In order to solve the Vehicle Routing Problem with Simultaneous Pickup-Delivery and Time Windows (VRPSPDTW)in the context of reverse logistics,the corresponding vehicle routing problem model was established according to the actual situation and solved by memetic algorithm. In the process of solving the model,the Guided Ejection Search (GES)was used to generate the initial population. In the process of population evolution,the Edge Assembly Crossover (EAX)method was used to generate the offspring,and in order to improve the quality of solutions and the search efficiency of algorithms,multiple neighborhood structures were used to repair and educate the offspring. The performance of memetic algorithm was tested and compared with Genetic Algorithm (GA),parallel-Simulate Annealing algorithm (p-SA) and Discrete Cuckoo Search(DCS)algorithm on Wang and Chen test dataset. Experimental results show that the proposed algorithm obtains the current optimal solutions when solving all small-scale examples;the algorithm updates or achieves current optimal solutions on 70% examples when solving the standard-scale examples,and the obtained optimal solution has more than 5% improvement compared with the current optimal solution,fully verifying the good performance of the algorithm for solving VRPSPDTW.

For the problems of scope decision-making of maintenance for civil aviation engine module and cost optimization of full-life maintenance, the engine module maintenance level decision-making and cost optimization model based on annealing frog leaping particle swarm optimization algorithm with return time interval as variable was proposed. Firstly, according to the maintenance logic diagram for each module in maintenance instruction manual and the replacement situation of life-limited parts, the engine shop visit cost function was built. Secondly, by using the annealing frog leaping particle swarm optimization algorithm, the shop visit costs of different return times and the maintenance level for each module in full life time were determined. Finally, based on examples, the proposed algorithm was compared with the basic particle swarm optimization algorithm, annealing particle swarm optimization algorithm and shuffled frog leaping optimization algorithm, and the influence of different return times on maintenance cost and reliability was analyzed. Experimental results indicate that, when the engine has five shop visits in its full life time, the average cost obtained using annealing frog leaping particle swarm optimization algorithm was 322.479 1 $/flight hour, which was the optimum value compared with those of the other three optimization algorithms. The proposed algorithm can facilitate the shop visit decision-making of airlines and overhaul companies.

Focusing on the problem that the Retrieval Matching Question and Answer (RMQA) model has weak adaptability to Chinese corpus and the neglection of semantic information of the sentence, a Chinese text semantic matching model based on Convolutional neural network Latent Semantic Model (CLSM) was proposed. Firstly, the word- N-gram layer and letter- N-gram layer of CLSM were removed to enhance the adaptability of the model to Chinese corpus. Secondly, with the focus on vector information of input Chinese words, an entity attention layer model was established based on the attention mechanism algorithm to strengthen the weight information of the core words in sentence. Finally, Convolutional Neural Network (CNN) was used to capture the input sentence context structure information effectively and the pool layer was used to reduce the dimension of semantic information. In the experiments based on a medical question and answer dataset, compared with the traditional semantic models, traditional translation models and deep neural network models, the proposed model has 4-10 percentage points improvement in Normalized Discount Cumulative Gain (NDCG).

The security mechanism of REpresentational State Transfer (REST) architecture is not perfect. In order to solve the problem, the security analysis and evaluation of REST architecture based on attack graph was proposed, and the security quantitative evaluation of REST architecture was realized by using attack graph. Firstly, the possible attack of REST architecture was predicted, the REST architecture attack graph model was constructed accordingly, and the attack probability parameter and attack realization parameter were calculated. Then, according to the attack state and attack behavior of attack graph, the security protection measures were proposed. In view of the above, the REST architecture attack graph model was reconstructed, and the attack probability parameter and attack realization parameter were recalculated too. By comparison, after the adoption of security protection measures, the attack possibility parameter has been reduced to about 1/10, and the attack realization parameter has been reduced to about 1/86. The comparison results show that the constructed attack graph can effectively and quantitatively evaluate the security performance of REST architecture.

