Approximate optimal AUTOSAR software components deploying approach for automotive E/E system

The AUTOSAR has been developed as the worldwide standard for automotive E/E software systems, making the electronic components of different suppliers to be employed universally. However, as the number of component-based applications in modern automotive embedded systems grows rapidly and the hardware topology becomes increasingly complex, deploying such large number of components in automotive distributed system in manual way is over-dependent on experience of engineers which in turn is time consuming. Furthermore, the resource limitation and scheduling analysis make the problems more complex for developers to find out an approximate optimal deploying approach in system integration. In this paper, we propose a novel method to deploy the AUTOSAR components onto ECUs with the following features. First, a clustering algorithm is designed for deploying components automatically within relatively low time complexity. Second, a fitness function is designed to balance the ECUs load. The goal of our approach is to minimize the communication cost over all the runnable entities while meeting all corresponding timing constraints and balancing all the ECUs load. The experiment results show that our approach is efficient and has well performance by comparing with other existing methods in specific and synthetic data set.     

Modeling research on manufacturing execution system based on large-scale system cybernetics

A cybernetics model of manufacturing execution system(MES CM) was proposed and studied from the viewpoint of cybernetics.Combining with the features of manufacturing system, the MES CM was modeled by"generalized modeling"method that is discussed in large-scale system theory.The mathematical model of MES CM was constructed by the generalized operator model, and the main characteristics of MES CM were analyzed.     

A data model applied to the knowledge-based ICAS

Image-guided computer aided surgery system (ICAS) contributes to safeness and success of surgery operations by means of displaying anatomical structures and showing correlative information to surgeons in the process of operation. Based on analysis of requirements for ICAS, a new concept of clinical knowledge-based ICAS was proposed. Designing a reasonable data structure model is essential for realizing this new concept. The traditional data structure is limited in expressing and reusing the clinical knowledge such as locating an anatomical object, topological relations of anatomical objects and correlative clinical attributes. A data structure model called mixed adjacency lists by octree-path-chain (MALOC) was outlined, which can combine patient's images with clinical knowledge, as well as efficiently locate the instrument and search the objects' information. The efficiency of data structures was analyzed and experimental results were given in comparison to other traditional data structures. The result of the nasal surgery experiment proves that MALOC is a proper model for clinical knowledge-based ICAS that has advantages in not only locating the operative instrument precisely but also proving surgeons with real-time operation-correlative information. It is shown that the clinical knowledge-based ICAS with MALOC model has advantages in terms of safety and success of surgical operations, and help in accurately locating the operative instrument and providing operation-correlative knowledge and information to surgeons in the process of operations.     

Analysis and improvement of authenticatable ring signcryption scheme

We show that the Zhang-Yang-Zhu-Zhang identity-based authenticatable ring signcryption scheme is not secure against chosen plaintext attacks.Furthermore, we propose an improved scheme that remedies the weakness of the Zhang-Yang-Zhu-Zhang scheme.The improved scheme has shorter ciphertext size than the Zhang-Yang-Zhu-Zhang scheme.We then prove that the improved scheme satisfies confidentiality, unforgeability, anonymity and authenticatability.     

Power network parameter estimation method based on data mining technology

The parameter values which actually change with the circumstances, weather and load level etc.produce great effect to the result of state estimation. A new parameter estimation method based on data mining technology was proposed. The clustering method was used to classify the historical data in supervisory control and data acquisition (SCADA) database as several types. The data processing technology was impliedto treat the isolated point, missing data and yawp data in samples for classified groups. The measurement data which belong to each classification were introduced to the linear regression equation in order to gain the regression coefficient and actual parameters by the least square method. A practical system demonstrates the high correctness, reliability and strong practicability of the proposed method.     

Virtual prototype simulation on underwater hydraulic impingement shovel

The virtual prototype technology is applied to the design of the hydraulic impingement shovel, which is to increase the reliability of the design. The work principle of hydraulic impingement shovel is expatiated, and its dynamic equations are established. The 3D model of virtual prototype is built by PRO/E. Then the couple between the mechanical body of prototype and the hydraulic system is completed by virtue of ADAMS. Finally, the simulation is made on the virtual prototype. The simulation results show that the design of underwater hydraulic impingement shovel is rational. The virtual prototype technology could lay sound foundation of successful manufacturing of physical prototype for the first time and offer highly effective and feasible means for the design and production of underwater equipments.     

Experimental study on the width of the turbulent area around bridge pier

At present, the method of calculating the turbulent flow width around the bridge pier is not given in the "Standard for Inland River Navigation" (GB50139-2004) in China, and the bridge designer usually increases the bridge span in order to ensure the navigation safety, which increases both of the structural design difficulty and the project investments. Therefore, it is extremely essential to give a research on the turbulent flow width around the bridge pier. Through the experiments of the fixed bed and the mobile bed, the factors influencing the turbulent flow width around the bridge pier have been analyzed, such as the approaching flow speed, the water depth, the angles between the bridge pier and the flow direction, the sizes of bridge pier, the shapes of the bridge pier, and the scouring around the bridge pier, etc. Through applying the dimension analytic method to the measured data, the formula of calculating the turbulent flow width around the bridge pier is then inferred.     

Using a SVM to evaluate damage to vibration isolators in an elastic raft system

Predicting damage to vibration isolators in a raft experiencing heavy shock loadings from explosions is an important task when designing a raft system. It is also vital to be able to research the vulnerability of heavily shocked floating rafts unreliable, especially when the allowable values The conventional approach to prediction has been or ultimate values of vibration isolators of supposedly uniform standard in a raft actually have differing and uncertain values due to defective workmanship. A new model for predicting damage to vibration isolators in a shocked floating raft system is presented in this paper. It is based on a support vector machine（SVM）, which uses Artificial Intelligence to characterize complicated nonlinear mapping between the impacting environment and damage to the vibration isolators. The effectiveness of the new method for predicting damage was illustrated by numerical simulations, and shown to be effective when relevant parameters of the model were chosen reasonably. The effect determining parameters, including kernel function and penalty factors, has on prediction results is also discussed. It can be concluded that the SVM will probably become a valid tool to study damage or vulnerability in a shocked raft system.     

A second order volume of fluid （VOF） scheme for numerical simulation of 2-D breaking waves

Among all environmental forces acting on ocean structures and marine vessels, those resulting from wave impacts are likely to yield the highest loads. Being highly nonlinear, transient and complex, a theoretical analysis of their impact would be impossible without numerical simulations. In this paper, a pressure-split two-stage numerical algorithm is proposed based on Volume Of Fluid (VOF) methodology. The algorithm is characterized by introduction of two pressures at each half and full cycle time step, and thus it is a second-order accurate algorithm in time. A simplified second-order Godunov-type solver is used for the continuity equations. The method is applied to simulation of breaking waves in a 2-D water tank, and a qualitative comparison with experimental photo observations is made. Quite consistent results are observed between simulations and experiments. Commercially available software and Boundary Integral Method (BIM) have also been used to simulate the same problem. The results from present code and BIM are in good agreement with respect to breaking location and timing, while the results obtained from the commercial software which is only first-order accurate in time has clearly showed a temporal and spatial lag, verifying the need to use a higher order numerical scheme.