We propose a multiresolution volume simplification and polygonization algorithm. Traditionally, voxel-based algorithms lack the adaptive resolution support and consequently simplified volumes quickly lose sharp features after several levels of downsampling, while tetrahedral-based simplification algorithms usually generate poorly shaped triangles. In our method, each boundary cell is represented by a carefully selected representative vertex. The quadric error metrics are applied as the geometric error metric. Our approach first builds an error pyramid by bottom-up cell merging. We avoid topology problems in hierarchical cell merging by disabling erroneous cells and penalizing cells containing disconnected surface components with additional costs. Then, a top-down traversal is used to collect cells within a user specified error threshold. The surfacenets algorithm is used to polygonize these cells. We enhance it with online triangle shape optimization and budget control. Finally, we discuss a novel octree implementation which greatly eases the polygonization operations.
Recently, the restricted Boltzmann machine (RBM) has aroused considerable interest in the multiview learning field. Although effectiveness is observed, like many existing multiview learning models, multiview RBM ignores the local manifold structure of multiview data. In this article, we first propose a novel graph RBM model, which preserves the data manifold structure and is amenable to Gibbs sampling. Then, we develop a multiview graph RBM model on the basis of the graph RBM, which performs local structural learning and multiview representation learning simultaneously. The proposed multiview model has the following merits: 1) it preserves the data manifold structure for multiview classification and 2) it performs view-consistent representation learning and view-specific representation learning simultaneously. The experimental results show that the proposed multiview model outperforms other state-of-the-art multiview classification algorithms.
The principle and applications of the support vector machine(SVM) are briefly reviewed.Firstly,the background and the development prospects of SVM are described and then the definition,classification and algorithms of SVM are briefly introduced.Finally,we discussed the SVM-based applications,such as in text identification,handwritten numeral recognition,face detection,recognition and verification,regression analysis and prediction,image retrieval,feature selection and so on.
File lock mechanism is an important technique of controlling concurent processes accessing the file in order to protect integrity and consistency of the data.This paper summarizes the file lock technology of the Unix system and its implementation principle,characteristics and core implementation of all kinds of document locks,and problems of deadlock.
This paper presents a new approach for preventing cascading outage by coordinated system and local monitoring and control scheme. System monitoring evaluates the vulnerability and security of the power system during dynamic changing conditions. It finds the vulnerable power system components indicating that their protective relays need to be monitored closely. Local monitoring can provide the exact disturbance information and monitor the correctness of the actual relay operations. If the relays act improperly, the proposed approach enables one to mitigate the disturbance or prevent the possible cascading outage. Further system control actions may be chosen based on the local information update. Several examples using the IEEE test system demonstrate the advantages of this approach.
This study rapidly identified and quantified the chemical components of the Wuzhuyu Decoction nanophase(WZYD-N) and suspension phase(WZYD-S) using ultra-high performance liquid chromatography coupled with triple quadrupole mass spectrometry(UPLC-QQQ-MS/MS). Based on preliminary pharmacodynamic experiments and network pharmacology analysis, the differential anti-inflammatory and analgesic activities of WZYD-N and WZYD-S were explored to understand their pharmacodynamic basis. WZYD-N and WZYD-S were separated by differential centrifugation-dialysis, and their particle size, Zeta potential, PDI, and morphology were characterized by dynamic light scattering and transmission electron microscopy. A method was established to quantify 23 representative components of WZYD using UPLC-QQQ-MS/MS, clarifying the differences in component content between the two phases. The anti-inflammatory and analgesic activities of WZYD-N and WZYD-S were preliminarily investigated using the acetic acid-induced enhanced capillary permeability inflammation model and the acetic acid writhing pain model. Network pharmacology was applied to screen the key anti-inflammatory and analgesic targets and active components of WZYD, and the relationship between the components and pharmacodynamics of WZYD-N and WZYD-S was analyzed based on quantitative results. The results showed that WZYD-N primarily consisted of spherical self-assembled aggregates around 200 nm, with a PDI of approximately 0.299 and a zeta potential of-22.1 mV. With an equivalent amount of crude drugs, obacunone and dihydroevocarpine were quantified in equal amounts in WZYD-N and WZYD-S. The content of rutaecarpine, evocarpine, rutaevine, limonin, and ginsenoside Ro was higher in WZYD-S, while 15 other components, including evodiamine, dehydroevodiamine, ginsenoside Re, 6-gingerol, and ginsenoside Rg_1, were higher in WZYD-N. Moreover, 6-dehydrogingerdione was low in both WZYD-N and WZYD-S. Preliminary pharmacodynamic experiments showed that WZYD-N could reduce the number of writhing responses and inhibit pain responses induced by acetic acid in mice, exhibiting analgesic effects similar to the WZYD group. WZYD-S could reduce the absorbance value of the intraperitoneal lavage fluid in mice, exhibiting anti-inflammatory effects comparable to the WZYD group. Network pharmacology analysis indicated that dehydroevodiamine, rutaecarpine, 6-gingerol, and ginsenoside Rg_1 might be the analgesic active components of WZYD, and limonin, rutaevine, and ginsenoside Ro might be the anti-inflammatory active components of WZYD. This study proposed a novel strategy for elucidating the pharmacodynamic basis of WZYD and innovating classical formulas.
Gyro-less attitude and angular rate estimations are of great importance in small, low-cost spacecraft, where high performance gyroscopes are not available due to multiple limitations. Recent development of accurate, high-bandwidth attitude sensors such as high data-rate star trackers, makes this approach implementable. The gyro-less estimator propagates the estimated states by nonlinear attitude dynamics model, and obtains measurements from nonlinear observer. The state estimation of such nonlinear systems requires approximation of the system equations, as done by the classical extended Kalman filter (EKF), or approximation of the probability densities, as done by Unscented Kalman filter (UKF) including linear regression Kalman filters (LRKFs). In particular, LRKFs utilize a set of deterministically chosen sample points, namely the sigma points, to approximate the state and measurement probability density function. However, the sigma points required in LRKFs grow linearly with the dimension of the state space, which becomes an obstacle for their onboard implementation for overload computational complexity. In this paper, we propose a partial-state sigma-point filter that retains the benefits of LRKFs' ability to deal with nonlinearity and is free from Jacobian matrices derivation. In the proposed filter, the state is decomposed into two parts: the directly observed part of the attitude, and the indirectly observed parts of the angular rate and acceleration. The state and covariance for attitude are approximated based on the geometric simplex transform, which utilize symmetric 4-sigma points to capture the first two moments of a vector in three-dimensional Euclidean space. The remaining states and process noises are treated based on marginalized conditional sigma-point transformation. Therefore, the proposed algorithm requires only four-sigma points to realize a ten-state estimation (attitude, angular rate and angular acceleration). In addition, similar precision to classical UKF is guaranteed and a significantly lower computational complexity is achieved. The performance of the new algorithm is demonstrated by simulations.
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