To effectively overcome the free-rider problem existing in Peer-to-Peer (P2P) network, this paper presented resource allocation scheme based on Nash bargaining which guarantees the minimum Quality of Service (QoS). Firstly, the article built the system model of the minimum QoS, analysis indicated that the cooperative peer' bargaining power is positively related to the maximum contribution ability but the non-cooperative peer' bargaining power is negative related to the maximum contribution ability, so, the cooperative peers can obtain more resources than non-cooperative peers; secondly, the article demonstrated that the cooperative peer who has larger relative bargaining power could obtain more resources than the others. Lastly, simulations show that to guarantee the peers receiving the minimum QoS, the cooperation peers resource allocation related to the initial resource allocation and the Nash bargaining power and other factors; the initial resource allocation is positively related to the maximum contribute ability of the cooperation peers, which reduces when the number of peers increases; the bargaining power decreases when the number of peers increases and resource allocation increases when the bargaining power increases. This resource allocation mechanism was compared with the classical average resource allocation mechanism which also guarantees the fairness, the cooperators can obtain more resources. The simulation results verified that the greater the bargaining power of nodes, the more resources to obtain within the minimum QoS.

To solve the problems of updating, modifying, upgrading and maintaining the function of robot by offline and static method, SoftMan was introduced for robot platform, and the architecture of robot system, whose managing center is host SoftMan, was built. The host SoftMan was mainly researched. Firstly, the architecture of host SoftMan was constructed. Then the descriptive unification model of knowledge and behavior of host SoftMan was put forward, the knowledge model was constructed and implemented based on data structure, and the design specifications and reference realization of the algorithm were given for its main service behaviors. Finally, the robot system was unified with the SoftMan system. Through the test, the function of robot was successfully replaced online and dynamically, verifying the correctness and feasibility of the method of designing and implementing the host SoftMan.

Aiming at the problem that the current display module could not provide a perfect stereo vision on the principle of human visual system, a solution of Virtual Reality (VR) stereo vision was proposed based on the oblique crossing frustum camera. Firstly, by studying the ken model and the theory of accessing to the depth data by eyes, a mathematical model of eyes parallex was built. Secondly, the industrial engine 3DVIA Studio was used as the simulation platform, which relied on the VSL programming language to screen. The relationship of child and parent was set up and the module of visual interaction was designed to construct the stereo camera. Then, the point cloud model was developed to quantize the stereo sense. The advantages and disadvantages of each model were analyzed based on the characteristics of depth display and distortion, and all models were optimized step by step. Center axis parallel normal frustum camera model and normal frustum model whose center axis crossed at the viewing distance were developed, the frustum of camera was optimized to develop a VR camera model of oblique crossing frustum. At last, using 3DVIA Studio as the experiment platform, specific data were substituted on it to do projective transformation. The result shows that the proposed camera model of oblique crossing frustum eliminates the distortion guarantees the depth information display effection, and provides an excellent effect of vision.

In the multimodal biometric system, the parallel fusion mode has more advantages than the serial fusion mode in convenience and efficiency. Based on current works on serial multimodal biometric system, a framework combined with parallel fusion mode and serial fusion mode was proposed. In the framework, the weighted score level fusion algorithm using biological features of gait, face and finger was proposed at first;then semi-supervised learning techniques were used to improve the performance of weak traits in the system, and the simultaneous upgrade of user convenience and recognition accuracy was achieved. Analysis and experimental result indicate that the performance of the weak classifier can be improved by online learning, the convenience and recognition accuracy are successfully promoted in this framework.

To realize 10Gbps level wireless access under the condition of terahertz (THz) carrier frequency, a new Medium Access Control (MAC) protocol for THz ultra-high data-rate wireless networks, MAC-T (Medium Access Control for THz) was proposed in this paper. In MAC-T, a new TDMA (Time Division Multiple Access)+CSMA (Carrier Sense Multiple Access) adaptive hybrid MAC access control mechanism and a new superframe structure were designed. Moreover, some key parameters corresponding to terahertz communications were defined. Therefore, MAC-T could make the maximum data transmission rate reach up to 10Gbps or higher. The theoretical analysis and simulation results show that MAC-T can operate normally in terahertz networks and the data rate can reach up to 18.3Gbps which is 2.16 times 5.78Gbps that IEEE 802.15.3c can achieve. Meanwhile, the average access delay of MAC-T is 0.0044s which improves about 42.1% compared with that of IEEE 802.15.3 which is 0.0076s. Thus, MAC-T can provide significant support in the research and application of terahertz ultra-high data-rate wireless networks.

This paper proposed a fast linear pulse incremental interpolation algorithm. The algorithm can get two forward steps’ pulse increments in three axes every interpolation step, and uses only integer operations. The algorithm improves the efficiency of interpolation and its error is litter than 0.707δ. It is suitable for various CNC systems of machine tools and rapid prototyping machines.