To solve the long training time and slow convergence problems when applying SAC （Soft Actor-Critic） algorithm to the local path planning of mobile robots， a PER-SAC algorithm was proposed by introducing the Prioritized Experience Replay （PER） technique. Firstly， to improve the convergence speed and stability of the robot training process， a priority strategy was applied to extract samples from the experience pool instead of the traditional random sampling and the network prioritized the training of samples with larger errors. Then， the calculation of Temporal-Difference （TD） error was optimized， and the training deviation was reduced. Next， the transfer learning was used to train the robot from a simple environment to a complex one gradually in order to improve the training speed. In addition， an improved reward function was designed to increase the intrinsic reward of robots， and therefore， the sparsity problem of environmental reward was solved. Finally， the simulation was carried out on the ROS （Robot Operating System） platform， and the simulation results show that PER-SAC algorithm outperforms the original algorithm in terms of convergence speed and length of the planned path in different obstacle environments. Moreover， the PER-SAC algorithm can reduce the training time and is significantly better than the original algorithm on path planning performance.

In the research of image classification tasks in deep learning， the phenomenon of adversarial attacks brings severe challenges to the secure application of deep learning models， which arouses widespread attention of researchers. Firstly， around the adversarial attack technologies for generating the adversarial perturbations， the important white-box adversarial attack algorithms in the image classification tasks were introduced in detail， and the advantages and disadvantages of different attack algorithms were analyzed. Then， from three realistic application scenarios： mobile application， face recognition and autonomous driving， the application status of the white-box adversarial attack technologies was illustrated. Additionally， some typical white-box adversarial attack algorithms were selected to perform experiments on different target models， and the experimental results were analyzed. Finally， the white-box adversarial attack technologies were summarized， and their valuable research directions were prospected.

Aiming at the problem that the key entity information in the police field is difficult to recognize， a neural network model based on BERT （Bidirectional Encoder Representations from Transformers）， namely BERT-BiLSTM-Attention-CRF， was proposed to recognize and extract related named entities， in the meantime， the corresponding entity annotation specifications were designed for different cases. In the model ，the BERT pre-trained word vectors were used to replace the word vectors trained by the traditional methods such as Skip-gram and Continuous Bag of Words （CBOW）， improving the representation ability of the word vector and solving the problem of word boundary division in Chinese corpus trained by the character vectors. And the attention mechanism was used to improve the architecture of classical Named Entity Recognition （NER） model BiLSTM-CRF. BERT-BiLSTM-Attention-CRF model has an accuracy of 91% on the test set， which is 7% higher than that of CRF++ Baseline， and 4% higher than that of BiLSTM-CRF model. The F1 values of the entities are all higher than 0.87.

Concerning the low efficiency of present methods of IP lookup, a new data lookup algorithm based on Multi-Bit Priority Tries (MBPT) was proposed in this paper. By storing the prefixes with higher priority in dummy nodes of multi-bit tries in proper order and storing the prefixes for being extended in an auxiliary storage structure，this algorithm tried to make the structure find the longest matching prefix in the internal node instead of the leaf node. Meanwhile, the algorithm avoided the reconstruction of router-table when it needed to be updated. The simulation results show that the proposed algorithm can effectively minimize the number of memory accesses for dynamic router-table operations, including lookup, insertion and deletion, which significantly improves the speed of router-table lookup as well as update.

Concerning the deficiency of the digital image scrambling algorithm in double scrambling, an image scrambling algorithm based on cloud model was proposed. The algorithm used the function value generated by the three-dimensional cloud model to change the positions and values of the image pixels, to achieve a double scrambling. The experimental verification as well as quantitative and qualitative analysis show that the scrambling image renders white noise and realizes the image scrambling. There is no security issue on cyclical recovery. The algorithm can quickly achieve the desired effect, resistant to shear, plus noise, filtering and scaling attacks. This proves that the algorithm is effective and reasonable, and also can be better applied to the image scrambling.

