Self-organising neural networks for adaptive control

Self-organizing neural networks have been implemented in a wide range of application areas such as speech processing, image processing, optimization and robotics. Recent variations to the basic model proposed by the authors enable it to order state space using a subset of the input vector and to apply a local adaptation procedure that does not rely on a predefined test duration limit. Both these variations have been incorporated into a new feature map architecture that forms an integral part of an Hybrid Learning System (HLS) based on a genetic-based classifier system. Problems are represented within HLS as objects characterized by environmental features. Objects controlled by the system have preset targets set against a subset of their features. The system's objective is to achieve these targets by evolving a behavioural repertoire that efficiently explores and exploits the problem environment. Feature maps encode two types of knowledge within HLS — long-term memory traces of useful regularities within the environment and the classifier performance data calibrated against an object's feature states and targets. Self-organization of these networks constitutes non-genetic-based (experience-driven) learning within HLS. This paper presents a description of the HLS architecture and an analysis of the modified feature map implementing associative memory. Initial results are presented that demonstrate the behaviour of the system on a simple control task.

A helmet mounted display system with active gaze control for visual telepresence

The objective of a Visual Telepresence System is to provide the operator with a high fidelity image from a remote stereo camera pair linked to a pan/tilt device such that the operator may reorient the camera position by use of head movement. Systems such as these which utilise virtual reality style helmet mounted displays have a number of limitations. The geometry of the camera positions and of the displays is generally fixed and is most suitable only for viewing elements of a scene at a particular distance. To address such limitations, a prototype system has been developed where the geometry of the displays and cameras is dynamically controlled by the eye movement of the operator. This paper explores why it is necessary to actively adjust the display system as well as the cameras and justifies the use of mechanical adjustment of the displays as an alternative to adjustment by electronic or image processing methods. The electronic and mechanical design is described including optical arrangements and control algorithms. The performance and accuracy of the system is assessed with respect to eye movement.

Parallel pipelined array architectures for real-time histogram computation in consumer devices

The real-time parallel computation of histograms using an array of pipelined cells is proposed and prototyped in this paper with application to consumer imaging products. The array operates in two modes: histogram computation and histogram reading. The proposed parallel computation method does not use any memory blocks. The resulting histogram bins can be stored into an external memory block in a pipelined fashion for subsequent reading or streaming of the results. The array of cells can be tuned to accommodate the required data path width in a VLSI image processing engine as present in many imaging consumer devices. Synthesis of the architectures presented in this paper in FPGA are shown to compute the real-time histogram of images streamed at over 36 megapixels at 30 frames/s by processing in parallel 1, 2 or 4 pixels per clock cycle.

Simulation of urban microclimates

Urban microclimates are greatly affected by urban form and texture and have a significant impact on building energy performance. The impact of urban form on energy consumption in buildings mainly relates to the availability of the uses of solar radiation, daylighting and natural ventilation. The urban heat island (UHI) effect increases the risk of overheating in buildings as well as the maximum energy demand for cooling. A need has arisen for a robust calculation tool (using the first-cut calculation method) to enable planners, architects and environmental assessors, to quickly and accurately compare the impact of different urban forms on local climate and UHI mitigation strategies. This paper describes a tool for the simulation of urban microclimates, which is developed by integrating image processing with a coupled thermal and airflow model.

Dynamic vergence telepresence system incorporating active gaze control

Visual Telepresence system which utilize virtual reality style helmet mounted displays have a number of limitations. The geometry of the camera positions and of the display is fixed and is most suitable only for viewing elements of a scene at a particular distance. In such a system, the operator's ability to gaze around without use of head movement is severely limited. A trade off must be made between a poor viewing resolution or a narrow width of viewing field. To address these limitations a prototype system where the geometry of the displays and cameras is dynamically controlled by the eye movement of the operator has been developed. This paper explores the reasons why is necessary to actively adjust both the display system and the cameras and furthermore justifies the use of mechanical adjustment of the displays as an alternative to adjustment by electronic or image processing methods. The electronic and mechanical design is described including optical arrangements and control algorithms, An assessment of the performance of the system against a fixed camera/display system when operators are assigned basic tasks involving depth and distance/size perception. The sensitivity to variations in transient performance of the display and camera vergence is also assessed.

Smooth Regrading of Discretized Data

Methods for producing nonuniform transformations, or regradings, of discrete data are discussed. The transformations are useful in image processing, principally for enhancement and normalization of scenes. Regradings which “equidistribute” the histogram of the data, that is, which transform it into a constant function, are determined. Techniques for smoothing the regrading, dependent upon a continuously variable parameter, are presented. Generalized methods for constructing regradings such that the histogram of the data is transformed into any prescribed function are also discussed. Numerical algorithms for implementing the procedures and applications to specific examples are described.

An overview of interactive visual data mining techniques for knowledge discovery

n the past decade, the analysis of data has faced the challenge of dealing with very large and complex datasets and the real-time generation of data. Technologies to store and access these complex and large datasets are in place. However, robust and scalable analysis technologies are needed to extract meaningful information from these datasets. The research field of Information Visualization and Visual Data Analytics addresses this need. Information visualization and data mining are often used complementary to each other. Their common goal is the extraction of meaningful information from complex and possibly large data. However, though data mining focuses on the usage of silicon hardware, visualization techniques also aim to access the powerful image-processing capabilities of the human brain. This article highlights the research on data visualization and visual analytics techniques. Furthermore, we highlight existing visual analytics techniques, systems, and applications including a perspective on the field from the chemical process industry.

