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This study focuses on the thermo-mechanical properties of mortar in the retrofitting cover of additional reinforcement for existing concrete structures. In addition, the residual mechanical properties of high strength mortar incorporating polypropylene fibers subjected to the effect of fiber length and the elevated temperature were investigated. Several experiments were conducted to determine the optimum mixture proportions of high strength mortar incorporating polypropylene fibers which had a slump-flow of 25–30 cm, compressive strength of 50 MPa or higher, and flexural strength of 4–8 MPa. Subsequently, an experiment was conducted by using high-strength mortar-blended polypropylene fibers with a length of 2 cm, and the ratio of fiber length to the diameter of cylinder mortar-specimens was 0.4. The experimental parameters were the weight volume of fibers (0 %, 0.5 %, 1 %, and 2%) and the heating temperature (100, 200 and 300 °C). The effect of the mixing parameters, including polypropylene length on compressive strength, slump-flow and the flexural strength of mortar were discussed. It is evident that fiber in the mortar cover influenced the initial and residual mechanical properties, such as elasticity, compressive strength, and Poisson’s ratio, of the mortar.

Image segmentation is a key link of vision system of the global vision bionic robot fish, and a precondition of target localization and tracking. In this paper, we propose a visual threshold method for color image segmentation. Firstly, a visualization research on the R, G and B components in different regions of the image is carried out to find out the main factors, which influence the image segmentation effect, and then an image segmentation method is proposed based on R and B components. It is proved by experiments that the image segmentation method is simple and practical, which is more suitable for the image segmentation and target tracking in our test-bed than the Gaussian mixture model. The image segmentation method also provides reference for other fields.

Based on AMESim simulation platform, the pressure-time curve of constant deceleration braking system is obtained in this paper firstly, by simulating three typical faults of brake, the spring stiffness decrease, the brake shoe friction coefficient decrease and brake leaking. Then pressure data on the curve for each time are seen as a variable and the curve is chosen as the fault sample, analysed by the method of Principal Component Analysis (PCA). Last, principal components or sum of variance contribution rates more than 95% are selected as sample eigenvalues and Support Vector Machine (SVM) is used for fault diagnosis. Diagnosis results show that all testing faults can be identified accurately, which indicates SVM model has an extremely excellent ability to identify faults. To further verify the performance of SVM for fault identification, BP neural network is established to compare. The result shows that SVM model is more accurate than BP neural network in fault recognition.

With college enrollment, the number of students continues to soar, significantly increasing the difficulty of teaching management. In the highly developed network of information technology today, how to achieve through modern information technology and efficient integration of network information resources, in order to achieve continuous improvement of the level of education, teaching and simplify management and reduce the human and financial investment, the university has become common Follow hot topic. Based on this, on a systematic and structural design of the .NET technology teaching management system based on a research point, the system through ADO.NET technology to access educational information and database retrieval, XML technology to achieve rights management, Finally, this system functions realization more thorough discussion. This system is used for the teaching management mode of German dual system localization, has a good effect