The traditional baud spaced equalizer is used to compensate the aliasing frequency response characteristics of the received signal, but it cannot compensate the channel distortion. Concerning this problem, a normalized cumulant blind equalization algorithm based on oversampling technology was proposed. The received signal was oversampled firstly, and then the variable step-size was used to adaptively adjust weight coefficients of equalizer. It can not only avoid falling into local optimum, but also compensate the channel distortion effectively. The simulation results show that the algorithm can effectively speed up the convergence, and reduce the steady residual error.

To effectively use the chaotic system, a scale design method based on Chen's chaotic system was proposed in this paper. Scaling transformation and differential to integral conversion were performed on the Chen's system, and the characteristics of the scaled Chen's system were analyzed in detail. The scaled Chen's chaotic circuit was taken by the system as model with common electronic circuit structures. The synchronization of the drive and response systems could be realized by carrying out unidirectional single-variable linking substitution method on the scale system. The theoretical analyses and hardware experimental results show that the proposed method can be applied to industrial production directly.

Since the present network security assessment methods cannot evaluate vulnerability relevance effectively, a vulnerability threat assessment method based on relevance was presented. Firstly, an attack graph must be created as the source data. Secondly, by taking both pre-nodes and post-nodes diversity into consideration, integrating the methods of Forward In (FI) and Backward Out (BO), the authors calculated the probability of vulnerability being used on multiple attack routes through optimizing calculation formulas originating from Bayesian network, then the weighted average method was utilized to evaluate the risk of certain vulnerability on a particular host, and finally the quantitative results were achieved. The experimental results show that this method can clearly and effectively describe the security features of systems.

In order to increase the efficiency of the line drawing algorithm when the slope of the line is greater than 0.5, a line drawing algorithm based on pixel chain was proposed. A straight line was treated as an aggregation of several horizontal pixel chains or diagonal pixel chains. An algorithm of line drawing in a reverse direction, which was similar to Bresenham algorithm, was introduced, by which the slope between 0.5 and 1 was converted to that between 0 and 0.5 while generating line. One pixel chain was generated by one judgment. The simulation results show the straight line generated by new algorithm is as same as that generated by Bresenham algorithm, but the calculation is greatly reduced. The new algorithm has generated two integer arithmetic: addition and multiplication, and it is suitable for hardware implementation. The generation speed of the new algorithm is 4 times of Bresenham algorithm with the same complexity of design.

To deal with the gradient problem in the clustering process of text extraction, an algorithm based on binary clustering was proposed. The original image was converted to binary bitmap after preprocessing. The background blocks of the image were clustered by the region features, and then text blocks were recognized by the distribution features. The experiment shows this method achieves satisfactory result on various kinds of images.

Component-based software was considered as Markov process. To attach more attention to the reliability of links and become fit to different Markov process states, different state components and link use frequency computing models were proposed. Then, the calculation method for reliability of component-based software was presented, and an example was also given. Compared with traditional methods, the proposed method not only provides a more accurate analysis method for the reliability of software, but also widened the application of the model.

Because the heterogeneous information is relatively loose and independent in seamless transportation, data grid is adopted to manage the distributed heterogeneous information and realize resources share and information integration. The paper presents a architecture of seamless transportation information grid(STIG),the architecture integrates Information integration, semantic query, transportation planning, etc key technologies. At last, take combined rail and sea transport for example, the process of multimodal transportation based on STIG was described.

XML is a de facto standard for exchanging and presenting information on the Web. However, XML data is also recognized as verbosity since it heavily inflates the data size due to the repeated tags and structures. The data verbosity problem gives rise to many challenges of conventional query processing and data exchange. The hindrance is more apparent in bandwidth- and memory-limited devices. Compression techniques are the important way to overcome the verbosity problem. Multifarious XML-conscious compression methods were collected, and six XML-conscious compression technologies were compared and analyzed in terms of compression ratio, compression and decompression times, memory consumption, and query performance. Their advantages and shortcomings were discussed, and then further work of XML-conscious compression was pointed out.