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.     

田湾核电站扩建工程取水明渠导流堤优化设计

取水工程为核电厂重要构筑物,按照较高的核电标准设计往往断面较大,在保证取水安全的前提下,分析不同工程的使用要求,有针对性的的进行优化设计,可降低工程造价。以田湾核电取水工程为例,分析优化设计过程,供类似工程参考。     

海底埋设管线平管起吊运动分析

基于有限元软件OrcaFlex,充分考虑不规则波浪、海流、管土相互作用以及船舶管线耦合运动,建立海底埋设管线平管起吊模型。参考DNV-RP-F110计算埋深管道受到的土壤阻力,依据DNV-RP-C205确定相关水动力系数。通过数值模拟研究分析管线在平管起吊过程中管道的运动响应以及吊绳张力的时间历程变化,为实际海底管线平管起吊提供一定理论参考。     

Prediction of Scour Depth around Offshore Pipelines in the South China Sea

Scour depth prediction of offshore pipelines is of great significance to the design and construction of the submarine pipeline projects. In this paper, based on the CFD software package FLUENT and User...     

基于直流漏泄电流的无铠装电缆绝缘性能检测方法

电缆绝缘性能的好坏对供电系统连续运行具有重要意义。采用直流漏泄电流方法,提出一种无铠装电缆的绝缘性能检测方法。该方法把电缆两端电流的同步测量,转换成电缆输出端开路时输入端电流的准确测量,简化了测量的复杂性,提高了直流漏泄电流的测量精度,改善了电缆绝缘性能的诊断准确度。该法用于地铁牵引变电站直流馈线电缆绝缘性能检测中,取得了良好的效果。