Knowledge Graph (KG) strongly support the research of knowledge-driven artificial intelligence. Aiming at this fact, the existing technologies of knowledge graph and knowledge hypergraph were analyzed and summarized. At first, from the definition and development history of knowledge graph, the classification and architecture of knowledge graph were introduced. Second, the existing knowledge representation and storage methods were explained. Then, based on the construction process of knowledge graph, several knowledge graph construction techniques were analyzed. Specifically, aiming at the knowledge reasoning, an important part of knowledge graph, three typical knowledge reasoning approaches were analyzed, which are logic rule-based, embedding representation-based, and neural network-based. Furthermore, the research progress of knowledge hypergraph was introduced along with heterogeneous hypergraph. To effectively present and extract hyper-relational characteristics and realize the modeling of hyper-relation data as well as the fast knowledge reasoning, a three-layer architecture of knowledge hypergraph was proposed. Finally, the typical application scenarios of knowledge graph and knowledge hypergraph were summed up, and the future researches were prospected.

To solve the problems of too long time of pathfinding and collision and blocking during movement in real-time strategy games， a combined improved flow field pathfinding algorithm was proposed. Firstly， the red-black tree was used to store data to improve the speed of data access. Secondly， by using the penalty function， the calculation of the integration field cost was simplified through transforming the nonlinear partial differential equation problem into a linear unconstrained problem. Finally， a pre-adjacency node was introduced to generate the flow direction. Compared with the flow field pathfinding algorithm without improvement， the improved algorithm has the path calculation time reduced by 20%， and the average moving time is stable at 20 s. Experimental results show that the improved flow field pathfinding algorithm can effectively shorten the pathfinding time， increase the moving speed of Agents and improve the level of game artificial intelligence in real-time strategy games.

For the inefficiency and imbalance between robustness and imperceptibility of most of the current audio watermarking algorithms when applied to MP3 audio, a watermarking algorithm in compressed domain based on low frequency energy of channels of MP3 frames was proposed. The watermarking can be embedded and extracted during MP3 compression and decompression processes, which greatly enhances the efficiency. Considering the good stability of low frequency energy, the low frequency energy of channels was calculated by using Modified Discrete Cosine Transform (MDCT) coefficients produced in MP3 encoding and decoding processes, then the ratio between the energy of left and right channels was quantized with fixed step, and the watermarking was embedded by modifying some MDCT coefficients according to quantified results. Meanwhile, with the proportion of energy in different scalefactor bands, the embedding bands were selected before calculating low frequency energy of channels, which ensured a good balance between robustness and imperceptibility. The experimental results show that the proposed algorithm has a good robustness against various types of attacks while maintaining the original audio quality, especially against MP3 recompression attacks.

Aiming at the problem that the traditional video monitoring method can not divide the dense foreground objects accurately, a multi-target video monitoring method based on Adaboost and codebook model was proposed. Firstly, the Adaboost human head classifier was obtained by training, and the background model was established for the vertical elevator image by the codebook algorithm. The foreground image was extracted and heads were detected and tracked. After that, the pedestrian targets were removed to get the object targets, and the object targets were tracked. Finally, the movement of pedestrians and objects was monitored. The experimental results on 12 entrance area videos show that the method can track pedestrians and objects accurately and stably. It can accomplish the monitoring tasks of retrograde detection, passenger statistics, pedestrian congestion and object retention. With the processing speed of 36 frames per second, the tracking-accuracy rate is above 94% and the monitoring-accuracy rate is 95.8%. The proposed algorithm meets robustness, real-time and accuracy requirements of the intelligent video monitoring system.

As the source of the haze data, the reliability of the haze monitoring sites is very important to the reliability of the big data. Due to the lack of effective evaluation method for the haze monitoring points, the monitoring data is not reliable enough. In order to solve the problem that the perceived data was not reliable, a kind of perceptual source trust evaluation and selection model was proposed based on the data trigger detection method. When the perceived data arrived, the K-Means clustering algorithm and the statistical results were firstly used to calculate the benchmark data, then the trust degree of data was calculated by using the current perceived data, the benchmark data and the threshold values. Secondly, according to the location of the perceptual source, neighbor relationship was determined. The current perceived data and the data of the neighbors were compared, according to the absolute value of the difference and the value of the threshold, the neighbor recommendation trust degree was calculated. Finally, the comprehensive trust degree was calculated by using the truest degree of perceived data, the historical trust degree and the recommendation trust degree of the neighbor. The initial value of the historical trust was set as the number of monitoring items, and then updated by the comprehensive trust. Theoretical analysis and simulation results prove that the proposed method can effectively evaluate the perceived source, avoid the abnormal data, and reduce post processing overhead.

