FPGA-based Anomalous trajectory detection using SOFM

A system for automatically classifying the trajectory of a moving object in a scene as usual or suspicious is presented. The system uses an unsupervised neural network (Self Organising Feature Map) fully implemented on a reconfigurable hardware architecture (Field Programmable Gate Array) to cluster trajectories acquired over a period, in order to detect novel ones. First order motion information, including first order moving average smoothing, is generated from the 2D image coordinates (trajectories). The classification is dynamic and achieved in real-time. The dynamic classifier is achieved using a SOFM and a probabilistic model. Experimental results show less than 15\% classification error, showing the robustness of our approach over others in literature and the speed-up over the use of conventional microprocessor as compared to the use of an off-the-shelf FPGA prototyping board

Techniques for clustering gene expression data

Many clustering techniques have been proposed for the analysis of gene expression data obtained from microarray experiments. However, choice of suitable method(s) for a given experimental dataset is not straightforward. Common approaches do not translate well and fail to take account of the data profile. This review paper surveys state of the art applications which recognises these limitations and implements procedures to overcome them. It provides a framework for the evaluation of clustering in gene expression analyses. The nature of microarray data is discussed briefly. Selected examples are presented for the clustering methods considered

Organising Therapists’ Emotional-Social Skills: Are Therapists that Different? : A thesis in partial fulfilment of the requirements for the degree of Doctor of Clinical Psychology at Massey University, Palmerston North New Zealand

Wampold and Imel (2015) argue that therapeutic outcomes may be more dependent on variables associated with therapists than treatment systems. An element of these therapist variables include the emotional and social skills of therapists, however, to date, little has been done to investigate the relationships between these therapy factors. One exception to this is pilot research conducted by my supervisors, their students, and myself (Harvey, Marwick, Baken, Bimler, & Dickson, 2016). This thesis aims to replicate and extend on this pilot research as to better understand therapists’ emotional and social skills in practice. Using three complementary approaches including thematic analysis of therapist transcripts, a date-specific literature review, and revision of foundational research, Harvey et al.’s original pool of emotional and social skills was revised and extended. Subsequently, using a statistical method for mapping psychological constructs, therapists’ emotional practices were transformed into a ‘map’ with three spatial dimensions, which was generally supported by comparative reliability checks including a validation study with a foreign-language sample. Finally, the nature of emotional practice was further investigated by administering a questionnaire of emotional practice items to 79 therapists. From this, eight salient practice constructs were identified. Statistical links were also found between these and both demographic data and a modified measure of the therapeutic relationship. Furthermore, using Q-analysis, a general consensus of responding was found between therapists’ emotional response patterns and as a result, a tentative pathway to therapists’ practice styles was developed. From these findings important research and clinical applications are apparent

Self-Referential Noise and the Synthesis of Three-Dimensional Space

Generalising results from Godel and Chaitin in mathematics suggests that self-referential systems contain intrinsic randomness. We argue that this is relevant to modelling the universe and show how three-dimensional space may arise from a non-geometric order-disorder model driven by self-referential noise.Comment: Figure labels correcte

Virtual environment trajectory analysis:a basis for navigational assistance and scene adaptivity

This paper describes the analysis and clustering of motion trajectories obtained while users navigate within a virtual environment (VE). It presents a neural network simulation that produces a set of five clusters which help to differentiate users on the basis of efficient and inefficient navigational strategies. The accuracy of classification carried out with a self-organising map algorithm was tested and improved to in excess of 85% by using learning vector quantisation. This paper considers how such user classifications could be utilised in the delivery of intelligent navigational support and the dynamic reconfiguration of scenes within such VEs. We explore how such intelligent assistance and system adaptivity could be delivered within a Multi-Agent Systems (MAS) context

Trace element contamination in the arms of the Danube Delta (Romania/Ukraine): Current state of knowledge and future needs

This paper provides the first critical synopsis of contamination by selected trace elements in the whole Danube Delta (Romania/Ukraine) to: identify general patterns of contamination by trace elements across the Delta, provide recommendations to refine existing monitoring networks and discuss the potential toxicity of trace elements in the whole Delta. Sediment samples were collected between 2004 and 2007 in the three main branches of the Delta (Chilia, Sulina and Sfantu Gheorghe) and in the secondary delta of the Chilia branch. Samples were analyzed for trace elements (Cd, Co, Cr, Cu, Ni, Pb, V, and Zn) and TiO2, Fe2O3, MnO, CaCO3 and total organic carbon. Cluster analysis (CA) and Principal Component Analysis (PCA) showed that levels of Cd, Cu, Pb, and Zn were influenced by anthropogenic activities. At the opposite, concentrations of Cr and Ni largely originated from the weathering of rocks located in the Romanian part of the Danube catchment and naturally rich in these elements. Data analysis using Self- Organizing Maps confirmed the conclusions of CA/PCA and further detected that the contamination tended to be higher in the Chilia and Sulina arms than in the Sfantu Gheorghe arm. The potential ecological risks due to trace element contamination in the Danube Delta could be identified as moderate and localized, provided that the presence of the natural sources of Cr and Ni was properly considered. The available results suggest that monitoring sediment quality at the mouths of Sulina and Sfantu Gheorghe arms is probably enough to get a picture of the sediment quality along their entire lengths. However, a larger network of monitoring points is necessary in the Chilia and secondary Chilia delta to account for the presence of local point sources and for the more complex hydrodynamic of this part of the Danube Delta

Towards adaptive multi-robot systems: self-organization and self-adaptation

Dieser Beitrag ist mit Zustimmung des Rechteinhabers aufgrund einer (DFG geförderten) Allianz- bzw. Nationallizenz frei zugänglich.This publication is with permission of the rights owner freely accessible due to an Alliance licence and a national licence (funded by the DFG, German Research Foundation) respectively.The development of complex systems ensembles that operate in uncertain environments is a major challenge. The reason for this is that system designers are not able to fully specify the system during specification and development and before it is being deployed. Natural swarm systems enjoy similar characteristics, yet, being self-adaptive and being able to self-organize, these systems show beneficial emergent behaviour. Similar concepts can be extremely helpful for artificial systems, especially when it comes to multi-robot scenarios, which require such solution in order to be applicable to highly uncertain real world application. In this article, we present a comprehensive overview over state-of-the-art solutions in emergent systems, self-organization, self-adaptation, and robotics. We discuss these approaches in the light of a framework for multi-robot systems and identify similarities, differences missing links and open gaps that have to be addressed in order to make this framework possible