Gelenbe E.,Intelligent Group
Performance Evaluation Review | Year: 2016
We introduce a model of mutually influencing individuals who hold one of two opinions about some matter. This is similar to a system of particles that can have one of two spin states. The model considers N sub-systems where individuals stay for some time, and then move from one subnetwork to another independently of each other, or they may leave the overall network from any one of the sub-systems. They arrive externally to any sub-system according to independent Poisson processes. In each sub-system individuals can influence each other to align with their own opinion or spin, and their opinion can also fluctuate at random in either opinion. The system also allows for a bias or directional field in any of the sub-systems that influences the individuals or spins that are locally present. We show that even with a weak bias, when random fluctuations become small then all the individuals or spins in a given sub-network will align with probability one, to the opinion or spin direction represented by the bias or spin.
Haddow P.C.,Norwegian University of Science and Technology |
Tyrrell A.M.,Intelligent Group
Genetic Programming and Evolvable Machines | Year: 2011
Nature is phenomenal. The achievements in, for example, evolution are everywhere to be seen: complexity, resilience, inventive solutions and beauty. Evolvable Hardware (EH) is a field of evolutionary computation (EC) that focuses on the embodiment of evolution in a physical media. If EH could achieve even a small step in natural evolution's achievements, it would be a significant step for hardware designers. Before the field of EH began, EC had already shown artificial evolution to be a highly competitive problem solver. EH thus started off as a new and exciting field with much promise. It seemed only a matter of time before researchers would find ways to convert such techniques into hardware problem solvers and further refine the techniques to achieve systems that were competitive with or better than human designs. However, 15 years on\-it appears that problems solved by EH are only of the size and complexity of that achievable in EC 15 years ago and seldom compete with traditional designs. A critical review of the field is presented. Whilst highlighting some of the successes, it also considers why the field is far from reaching these goals. The paper further redefines the field and speculates where the field should go in the next 10 years. © 2011 Springer Science+Business Media, LLC.
Schreuder M.,TU Berlin |
Blankertz B.,TU Berlin |
Blankertz B.,Intelligent Group |
Tangermann M.,TU Berlin
PLoS ONE | Year: 2010
Most P300-based brain-computer interface (BCI) approaches use the visual modality for stimulation. For use with patients suffering from amyotrophic lateral sclerosis (ALS) this might not be the preferable choice because of sight deterioration. Moreover, using a modality different from the visual one minimizes interference with possible visual feedback. Therefore, a multi-class BCI paradigm is proposed that uses spatially distributed, auditory cues. Ten healthy subjects participated in an offline oddball task with the spatial location of the stimuli being a discriminating cue. Experiments were done in free field, with an individual speaker for each location. Different inter-stimulus intervals of 1000 ms, 300 ms and 175 ms were tested. With averaging over multiple repetitions, selection scores went over 90% for most conditions, i.e., in over 90% of the trials the correct location was selected. One subject reached a 100% correct score. Corresponding information transfer rates were high, up to an average score of 17.39 bits/minute for the 175 ms condition (best subject 25.20 bits/minute). When presenting the stimuli through a single speaker, thus effectively canceling the spatial properties of the cue, selection scores went down below 70% for most subjects. We conclude that the proposed spatial auditory paradigm is successful for healthy subjects and shows promising results that may lead to a fast BCI that solely relies on the auditory sense. © 2010 Schreuder et al.
Nolte G.,Intelligent Group |
Muller K.-R.,TU Berlin
Frontiers in Human Neuroscience | Year: 2010
Estimating brain connectivity and especially causality between different brain regions from EEG or MEG is limited by the fact that the data are a largely unknown superposition of the actual brain activities. Any method, which is not robust to mixing artifacts, is prone to yield false positive results. We here review a number of methods that allow for addressing this problem. They are all based on the insight that the imaginary part of the cross-spectra cannot be explained as a mixing artifact. First, a joined decomposition of these imaginary parts into pairwise activities separates subsystems containing different rhythmic activities. Second, assuming that the respective source estimates are least overlapping, yields a separation of the rhythmic interacting subsystem into the source topographies themselves. Finally, a causal relation between these sources can be estimated using the newly proposed measure Phase Slope Index (PSI). This work, for the first time, presents the above methods in combination; all illustrated using a single, simulated data set. © 2010 Nolte and Mueller.
