The use of macroinvertebrates as indicators water quality is an effective and low-cost tool, which widely implemented in biomonitoring programmes. Certain taxa are characteristic impaired watercourses (e.g. Oligochaeta, Chironomidae Amphipoda), while others good-quality Ephemeroptera, Plecoptera Trichoptera; EPT). In this work, we evaluated the response macroinvertebrate assemblages to differen...

We propose novel gaze control algorithms for active perception in mobile autonomous agents with directable, foveated vision sensors. Our agents are realistic artificial animals, or animats, situated in physics-based virtual worlds. Their active perception systems continuously analyze photorealistic retinal image streams to glean information useful for controlling the animat’s eyes and body. The...

The “Flume Room” The University of Michigan has created a specialized laboratory containing 150 artificial mini-streams, or “flumes,” that mimic a variety of river conditions as closely as possible. The flumes are populated with rocks, sediment, biota, and more than 3,000 gallons of water from the Huron River. The goal is to better understand how different stressors—nutrient and chemical pollut...

We propose novel gaze control algorithms for active perception in mobile autonomous agents with directable, foveated vision sensors. Our agents are realistic artificial animals, or animats, situated in physics-based virtual worlds. Their active perception systems continuously analyze photorealistic retinal image streams to glean information useful for controlling the animat ’ s eyes and body. T...

This tutorial paper presents an annotated overview of existing hardware implementations of Artificial Neural Systems based on “Pulse Stream” modulations. Pulse Streams are quasi-periodic binary waveforms which convey analog information on waveform timing. The theoretical bases of Pulse Stream computation are shown for the major techniques, and basic circuits are briefly described for most Neura...

In competitive consumer markets, data mining for customer relationship management faces the challenge of systematic knowledge discovery in large data streams to achieve operational, tactical and strategic competitive advantages. Methods from computational intelligence, most prominently artificial neural networks and support vector machines, compete with established statistical methods in the do...

We present an approach to learning to recognize concurrent activities based on multiple data streams. One example is recognition of concurrent activities in hospital operating rooms based on multiple wearable and embedded sensors. This problem differs from standard time series classification in that there is no natural single target dimension, as multiple activities are performed at the same ti...

Smog disaster is a severe global problem. Although it has been investigated for decades in environmental sciences, the analysis of smog data recently becomes an open problem in fields like big data and artificial intelligence. In this paper, we present our study of utilizing semantic reasoning techniques for accurate and explanatory smog disaster prediction. To this end, we enriched the smog da...