In Dynamically Tuned Gyroscope (DTG) system, traditional identification methods, including least square identification method and traditional frequency domain identification method, could not achieve acceptable identification fitness degree. To deal with this problem, outlier-eliminated frequency identification method was proposed. In consideration of the characteristics of DTG model structure and intrinsic colored noise, outlier-eliminated method was applied to DTG frequency domain identification. The experimental results indicate that outlier-eliminated frequency identification method, with a fitness degree above 90%, compared with both least square identification method and traditional frequency domain identification method, has a better performance. In addition, outlier-eliminated frequency identification method possesses of good repeatability and stability. Outlier-eliminated frequency identification method could improve the identification fitness degree of DTG system.

IntraVascular UltraSound (IVUS) imaging can provide information of the coronary atherosclerotic plaque. It allows the doctor to make comprehensive and accurate evaluation of diseased vessel. Some ultrasound data collecting devices for imaging system exhibited insufficient data transfer speed, high cost or inflexibility, so the authors presented a high speed data transfer and imaging method for intravascular ultrasound. After being collected and processed, ultrasound data was transferred to computer through USB3.0 interface. In addition, logarithmic compression and digital coordinate conversion were applied in computer before imaging. Data transmission experiment shows that the transfer speed always stays around 2040Mb/s. Finally, phantom imaging was conducted to demonstrate the performance of the system. It shows a clear pipe wall and a smooth luminal border.

Concerning the medium access control shortcoming of wireless network, a sort of new algorithm was proposed in this paper. The algorithm was based on the dynamic p-persistent algorithm and its kernel idea was derived from virtual transmission or virtual thread. The aim that provided more information for the dynamic p-persistent algorithm to obtain the optimal transmission probability was to increase available efficiency of wireless bandwidth. The simulations show that the proposed algorithm increases throughput about 27%, and reduces collision rate about 28% on average.

The problem how to render the important information of the volume data qualitatively in medical visualization needs to be resolved urgently. The method of designing high dimensional transfer function interactively according to the high dimension histogram was used widely, but this method is complex and is of low quality. To solve the design problems of the characteristic high dimensional transfer function, a volume rendering method of automatic and interactive design of high dimensional transfer function based on K-Means++ clustering algorithm was presented in this paper. Firstly, feature extraction was done on the volume data, then to cluster the feature space, K-Means++ clustering algorithm was used, and the group of label transfer function was generated automatically. Finally, a convenient interactive user interface was provided to users to adjust. The GPU (Graphic Processing Unit) based volume rendering was used to perform the strong parallel computing ability for real-time rendering. The experimental results show that this method can eliminate the complexity of the design of high dimensional transfer function, and many kinds of human body organization structure characteristics can be shown in the rendering results.

To meet the physiological perception of human eyes, a color image enhancement algorithm based on improved Intersecting Cortical Model (ICM) was proposed. The internal activities and dynamic threshold were improved to nonlinear attenuation, which satisfied the nonlinear perception of human eyes. And the decay factor was replaced by the step factor, while maintaining some of the significant features of the original model. It applied the Threshold Versus Intensity (TVI) function of the human visual system on the intensity component of the input image to adjust the dynamic range compression. At the same time, it also adjusted the saturation component of the input image by nonlinearity. Compared to the original ICM, this algorithm reduced the complexity and improved the adaptability. The experimental results confirm that the method can obtain clear and bright results.

Since the traditional Geographic Information System (GIS)'s structured or semi-structured attribute query poses sort of limitation on input accuracy and scope of query sentences, a GIS descriptive query method for text-related non-structured text data was suggested based on the expanded version of a dictionary of English synonyms, TongYiCi CiLin. compiled by Harbin Institute of Technology. Basic process is to calculate correlation between descriptive query sentence and text connected to the geographic element, then getting general query results according to it. The comparison experiment shows that descriptive query method not only supports diversity of input query sentence, but also effectively gets geographic element related to input descriptive query.

The Adaptive Resonance Theory 2 (ART2) is one of well-known clustering algorithms and has been applied to many fields practically. However, to be a clustering algorithm for two-dimension spatial data, it not only has the shortcomings of pattern drift and vector model of information missing, but also is difficult to adapt to spatial data clustering of irregular distribution. A Tree-ART2 (TART2) network model was proposed. It retained the memory of old model which maintained the constraint of spatial distance by learning and adjusting Long Time Memory (LTM) pattern and amplitude information of vector. Meanwhile, introducing tree structure to the model could reduce the subjective requirement of vigilance parameter and decrease the occurrence of pattern mixing. The comparative experimental results show that TART2 network is suitable for clustering about the ribbon distribution of spatial data, and it has higher plasticity and adaptability.

Aiming at the all-pairs shortest-path problem in the directed graph,a practical parallel algorithm,which based on the Floyd algorithm with an extended path array,was brought forward on 2-D mesh network.The planar evenly partition method was chosen for task division in this parallel algorithm.The parallel algorithm was implemented on MPI on NOW.The theoretical analysis and the experimental results prove that the parallel algorithm is an efficient and scalable algorithm.