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Carbonized traditional Chinese medicine (TCM) is a kind of distinctive traditional drug which has been widely used in various bleeding syndromes for over two thousand years, and most of them are still in clinical use. Although they share similar processing method: stir-frying, there are no specific quality standards and few quality control researches carried out on carbonized TCM up until now. Carbonized Typhae Pollen (CTP) is a typical carbonized TCM with efficacy of eliminating blood stasis and stanching bleeding. In this study, a novel process quality control model coupled with near infrared spectroscopy was established, called Gradient-based Discriminant Analysis method (GDA). Compared with conventional modeling methods (Convolutional Neural Network, Linear Discriminant Analysis, Standard Normal Variate-LDA), GDA model applied in fiber optic probe acquisition mode exhibited highest test accuracy (0.961), satisfactory correct identification (internal validation, 100%; external validation, 97.1%) and excellent model stability. This method provided a perfect guideline for process quality control of Carbonized TCM as well as ensured their clinical efficacy.

Particle filter (PF) has been proven to be a powerful tool to solve visual tracking problem. However, the problem of sample impoverishment is a constraint of PF. To solve this problem, a cuckoo search-based particle filter is proposed. The particles in PF are optimized using cuckoo search. The meaningful particles are increased and can approximate the true state of the target more accurately. Experiments on visual tracking show that the proposed algorithm outperforms the standard particle filter in solve the visual tracking problems with various challenging conditions.

Aiming for the least squares method, all the points in the region are used as the features to be extracted. There is a problem that the computational complexity is large and it is easy influenced by edge interference information, which leads to inaccurate feature extraction. The self-tuning feature extraction method fusing mean clustering and K-L transform is proposed. The principal component analysis method is used to ensure that the extracted line features are consistent with the distribution of the main data points. The self-tuning feature extraction method can remove edge interference information through the clustering center calculation, parallel area division and other operations. It improves the accuracy of line feature extraction. Compared to the least squares method, K-L transform is faster and has better real-time performance.

In view of solar arrays applied in large-scale stratospheric airship, modular thinking was proposed by reasonable decomposition of solar array to design composite maximum power point tracking (MPPT) controller where the input and output are both in parallel, which ensures maximized solar energy output on a limited area. And each solar array sub-model was equipped with independent MPPT controller to control power tracking separately. Then, the solar array composed of three sub-models was used for simulation and its result indicates that MPPT controller of each sub-model can track the power quickly, and the output power can reach 93% of maximum input power when the efficiency loss of converter in reality is not considered . So, the model constructed in this paper can be used to optimize the design and analyze output characteristics quantitatively for the large-scale stratospheric airship's solar array.

As one of the key technic of achieving high-altitude and long-time flight, the stratospheric airship energy system in stratosphere is always the important point but also very difficult. In this paper, the stratospheric airship geometry analysis as a starting point, through a series analysis as follow: the stratospheric airship surface mesh model, the sun vector, the relationship between the sun vector and the body coordinate system, and the solar radiation model, we have accomplished the characteristics analysis of the radiation receiving on stratospheric airship. The analysis result show that: Although different flight direction corresponding to different distribution of light intensity, the light changes from sunrise to sunset is symmetrical when the stratospheric airship on the condition of level flight. Airship for east heading of region resides, the maximum energy can be obtained when the solar array laying in the installation of 0 β π / 4. With the changing of heading angle and pitch angle, the radiation receiving of the solar array can also transform, but the influence of pitch angle greater than heading angle.

The Internet of Things(IOT) is used very widely in various of fields, it brings great convenience to people and promotes social civilization and progress. Focused on the development of IOT and some key technologies which are applied by it, and pointed out its trend of development.

