In the container terminal system,the effective quay crane assignment for vessels is helpful to ease the strain that berths and quay cranes are in short supply in container terminals and improve the operational efficiency of ports. Aiming at the integrated optimization problem of berth allocation and quay crane assignment of dynamic arriving vessels under continuous berth,the quay crane assignment for vessels was dynamically adjusted based on ship efficiency,a model with the purpose of minimizing the total cost containing delayed berthing cost,preference deviated berthing cost,delayed departure cost and quay crane reassignment cost was established,and a heuristic algorithm based on the adjustment rules of quay crane assignment was designed and Genetic Algorithm(GA) was used to solve the model. Finally,the experimental results verified the effectiveness of the proposed model and algorithm in solving the problem of berth allocation and quay crane assignment in actual ports,and by comparing with the results calculated by the traditional GA,the optimization effect of the proposed algorithm was proved.

In order to improve the efficiency of operation in container terminal and reduce the influence of uncertain interference factors on the operation of delivery trucks, a method of processing the interference factors by rolling-window strategy was proposed, a mixed integer model with the goal of minimizing the operation delay penalty cost and yard crane movement cost was proposed, and Genetic Algorithm (GA) was used to solve the model. Firstly, rolling-window strategy was used to obtain the scheduling scheme of the delivery trucks in the case of no interference factors. Secondly, when the interference factor occurred, the rolling-window rescheduling mechanism was triggered to reschedule the operation order of delivery trucks. Finally, the optimal scheduling scheme in each window was calculated, and the optimal operation plan in the total planning time was proposed. By comparing and analyzing the results of case solving in different scenarios, the experimental results show that the minimum operation cost under the rolling-window strategy is 9% lower than that under the traditional operation mode in the case without interference, and in the case with interference, the rolling-window strategy makes the cost reduced by 15% compared to the traditional operation mode, which verifies the effectiveness of the algorithm and the superiority of the rolling-window strategy for the delivery truck operation.

The container terminal system is a complex production system which is composed of many subsystems, and the equipment scheduling in the system is also a complex problem which involves a variety of uncertainties. The probability distribution of equipment operation parameters was considered emphatically, and the coordinated scheduling problem between quay crane and yard truck was studied. The method of multidisciplinary variable coupling design optimization with time window constraint was presented, the yard truck distribution sub-model and yard truck configuration sub-model were built. Completion time and the number of trucks were regarded as public design variables to connect the two submodels, and the coupling model for coordination scheduling was established. This model selected data from a terminal of Shanghai port, and called Gurobi4.0 to solve the coupling model under the environment of Visual studio2012. Compared the final scheduling project with the original project, the cost of total delay time decreased by 90.69%, and the number of container trucks decreased by 30.76%, which shows that the model is effective and practical.

Concerning the high costs of traditional action recognition algorithm in color video and poor recognition performance caused by insufficient two-dimensional information, a new human action recognition method based on three-dimensional depth image sequence was put forward. On the temporal dimension, Temporal Depth Model (TDM) was proposed to describe the action. Specially, the entire depth maps were divided into several sub-actions under three orthogonal Cartesian planes. The absolute difference between two consecutive projected maps was accumulated to form a depth motion map to describe the dynamic feature of an action. On the spatial-dimension, Spatial Pyramid Histogram of Oriented Gradient (SPHOG) was computed from the TDM for the representation of an action to obtain the final descriptor. Support Vector Machine (SVM) was used to classify the proposed descriptors at last. The proposed method was tested on two authoritative datasets including MSR Action3D dataset and MSRGesture3D dataset, the recognition rates were 94.90% (cross subject test) and 94.86% respectively. The experimental results demonstrate that the proposed method has fast speed and better recognition, also it meets the real-time requirement in the depth video sequence system basically.

Bayesian network is one of the most important theoretical models for the representation and reasoning of uncertainty. At present, its structure learning has become a focus of study. In this paper, a Bayesian network structure learning algorithm was developed, which was based on topological order and quantum genetic algorithm. With the richness of the quantum information and the parallelism of quantum computation, this paper designed generator strategy of topological order based on a quantum chromosome to improve not only the efficiency of search, but also the quality of Bayesian network structure. And then by using self-adaptive quantum mutation strategy with upper-lower limit, the diversity of the population was increased, so that the search performance of the new algorithm was improved. Compared to some existing algorithms, the experimental results show that the new algorithm not only searches higher quality Bayesian structure, but also has a quicker convergence rate.

The research on the evolutionary mechanisms and models of Protein-Protein Interaction (PPI) network is significant for understanding the evolution of the biological systems as well as the formation process of the organisms. So far, there have been kinds of models based on different evolutionary mechanisms. All of these models exhibit certain topological characteristics emerging from the protein-protein interaction networks, while some limitations exist simultaneously. This paper focused on several classic protein-protein interaction network models, analyzing the main ideas of these models and comparing the topological characteristics derived from them with those of real protein-protein interaction networks. A summary of the features for each model was given based on the experiments. At last, several viewpoints for the future research of protein-protein interaction network models were also proposed to provide a useful reference for further studies.

An effective registration approach was proposed for multiple-view images captured on a turntable. In combination with binocular stereo, a complete system for 3D reconstruction was proposed. The calibration target was mounted on a step-motor-controlled turntable and it was acquired under multiple views. The coordinate transformation between the turntable and the camera coordinate systems was computed by the angular point information on the calibration target. The coordinate transformation among multiple views was used for data registration at the fixed viewpoint. The experimental results show that the proposed registration method achieves high precision and can be effectively used in 3D reconstruction.

The existing Enterprise Service Bus （ESB） products can hardly fulfill enterprises' changeable requirements of business processes due to their absence or inadequacy of manageability, flexibility and openness. Importing work flow technology, an innovative ESB design scheme was proposed with component model as its basis, service chain as the design, deployment and management unit of ESB applications, and event-driven asynchronous messaging as the communication mechanism. Our work has been applied in the NPUESB system. Results prove that the design can not only effectively realize enterprise application integration, but also efficiently implement and manage ESB applications and deal with changeable enterprise business processes, meanwhile possessing good openness and scalability properties.