Occupant injury risk analysis at NASS/CDS database

Injury information for vehicle occupants from the body regions of the head, thorax, abdomen, and upper and lower extremities, due to the restraints and interior parts of the vehicle, were extracted from the 2009 ~ 2012 NASS/CDS database. For those cases with high occurrence frequency, a detailed and comprehensive data analysis was performed to find the relationship between the accident, occupant, vehicle, and injury data. A numerical frontal impact sled model with the Hybrid III dummy and the GHBMC human body model was constructed to simulate and identify those injury risks according to NASS/CDS. Among the 5,734 injuries to the aforementioned body regions from frontal crashes are, listed by frequency of occurrence, the lower extremity (27.8 %), upper extremity (21.3 %), thorax (15.1 %), face (10.9 %), spine (8.7 %), head (7.3 %), and abdomen (6.9 %). The main injury sources to the head were the windshield, side structure, and steering wheel. For the thorax and abdomen they were the seat belt and steering wheel. For the lower extremity it was the instrument panel. The main injury patterns for the head were the concussion and the contusion. For the thorax they were vessel laceration and lung contusion. For the abdomen they were laceration and contusion of the organs. For the lower extremity they were bone fracture and ligament rupture. The steering wheel and seat positions were main factors affecting head and thorax injury risks. From the sled impact simulation, high injury risks of the head and thorax were assessed respectively at conditions of steering column tilt down and rear most seat position, which correlated well with the findings from the NASS/CDS data analysis.     

Integrated approach to an optimal automotive timing chain system design

Ensuring engine efficiency is a crucial issue for automotive manufacturers. Several manufacturers focus on reducing the time taken to develop and introduce brand new vehicles to the market. Thus, a synergic approach including various simulations is generally adopted to achieve a development schedule and to reduce the cost of physical tests. This study involved proposing a design process that is very useful in the preliminary development stage through effective support from simulations. This type of simulation-based design process is effective in developing timing chain drives; the use of this process, based on results from multiple trials, showed improvements in performance including low friction and vibration, improved durability, and cost-effective part design when compared to conventional processes. This study proposes an integrated approach to the preliminary design of an automotive timing chain system. The approach involves structural and dynamic analyses. The details of the design process are described by using the case of a virtual engine. This study conducted and summarized a dynamic and structural analysis as well as topological optimization to describe a process to obtain optimal results. The results of this study indicated the following improvements in overall performance factors: 12.1 % improvement in transmission error, 10.1 % reduction in chain tension, 46 % reduction in tensioner arm weight, and 11 % reduction in transversal displacement.     

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.     

昆明市“月月无车日活动”及公众调查分析

调查了解公众对无车日活动常态化这一公共政策的反应,能够为城市交通政策的制定提供一定的技术参考。介绍了昆明市城市交通概况及首个无车日活动成效,同时,对“月月无车日活动”做了概述,在总结前几次活动经验的基础上,给出了活动的进一步调整方案。通过对无车日活动公众调查问卷的数据分析,得出大多数公众对“月月无车日活动”的态度是理解和支持的;在无车日当天,私人小汽车拥有者选择公共交通作为替代小汽车出行方式的比例最高。另外,大力发展公共交通也被受访者认为是解决城市交通拥堵应当首选的措施。     

行人微观仿真中的运动模型与行为模型——STEPS与NOMAD模型对比

为了解各类行人仿真模型的性能差异和适用范围,以选取适当模型进行交通枢纽行人仿真,对两种典型行人仿真模型进行研究。依据模型对行人行为描述的复杂程度,将行人仿真模型分为运动模型、部分行为模型、行为模型3类,并分别介绍了各自的特点。选取典型的运动模型软件STEPS和行为模型软件NOMAD,详细探讨其采用的数学模型,并通过4个仿真实例对比分析这两种模型的特点。分析结果得出两种模型在宏观与微观层面的异同点以及存在的问题。     

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.