In automated industrial scenarios， the amount of time series log data generated by a large number of industrial devices has exploded， and the demand for access to time series data in business scenarios has further increased. Although HBase， a distributed column family database， can store industrial time series big data， the existing strategies cannot meet the specific access requirements of industrial time series data well because the correlation between data and access behavior characteristics in specific business scenarios is not considered. In view of the above problem， based on the distributed storage system HBase， and using the correlation between data and access behavior characteristics in industrial scenarios， a distributed storage performance optimization strategy for massive industrial time series data was proposed. Aiming at the load tilt problem caused by characteristics of industrial time series data， a load balancing optimization strategy based on hot and cold data partition and access behavior classification was proposed. The data were classified into cold and hot ones by using a Logistic Regression （LR） model， and the hot data were distributed and stored in different nodes. In addition， in order to further reduce the cross-node communication overhead in storage cluster and improve the query efficiency of the high-dimensional index of industrial time series data， a strategy of putting the index and main data into a same Region was proposed. By designing the index RowKey field and splicing rules， the index was stored with its corresponding main data in the same Region. Experimental results on real industrial time series data show that the data load distribution tilt degree is reduced by 28.5% and the query efficiency is improved by 27.7% after introducing the optimization strategy， demonstrating the proposed strategy can mine access patterns for specific time series data effectively， distribute load reasonably， reduce data access overhead， and meet access requirements for specific time series big data.

Point cloud data has sparsity， irregularity， and permutation invariance， and lacks topological information， which makes it difficult to extract features of point cloud. Therefore， a Siamese Adaptive Graph Convolution Algorithm （SAGCA） was proposed for point cloud classification and segmentation. Firstly， the topological relationships between irregular and sparse point cloud features were mined by constructing feature relationship graph. Then， the Siamese composition idea of sharing convolution learning weights was introduced to ensure the permutation invariance of point cloud data and make the topological relationship expression more accurate. Finally， SAGCA was combined with various deep learning networks for processing point cloud data by both global and local combination methods， thereby enhancing the feature extraction ability of the network. Comparison results with PointNet++ benchmark network of the classification， object part segmentation and scene semantic segmentation experiments on ScanObjectNN， ShapeNetPart and S3DIS datasets， respectively， show that， based on the same dataset and evaluation criteria， SAGCA has the class mean Accuracy （mAcc） of classification increased by 2.80 percentage points， the overall class average Intersection over Union （IoU） of part segmentation increased by 2.31 percentage points， and the class mean Intersection over Union （mIoU） of scene semantic segmentation increased by 2.40 percentage points， verifying that SAGCA can effectively enhance the feature extraction ability of the network and is suitable for multiple point cloud classification and segmentation tasks.

Privilege deduction relation makes the authorization management easier, and at the same time it also causes the calculation of valid privileges more difficult. Therefore, it is important for authorization and access control to calculate deduction relations between privileges correctly and efficiently. Based on the resource hierarchy and operation hierarchy, the rule of privilege deduction was given in this paper. According to the fact that privilege query happens more frequently than privilege update, a new method of calculating deduction relations based on reachability matrix of privilege deduction was proposed. The experimental results show that the new method is more efficient than the way calculating deduction relations directly.

TCP Friendly Rate Control (TFRC) is a congestion control mechanism designed for non-TCP flows. Due to that not all losses are related to congestion in wireless network, to adopt initial TFRC will induce maloperations. In the paper, biased queue method was used to distinguish congestion losses from random losses. It would prevent unnecessary congestion control and would improve the quality of transmission in wireless networks. Through simulations and experiments, it is found that the method can greatly improve the stability of transport rate, finally accomplishes QoS of application layer.

Simulation of radar scanning is one of the difficulties in the visual simulation of battlefield situation. To introduce a real-time simulation method of three-dimensional scanning radar based on particle system. According to the rule of radar scan, the traditional particle system model was changed, and the radar afterglow particles were rendered with point. It was implemented on Personal Computer with OpenGL. The result shows that the method is able to meet the needs of reality and real time.

A new method for matching feature points of images from two cameras of a stereo vision system in the game engine was presented. The main issue is how to meet the request of real-time processing and accuracy of the system. Our method is to calibrate the epipolar constrains and calculate the offset of two image along with the constraints of homography. Then we used a fast method to match the feature points in a local area. This method is proved to be real-time and accurate enough to fulfill the request of our game engine.

Parameterization is the basic principle of 3D games modeling and the crucial technique in surface fitting. A new algorithm for mesh parameterization was proposed. Attach a convex boundary for non-convex mesh and then parameterize the interior vertices based on mean value coordinate method. This algorithm was applied to the modeling module of game engine, and the experimental results demonstrate the feasibility and efficiency of the method.

An approach based on smoothed particle hydrodynamics to simulate fluids with free surfaces was proposed, while surface tension was modeled by using Van der Waals equation of state with a combination of short-range repulsive and longer-range attractive interactions between fluid particles, finally a GPU-based particle splatting algorithm was designed for rendering. This approach completely avoids the temporal discretization artifacts, which results in the interactive rendering effects with high quality. In contrast to traditional Lagrangian approaches, this method uses the simplified surface tension model with fast rendering algorithm, reduces the complexity of the simulation and efficiently advances the run-time speed.

Physical-based deformable models have been popular in the field of computer graphics. The most significant contributions were presented including Euler method, mass-spring system, finite element, boundary element, smoothed particle hydrodynamics and meshfree method. The connection to the simulation of other continua was also discussed, such as fluid, fire, gas, lava flow and melting objects for completeness. Finally, the areas of application were summarized, such as elastoplastic deformation and fracture, cloth and thin shell simulation, sand and mud animation, interactive entertainment. Future research areas were also described.

As TCP Friendly Rate Control (TFRC) is used in the application of the Real-Time Streaming Media, the fluctuation of the sending rate is obvious. It is harmful to the transmission of the Real-Time Streaming Media. This essay employed Relaxation Algorithm to limit the variation of the sending rate of the TFRC flow adaptively. It made the sending rate of the TFRC flow more smooth and constringent. The experimental results show that Relaxation Algorithm can improve the capability of TFRC while guaranteeing the high quality of transmission of the Real-Time Streaming Media.