composed. 40 specialized nurses in diabetes were trained with the special training manual. Training lasted for 3 months. After the training, the specialized nurses were assessed with the specialty knowledge of Diabetes Mellitus, the skill of clinical procedures, and the knowledge about patients' health education. Results: The skill of the trained nurses was improved. The satisfaction of patients was enhanced.Conclusion: Diabetes training manual can be used for specialized nurses in diabetes.目的  探讨糖尿病护士培训方式。方法  对2013年1—10月本院内分泌科的40名糖尿病护士培训,根据以往医院的培训，结合本院实际，应用自编的糖尿病培训手册，最后考核糖尿病专科理论、操作及宣教能力考核，培训时间为3个月。结果  培训前与培训后比较差别有统计学意义（P＜0.05），理论、操作及健康宣教能力较培训前提高；提高了患者及新护士的满意度。结论  糖尿病培训手册可以用于培养糖尿病新护士

Iron pnictides as a new setting for quantum criticality

Two major themes in the physics of condensed matter are quantum critical phenomena and unconventional superconductivity. These usually occur in the context of competing interactions in systems of strongly-correlated electrons. All this interesting physics comes together in the behavior of the recently discovered iron pnictide compounds that have generated enormous interest because of their moderately high-temperature superconductivity. The ubiquity of antiferromagnetic ordering in their phase diagrams naturally raises the question of the relevance of magnetic quantum criticality, but the answer remains uncertain both theoretically and experimentally. Here we show that the undoped iron pnictides feature a novel type of magnetic quantum critical point, which results from a competition between electronic localization and itinerancy. Our theory provides a mechanism to understand the experimentally-observed variation of the ordered moment among the undoped iron pnictides. We suggest P substitution for As in the undoped iron pnictides as a means to access this new example of magnetic quantum criticality in an unmasked fashion. Our findings point to the iron pnictides as a much-needed new setting for quantum criticality, one that offers a new set of control parameters.Comment: (v3) New abstract, more explanatory material, accepted for PNA

Novel fusion computing method for bio-medical image of WSN based on spherical coordinate

In bio-medical field, embedded numerous sensing nodes can be used to monitor and interact with physical world based on signal analysis and processing. Data from many different sources can be collected into massive data sets via localized sensor networks. Understanding the environment requires collecting and analyzing data from thousands of sensors monitoring, this is big data environment. The application of bio-medical image fusion for big-data computing has strong development momentum, big-data bio-medical image fusion is one of key problems, so the fusion method study is a hot topic in the field of signal analysis and processing. The existing methods have many limitations, such as large delay, data redundancy, more energy cost, low quality, so novel fusion computing method based on spherical coordinate for big-data bio-medical image of WSN is proposed in this paper. In this method, the three high-frequency coefficients in wavelet domain of bio-medical image are pre-processed. This pre-processing strategy can reduce the redundant ratio of big-data bio-medical image. Firstly, the high-frequency coefficients are transformed to the spherical coordinate domain to reduce the correlation in the same scale. Then, a multi-scale model product (MSMP) is used to control the shrinkage function so as to make the small wavelet coefficients and some noise removed. The high-frequency parts in spherical coordinate domain are coded by improved SPIHT algorithm. Finally, based on multi-scale edge of bio-medical image, it can be fused and reconstructed. Experimental results indicate the novel method is effective and very useful for transmission of big-data bio-medical image, which can solve the problem of data redundancy, more energy cost and low quality

Limits on the Superconducting Order Parameter in NdFeAsO1−x_{1-x}Fy_y from Scanning SQUID Microscopy

Identifying the symmetry of the superconducting order parameter in the recently-discovered ferro-oxypnictide family of superconductors, RFeAsO$_{1-x}$F$_{y}$, where $R$ is a rare earth, is a high priority. Many of the proposed order parameters have internal $\pi$ phase shifts, like the d-wave order found in the cuprates, which would result in direction-dependent phase shifts in tunnelling. In dense polycrystalline samples, these phase shifts in turn would result in spontaneous orbital currents and magnetization in the superconducting state. We perform scanning SQUID microscopy on a dense polycrystalline sample of \NdFeAsO$_{0.94}$F$_{0.06}$ with $T_c=48$ K and find no such spontaneous currents, ruling out many of the proposed order parameters.Comment: 10 pages, 5 figures; to appear in JPS