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Emerging technologies allow the implementation of advanced car features enhancing the safety and the comfort of the driver. These complex functions are distributed among several ECUs, implemented by multiple tasks executed on each processor, and are characterized by non-functional requirements, including timing constraints. The design of the physical architecture and the placement of tasks and messages must be performed in accordance with the constraints and optimizing the performance of the functions. We show how schedulability analysis can be used in the development of complex automotive systems to find the architectures that can best support the target application in a what-if iterative process, and we address the opportunities for the synthesis of architecture configurations. A case study of an experimental vehicle shows the applicability of the approach. [ABSTRACT FROM AUTHOR]

In 1980, the insurance industry in China was revived after twenty years of stagnation when economic system reform and opening up began in China. During the past two decades, the insurance industry has developed from a virtually nonexistent, minimal, and closed industry to a large, open industry with potential promise. The volume of insurance premiums grew rapidly from RMB 0.46 billion in 1980 to RMB 388 billion in 2003,230 ranking China eleventh in the world with 1.6 percent of the global market share (China Insurance Regulatory Commission (CIRC); Swiss Re 2004, p. 35).231 This fast growing economy coupled with the largest population in the world, rising personal income, and economic system reform could not only explain the rapid growth of China's insurance industry, but also foretell the increasing importance of China's insurance market in the future. [ABSTRACT FROM AUTHOR]

As an excellent membrane material, polypropylene microporous membrane (PPMM), has received much consideration in recent years. PPMM has also been used widely in many fields such as water treatment, enzyme immobilization, and blood oxygenation. However, poor surface properties cumber the further applications of this material. Many efforts have been made to solve this problem, and surface modification seems to be the most efficient way. In this article we introduce some work in which surface modification was conducted to reduce nonspecific protein adsorption and to modulate the activity of immobilized enzymes on the PPMM surface. We focus on the studies of our group, although other researches are also discussed. [ABSTRACT FROM AUTHOR]

In spectral datasets, such as those consisting of MR spectral data derived from MS lesions, neighboring features tend to be highly correlated, suggesting the data lie on some low-dimensional space. Naturally, finding such low-dimensional space is of interest. Based on this real-life problem, this paper extracts an abstract problem, neighboring feature clustering (NFC). Noticeably different from traditional clustering schemes where the order of features doesn't matter, NFC requires that a cluster consist of neighboring features, that is features that are adjacent in the original feature ordering. NFC is then reduced to a piece-wise linear approximation problem. We use minimum description length (MDL) method to solve this reduced problem. The algorithm we proposed works well on synthetic datasets. NFC is an abstract problem. With minor changes, it can be applied to other fields where the problem of finding piece-wise neighboring groupings in a set of unlabeled data arises. [ABSTRACT FROM AUTHOR]

Recommender systems are widely used to cope with the problem of information overload and, consequently, many recommendation methods have been developed. However, no one technique is best for all users in all situations. To combat this, we have previously developed a market-based recommender system that allows multiple agents (each representing a different recommendation method or system) to compete with one another to present their best recommendations to the user. In our system, the marketplace encourages good recommendations by rewarding the corresponding agents according to the users' ratings of their suggestions. Moreover, we have shown this incentivises the agents to bid in a manner that ensures only the best recommendations are presented. To do this effectively, however, each agent needs to classify its recommendations into different internal quality levels, learn the users' interests and adapt its bidding behaviour for the various internal quality levels accordingly. To this end, in this paper, we develop a reinforcement learning and Boltzmann exploration strategy that the recommending agents can exploit for these tasks. We then demonstrate that this strategy helps the agents to effectively obtain information about the users' interests which, in turn, speeds up the market convergence and enables the system to rapidly highlight the best recommendations. [ABSTRACT FROM AUTHOR]

Correlations of metallogenic elements and geochronological data from the Emeishan flood basalts indicate that Cu-Ni-PGE. Fe-Ti-V, native Cu-Ag and Pb-Zn-Ag-Ge deposits were related to fractionation processes of different magmas in deep and shallow magma chambers at initial and final stages of eruption. Synvolcanic hydrothermal activities also played an important role in the formation of these deposits. [ABSTRACT FROM AUTHOR]