16779458
Systems Biology Platform for Mechanism Clarification of TCM
According to the mechanism clarification problem of Traditional Chinese Medicine (TCM), a systems biology platform was constructed using the related achievements as the basis, Entity Grammar Systems as the framework and database construction, data mining, qualitative reasoning as the kernel techniques. This platform is composed of TCM active components database, TCM prescription database, drug targets database, biological molecular interaction network database, reasoning engine and user interface. After the TCM prescription is selected, the mechanism model can be generated automatically by the platform, which can be used to further study of TCM. This work will contribute to the modernization of Chinese Medicine.
40469721
Modeling, Learning and Simulating Biological Cells with Entity Grammar
In recent years, whole cell modeling approaches, which combine existing knowledge and machine learning results, have received considerable attention. These approaches are potentially very efficient for simulating and analyzing physiological function of cells. In this work, entity grammar system is proposed as formalism for knowledge representation and multistratgy learning techniques in systems biology. Modeling biological cells with entity grammar starts from the simple grammatical models. Integrating the simple models into a cooperating entity grammar of cell facilitates real-time model learning and updating. This makes a difference with many other formalisms to build preset models. The scheme of such a platform is described in the paper and the possible applications are discussed. The proposed formalism method is open to all reasoning paradigm and can be used for studying biological complex systems.
7939166
Evaluation methodology for the security of e-finance systems
E-finance refers to financial systems using the emerging Internet and e-commerce systems. Thanks to the worldwide interest in Web-based e-services, we find Web-services being ushered into financial markets that are sensitive to security concerns. This research was carried out to investigate the effectiveness of emerging security features of Web services in the context of financial markets. In the process we have developed a new evaluation framework (SEFAN) for the security of e-finance systems. This paper presents SEFAN model and its evaluation based on contextual interview of experts.
14027651
Optimizing Model of Blasting Parameters Based on Fuzzy Neural Network
Because of the complexity and polytropism of rock and the complexity of blasting proceeding, it is very difficult to obtain better blasting parameters with a certain way. In order to gain perfect blasting effects expected by designers, blasting engineers have been studying the optimizing of blasting parameters all the time. The intelligent optimizing model of blasting parameters based on fuzzy neural network is set up in this paper. The input parameters of the model are rock properties and blasting requirements, and the outputs are the properties of explosive, blasting parameters, initiation means and charging structure. When a new set of parameters are input into the model trained by some successful examples, a good output will be gotten very easily. At last, the optimizing model is applied to a cement mine. From the application, a conclusion can be drawn that it is feasible and reliable to carry out blasting design with the optimizing model based on fuzzy neural network.
15308955
Avoiding priority inversion on the processing of requests by active replicated servers
We consider the priority inversion problem in an actively replicated system. Priority inversion was originally defined in the context of non-replicated systems. Therefore we first introduce the concept of group priority inversion, which extends the concept of (local) priority inversion to the context of a group of processors that perform an actively replicated processing. We then present the properties of a request scheduling protocol to enforce a total ordering for the processing of requests while avoiding group priority inversions. These properties have been implemented in a protocol that relies on a timed asynchronous system model equipped with a failure detector of the class /spl square/S. The proposed solution allows one to replicate a critical server while ensuring that the processing of all the incoming requests is consistent (mechanisms for solving the atomic broadcast problem) and predictable (mechanisms for solving the group priority inversion problem). Thus, the described request scheduling protocol is a key component which can be used to develop fault tolerant real time applications in a timed asynchronous system.
19552464
Attribute reduction and optimal decision rules acquisition for continuous valued information systems
For continuous valued information systems, the attribute values of objects for the same attribute represent not only their ordinal relationship but also their relative distances. Therefore, the classical rough set model is not suitable for deducing attribute reductions and optimal decision rules for continuous valued information systems. Though some discretization methods are proposed to transform the continuous valued information systems into discrete ones, but those methods are too categorical and may lead to loss of information in some cases. To solve such information loss problem, we propose a tolerance rough set model in this paper. With a given level, the proposed model can divide a universe into some maximal tolerance classes. Also two types of lower and upper approximations are defined accordingly. Then the reductions of the maximal tolerance class and optimal decision rules based on the proposed attribute descriptors are defined, and the approximate discernibility function for the maximal tolerance class is constructed and used to compute all the corresponding optimal decision rules via using Boolean reasoning techniques. Finally, the general reductions and consistent reductions for continuous valued information systems are discussed.
2369938
Human-Currency Interaction: learning from virtual currency use in China
What happens when the domains of HCI design and money intersect? This paper presents analyses from an ethnographic study of virtual currency use in China to discuss implications for game design, and HCI design more broadly. We found that how virtual currency is perceived, obtained, and spent can critically shape gamers' behavior and experience. Virtual and real currencies can interact in complex ways that promote, extend, and/or interfere with the value and character of game worlds. Bringing money into HCI design heightens existing issues of realness, trust, and fairness, and thus presents new challenges and opportunities for user experience innovation.