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The classification of streaming data requires learning in an environment where the distribution of the incoming data might change continuously. Stream classification methodologies need to adapt to these changes under limitations of time and memory resources. As such, it is not possible to expect all the samples in the stream to be labeled, as labeling is often time consuming and expensive. In this...
Outlier detection is an important task in data mining. It is mainly used for finding strange mechanism or potential danger. This paper presents an outlier detection algorithm based on k-neighborhood minimum spanning tree(MST). This algorithm is applicable to data sets of any arbitrary shape and density and can effectively detect local outliers and local outlying clusters. Taking density and directional...
Background: Perhaps the most common of all software engineering activities is the modernization of software. Unfortunately, during such modernization often leaves behind artifacts that are difficult to understand for those other than its author. Thus, the Object Management Group (OMG) has defined standards in the modernization process, by creating the concept of Architecture-Driven Modernization (ADM)...
In Wireless Sensor Network (WSN), Clustering sensor nodes is an efficient topology control method to reduce energy consumption of the sensor nodes. Many link quality-based clustering techniques have been proposed in the literature. However, they assumed that each sensor node is equipped with a self-locating hardware such as GPS. Though this is a simple solution, the resulting cost renders that solution...
This paper deals with time Petri nets while assuming multiple-server semantics. The latter has been proved to be more expressive than standard semantics (single-server). However, the state space of the model is more complex to compute in this case as it involves to consider many instances of a same enabled transition. This results in a high cost in terms of computation and memory usage. Within this...
We propose and experiment a practical multi-level approach to maintain contradiction-free knowledge when some incoming additional information that can contradict the preexisting knowledge must be taken into account. The approach implements an any-time strategy that triggers successive reasoning paradigms ranging from credulous to computationally more intensive forms of skepticism about conflicting...
As a complex artefact, software has to meet requirements formulated and verified at different levels of abstraction. A basic distinction is drawn between behavioural (dynamic) and data (static) aspects. From an educational point of view, although disguised under a number of different designations, both issues are usually present, but kept separated, in typical Computer Science undergraduate curricula...
In this paper, we are interested in formalization, analysis and checking of the BPEL language at the semantic level. We propose translating rules from BPEL language to a low-level real-time model (DATA). This model is based on true-concurrency semantics and supports at the same time timing constraints and actions durations. This transformation approach gives a formal semantics to the BPEL language...
A primary objective of enterprise computing (via a data center, cloud, etc.) is the controlled delivery of data services (DS). Typical DSs include applications such as email, workflow, and records management, as well as system level features, such as file and access control management. Although access control (AC) currently plays an important role in imposing control over the execution of DS capabilities,...
In this paper we address the safety analysis of chemical plants controlled by programmable logic controllers (PLCs). We consider sequential function charts (SFCs)for the programming of the PLCs, extended with the specification of the dynamic plant behavior. The resulting hybrid SFC models can be transformed to hybrid automata, opening the way to the application of advanced techniques for their reachability...
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