High computational complexity and long time computation are the main characteristics for cloud detection based on texture feature. It affects the real time of cloud detection based on texture feature. So a parallel architecture for cloud detection is proposed, according to the characteristics of the algorithm on the basis of analyzing the computing property of the algorithm. The new parallel architecture is on the basis of the multi processing element(PE) parallel optimization method and pipeline optimization method base on run time and resource consumption. The parallel structure can improve the real time for the cloud detection algorithm. In order to verify the parallel structure for cloud detection proposed in the thesis, comparative analysis for run time, resource consumption and dynamic power between methods which have been proposed and the proposed method. It shows that the proposed method has the best run time, and decreases the area consumption effectively at the same time. It also decreases the dynamic power effectively.

In particle sizing with dynamic light scattering (DLS) technique, the determination of particle size distribution (PSD), via inversing the autocorrelation function (ACF) of scattering light, is usually limited by the inherently low particle size information in ACF data and, the lack of targeted inversion on the noise restriction and the particle size information utilization. For the ACF data in DLS measurement, most of particle size information is centrally contained in the decay section and the larger noise is contained in the larger delay section. However, no consideration of the particle size information distribution in the ACF data for the routine inversion method increases the difficulty of the accurate PSD inversion, especially the broad and bimodal PSDs. Until now, it is still a difficult problem to obtain an accurate recovery of the broad and bimodal PSDs, specifically the bimodal PSD with a peak position ratio less than 2:1 and containing large particles (350 nm). In this paper, a character-weighted constrained regularization (CW-CR) method is proposed, in which, the particle size information distribution in the ACF as the base and the adjustment parameter as the exponent are used to weight the ACF. By using the weighting coefficients corresponding to the particle size information distribution along the delay time in ACF, the CW-CR method can enhance the utilization of the particle size information in ACF data, and effectively weaken the effect of noise at large delay time. With this method, the closely spaced bimodal PSD (with nominal diameters of m 350 nm:500 nm in simulation, m 300 nm:502 nm in experiment) is recovered successfully at a high noise level of 0.01. It shows that the CW-CR method, combined with the multiangle DLS (MDLS) measurement, can effectively make the best use of the particle size information hiding in the noisy ACF data, and improve the resolution of bimodal PSD as well as the capability of noise suppression. So it can make the advantages of MDLS more highlighted than the routine method in the recovery of the broad and bimodal PSDs.

A simple theoretical method is introduced for studying the interrelation between electronic and molecular structures. By diagonalizing the 120 × 120 complete energy matrices, the relationships between zero-field splitting (ZFS) parameter D and local distortion parameter Δθ for Cr3+ ions doped, separately, in α- and β- alums are investigated. Our results indicate that there exists an approximately linear relationship between D and Δθ in a temperature range 4.2–297 K and the signs of D and Δθ are opposite to each other. Moreover, in order to understand the contribution of spin-orbit coupling coefficient ζ to ZFS parameter D, the relation between D and Δ is also discussed.

A simple theoretical method is introduced for studying the local molecular structure of the (MnO(6))(10) coordination complex. By diagonalizing the complete energy matrices of the electro-electron repulsion, the ligand field and the spin-orbit coupling for a d(5) configuration ion in a trigonal ligand field, the local distortion structure of the (MnO(6))(10) coordination complex for Mn(2-) ions in A PCC:Mn(2+) (PCC) - {[(CH(3))(2)N](2)OPOPO[N(CH(3))(2)](2)} (ClO(4))(2), A - Mg, Zn) complex systems is investigated. Both the second-order zero field splitting parameters b(2)(0) and the fourth-order zero field splitting parameter b(4)(0) are taken simultaneously in the structural investigation. From electron paramagnetic resonance (EPR) calculations, the local structure parameters R = 2.18 angstrom, theta = 56.38 degrees for Mn(2) ions in Mg PCC Mn(2+) and R = 2.20 angstrom, theta = 56.52 degrees for Mn(2+) complex systems are determined, respectively. It is found that the theoretical calculation results of the BPR spectra for Mn(2+) ions in A PCC:Mn(2+) complex systems are in good agreement with the experimental values. (c) 2009 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim