This paper focuses on the dynamic re-configuration and task optimization of holonic manufacturing systems (HMS). The concept of dynamic virtual clustering is extended to the control process of a holarchy or holonic organization. A task-oriented clustering mechanism and a corresponding optimization algorithm are presented as an efficient approach to the holonic control in the HMS domain. The med...

Dynamic systems are often best characterized by a combination of static and temporal features, with the static features describing time-invariant properties of the system, and the temporal features capturing dynamic aspects of the system. Our goal is to construct context based temporal behavior models of dynamic systems using information from both types of features. Our dynamic system profiling...

The purpose of this study is to explore an alternative means of hand image classification, one that requires minimal human intervention. The main tool for accomplishing this is a Genetic Algorithm (GA). This study is more than just another GA application; it introduces (a) a novel cooperative coevolutionary clustering algorithm with dynamic clustering and feature selection; (b) an extended fitn...

Graph clustering (or community detection) has long drawn enormous aŠention from the research on web mining and information networks. Recent literature on this topic has reached a consensus that node contents and link structures should be integrated for reliable graph clustering, especially in an unsupervised setting. However, existing methods based on shallow models o‰en su‚er from content nois...

The paper proposes an energy-aware dynamic clustering-based scheduling algorithm that aims at reducing communication energy consumption through clustering dependent tasks. A job can be described by a direct acyclic graph (DAG) of parallel tasks. Because the execution time is hard to estimate accurately, the current static scheduling strategies may cause energy increase due to task waiting. The ...

This paper explores the effect that changing access patterns has on the performance of database management systems. Changes in access patterns play an important role in determining the efficiency of key performance optimization techniques, such as dynamic clustering, prefetching, and buffer replacement. However, all existing benchmarks or evaluation frameworks produce static access patterns in ...

The use of 3D data in the form of triangle meshes is nowadays a widespread phenomenon. A great many examples of using this kind of data can be found in engineering applications or in film and gaming industry. These examples include not only static, but also dynamic meshes – 3D animations. This kind of data representation is usually voluminous and needs to be compressed for efficient storage and...

Most classification methods are based on the assumption that data conforms to a stationary distribution. The machine learning domain currently suffers from a lack of classification techniques that are able to detect the occurrence of a change in the underlying data distribution. Ignoring possible changes in the underlying concept, also known as concept drift, may degrade the performance of the ...

Clustering algorithms typically assume that the available data constitute a random sample from a stationary distribution. As data accumulate over time the underlying process that generates them can change. Thus, the development of algorithms that can extract clustering rules in non-stationary environments is necessary. In this paper, we present an extension of the k-windows algorithm that can t...

It is well accepted that genes are simultaneously involved in multiple biological processes and that genes are coordinated over the duration of such events. Unfortunately, clustering methodologies that group genes for the purpose of novel gene discovery fail to acknowledge the dynamic nature of biological processes and provide static clusters, even when the expression of genes is assessed acros...