Artificial Immune System (AIS) models hold many promises in the field of unsupervised learning. However, existing models are not scalable, which makes them of limited use in data mining. We propose a new AIS based clustering approach (TECNO-STREAMS) that addresses the weaknesses of current AIS models. Compared to existing AIS based techniques, our approach exhibits superior learning abilities, ...

For many application areas, where a task is most naturally represented by talking or where standard input devices are difficult to use or not available at all, virtual characters can be well suited as an intuitive man-machineinterface due to their inherent ability to simulate verbal as well as nonverbal communicative behavior. This type of interface is made possible with the help of multimodal ...

The biodegradation, photolysis, and adsorption of pentachlorophenol (PCP) in outdoor, aquatic environments were examined with man-made channels built by the U.S. Environmental Protection Agency at a field station on the Mississippi River near Monticello, Minn. Four channels were used, each channel being approximately 520 m long and receiving river water that flowed through the channels for abou...

Facial Recognition remains one of the most popular fields in computer imaging research due to its broad scope of applications in identity verification, human computer interactions, law enforcement applications and video surveillance systems. Although numerous artificial intelligence and machine learning techniques have been successfully applied to still image recognitions, recognition in video ...

Dataflow matrix machines are self-referential generalized recurrent neural nets. The self-referential mechanism is provided via a stream of matrices defining the connectivity and weights of the network in question. A natural question is: what should play the role of untyped lambda-calculus for this programming architecture? The proposed answer is a discipline of programming with only one kind o...

Data streams are ubiquitous. Examples range from sensor networks to financial transactions and website logs. In fact, even market basket data can be seen as a stream of sales. Detecting changes in the distribution a stream is sampled from is one of the most challenging problems in stream mining, as only limited storage can be used. In this paper we analyse this problem for streams of transactio...