Katuri J.,Sri Sathya Sai Institute of Higher Learning |
Katuri J.,Intelligent Group
Angewandte Chemie - International Edition | Year: 2015
Chemically powered micro- and nanomotors are small devices that are self-propelled by catalytic reactions in fluids. Taking inspiration from biomotors, scientists are aiming to find the best architecture for self-propulsion, understand the mechanisms of motion, and develop accurate control over the motion. Remotely guided nanomotors can transport cargo to desired targets, drill into biomaterials, sense their environment, mix or pump fluids, and clean polluted water. This Review summarizes the major advances in the growing field of catalytic nanomotors, which started ten years ago. © 2015 Wiley-VCH Verlag GmbH & Co. KGaA, Weinheim.
Srivastava A.N.,Intelligent Group
Data Mining and Knowledge Discovery | Year: 2012
The environmental impact of aviation is enormous given the fact that in the US alone there are nearly 6 million flights per year of commercial aircraft. This situation has driven numerous policy and procedural measures to help develop environmentally friendly technologies which are safe and affordable and reduce the environmental impact of aviation. However, many of these technologies require significant initial investment in newer aircraft fleets and modifications to existing regulations which are both long and costly enterprises. We propose to use an anomaly detection method based on Virtual Sensors to help detect overconsumption of fuel in aircraft which relies only on the data recorded during flight of most existing commercial aircraft, thus significantly reducing the cost and complexity of implementing this method. The Virtual Sensors developed here are ensemble-learning regression models for detecting the overconsumption of fuel based on instantaneous measurements of the aircraft state. This approach requires no additional information about standard operating procedures or other encoded domain knowledge. We present experimental results on three data sets and compare five different Virtual Sensors algorithms. The first two data sets are publicly available and consist of a simulated data set from a flight simulator and a real-world turbine disk. We show the ability to detect anomalies with high accuracy on these data sets. These sets contain seeded faults, meaning that they have been deliberately injected into the system. The second data set is from real-world fleet of 84 jet aircraft where we show the ability to detect fuel overconsumption which can have a significant environmental and economic impact. To the best of our knowledge, this is the first study of its kind in the aviation domain. © 2011 The Author(s).
Martin R.A.,Intelligent Group
IEEE Transactions on Information Theory | Year: 2010
In this paper, approximations of an optimal level-crossing predictor for a zero-mean stationary linear dynamical system driven by Gaussian noise in state-space form are investigated. The study of this problem is motivated by the practical implications for design of an optimal alarm system, which will elicit the fewest false alarms for a fixed detection probability in this context. This work introduces the use of Kalman filtering in tandem with the optimal level-crossing prediction problem. It is shown that there is a negligible loss in overall accuracy when using approximations to the theoretically optimal predictor, at the advantage of greatly reduced computational complexity. © 2010 IEEE.
Komarov S.,Intelligent Group |
Reinecke K.,Intelligent Group |
Gajos K.Z.,Intelligent Group
Conference on Human Factors in Computing Systems - Proceedings | Year: 2013
Online labor markets, such as Amazon's Mechanical Turk (MTurk), provide an attractive platform for conducting human subjects experiments because the relative ease of recruitment, low cost, and a diverse pool of potential participants enable larger-scale experimentation and faster experimental revision cycle compared to lab-based settings. However, because the experimenter gives up the direct control over the participants' environments and behavior, concerns about the quality of the data collected in online settings are pervasive. In this paper, we investigate the feasibility of conducting online performance evaluations of user interfaces with anonymous, unsupervised, paid participants recruited via MTurk. We implemented three performance experiments to re-evaluate three previously well-studied user interface designs. We conducted each experiment both in lab and online with participants recruited via MTurk. The analysis of our results did not yield any evidence of significant or substantial differences in the data collected in the two settings: All statistically significant differences detected in lab were also present on MTurk and the effect sizes were similar. In addition, there were no significant differences between the two settings in the raw task completion times, error rates, consistency, or the rates of utilization of the novel interaction mechanisms introduced in the experiments. These results suggest that MTurk may be a productive setting for conducting performance evaluations of user interfaces providing a complementary approach to existing methodologies. Copyright © 2013 ACM.
Intelligent Group | Date: 2016-01-13
A trolley and storage unit system comprises a trolley and at least one storage unit mountable on said trolley. The storage unit is selectively arrangable in either a non-tilted position or in a tilted position. One of said trolley and said storage unit comprises a first contact portion and a second contact portion. The other one of said trolley and said storage unit comprises a third contact portion. When the first contact portion is in contact with the third contact portion, the storage unit is in its non-tilted position. When the second contact portion is in contact with the third contact portion, the storage unit is in its tilted position.