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BPM software is playing more and more important role in the enterprise management, and the trust evaluation of Business Processes Management software is becoming a hot research topic. Based on inductive analysis of business processes software used in various fields, this paper has made a trust definition and has built an evaluation index system that confirms the importance of the indicators by the...
Current hardware implementations of TLS (thread-level speculation) in both Hydra and Renau's SESC simulator use a global component to check data dependence violations, e.g. L2 Cache or hardware list. Frequent memory accesses cause global component bottlenecks. Implementation and verification of the global component dramatically slows the processor's frequency. In this paper, we propose a cache coherence...
A new algorithm for human motion Recognition based on Conditional Random Fields (CRFs) and Hidden Markov Models (HMM) -- HMCRF is proposed. Most existing approaches to human motion recognition with hidden states employ a Hidden Markov Model or suitable variant to model motion streams; a significant limitation of these models is the requirement of conditional independence of observations. In contrast,...
SVM may have great difficulty in its realization, even can not work properly because of the tremendous increase of compute time and memory for large-scale training set. A new fast learning algorithm for large-scale SVM is proposed under the condition of sample aliasing. The aliasing sample points which are not the same class are eliminated first and then the relative boundary vectors (RBVs) are computed...
With the wide application of software, the scale of software systems is constantly expanding, and their structures and behaviors become more and more complicated. Therefore, people have more request and wish for their correctness, availability, reliability, safety, etc. This thesis presents a runtime verification framework, with a focus on software behavior. The theory of DFA is adopted to check whether...
Most existing process mining methods were designed for ignoring time variability from real business process data, thus it could be hard to implement adaptive process mining. To deal with this problem, a new method of adaptive process mining was proposed in order to mine unremittingly process models of gradual change which represents the improvement stages of business processes and improve accuracy...
In the evaluation of self-organized algorithm for web service providers, we need a great deal of web service information. And these services should be of natural similar properties by which they will be grouped into several alliances. In this paper, we propose an auto-generating method for web service contents based on artificial immune system. First of all, a semantic tree is designed to define the...
With the development of the distributed artificial intelligence system, multi-agent system (MAS) has been applied in construction of large-scale fault diagnosis systems. Procedure of construction of the knowledge base about fault diagnosis in conventional knowledge models cannot satisfy demands of a synchronism and concurrency of the system. To solve problems mentioned above, a new WFPN model and...
In order to further ease the disaster of computing costs in multi-objective optimization problem, we've put forward a kind of multi-objective genetic algorithm based on clustering. The algorithm uses the fuzzy c-means clustering control the similar individuals gathered in a class and for each class construct non-dominated set with arena's principle, so that we can use faster speed to choose the non-dominated...
Apriori algorithm was widely applied in association rule mining. Generally, we have to specify different ranges manually to discretize numeral fields to nominal fields, which may weaken the result due to unfit partitions. This paper introduced an approach to make discretized partitions in a self adaptive way to enhance the numeral quantitative association rule mining result.
Rough set theory is an effective mathematical tool for dealing with inconsistencies in information systems. Dominance based rough set (DBRS) is an extension to the original rough set, in which the equivalence relation is replaced by a dominance relation. However, in some condition, the lower approximation of DBRS can be emptied by only one "malicious" object. The variable consistency dominance...
Because of the larger difference between the two images to be registered, such as exposure degree or noise pollution, the common registration algorithm that based on mutual information of original gray, is easy to fall into local extreme value, thus the registration accuracy is unsatisfactory. In this case, a new method of image registration algorithm that based on mutual information of gradient and...
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