Thermal remote sensing of sea surface temperature

Sea surface temperature has been an important application of remote sensing from space for three decades. This chapter first describes well-established methods that have delivered valuable routine observations of sea surface temperature for meteorology and oceanography. Increasingly demanding requirements, often related to climate science, have highlighted some limitations of these ap-proaches. Practitioners have had to revisit techniques of estimation, of characterising uncertainty, and of validating observations—and even to reconsider the meaning(s) of “sea surface temperature”. The current understanding of these issues is reviewed, drawing attention to ongoing questions. Lastly, the prospect for thermal remote sens-ing of sea surface temperature over coming years is discussed.

Thermoelectric materials: a new rapid synthesis process for non-toxic and high-performance tetrahedrite compounds

The feasibility to synthesize, in large quantity, pure and non-toxic tetrahedrite compounds using high-energy mechanical-alloying from only elemental precursors is reported in the present paper for the first time. Our processing technique allows a better control of the final product composition and leads to high thermoelectric performances (ZT of 0.75 at 700 K), comparable to that reported on sealed tube synthesis samples. Combined with spark plasma sintering, the production of highly pure and dense samples is achieved in a very short time, at least 8 times shorter than in conventional liquid-solid-vapor synthesis process. The process described in this paper is a promising way to produce high performance tetrahedrite materials for cost-effective and large-scale thermoelectric applications.

Mapping low- and high-density clouds in astrophysical nebulae by imaging forbidden line emission

Emission line ratios have been essential for determining physical parameters such as gas temperature and density in astrophysical gaseous nebulae. With the advent of panoramic spectroscopic devices, images of regions with emission lines related to these physical parameters can, in principle, also be produced. We show that, with observations from modern instruments, it is possible to transform images taken from density-sensitive forbidden lines into images of emission from high- and low-density clouds by applying a transformation matrix. In order to achieve this, images of the pairs of density-sensitive lines as well as the adjacent continuum have to be observed and combined. We have computed the critical densities for a series of pairs of lines in the infrared, optical, ultraviolet and X-rays bands, and calculated the pair line intensity ratios in the high- and low-density limit using a four- and five-level atom approximation. In order to illustrate the method, we applied it to Gemini Multi-Object Spectrograph (GMOS) Integral Field Unit (GMOS-IFU) data of two galactic nuclei. We conclude that this method provides new information of astrophysical interest, especially for mapping low- and high-density clouds; for this reason, we call it `the ld/hd imaging method`.

PCA Tomography: how to extract information from data cubes

Astronomy has evolved almost exclusively by the use of spectroscopic and imaging techniques, operated separately. With the development of modern technologies, it is possible to obtain data cubes in which one combines both techniques simultaneously, producing images with spectral resolution. To extract information from them can be quite complex, and hence the development of new methods of data analysis is desirable. We present a method of analysis of data cube (data from single field observations, containing two spatial and one spectral dimension) that uses Principal Component Analysis (PCA) to express the data in the form of reduced dimensionality, facilitating efficient information extraction from very large data sets. PCA transforms the system of correlated coordinates into a system of uncorrelated coordinates ordered by principal components of decreasing variance. The new coordinates are referred to as eigenvectors, and the projections of the data on to these coordinates produce images we will call tomograms. The association of the tomograms (images) to eigenvectors (spectra) is important for the interpretation of both. The eigenvectors are mutually orthogonal, and this information is fundamental for their handling and interpretation. When the data cube shows objects that present uncorrelated physical phenomena, the eigenvector`s orthogonality may be instrumental in separating and identifying them. By handling eigenvectors and tomograms, one can enhance features, extract noise, compress data, extract spectra, etc. We applied the method, for illustration purpose only, to the central region of the low ionization nuclear emission region (LINER) galaxy NGC 4736, and demonstrate that it has a type 1 active nucleus, not known before. Furthermore, we show that it is displaced from the centre of its stellar bulge.

Identification of the nuclear factor kappa-beta (NF-kB) in cortical of mice Wistar using Technovit 7200 VCR (R)

Objective: this study aimed to develop a nondecalcified bone sample processing technique enabling immunohistochemical labeling of proteins by kappa-beta nuclear factor (NF-kB) utilizing the Technovit 7200 VCR (R) in adult male Wistar rats. Study Method: A 1.8 mm diameter defect was performed 0.5mm from the femur proximal joint by means of a round bur. Experimental groups were divided according to fixing solution prior to histologic processing: Group 1- ethanol 70%; Group 2-10% buffered formalin; and Group 3- Glycerol diluted in 70% ethanol at a 70/30 ratio + 10% buffered formalin. The post-surgical periods ranged from 01 to 24 hours. Control groups included a nonsurgical procedure group (NSPG) and surgical procedures where bone exposure was performed (SPBE) without drilling. Prostate carcinoma was the positive control (PC) and samples subjected to incomplete immunohistochemistry protocol were the negative control (NC). Following euthanization, all samples were kept at 4 degrees C for 7 days, and were dehydrated in a series of alcohols at -20 degrees C. The polymer embedding procedure was performed at ethanol/polymer ratios of 70%-30%, 50%-50%, 30%-70%, 100%, and 100% for 72 hours at -20 degrees C. Polymerization followed the manufacturer`s recommendation. The samples were grounded and polished to 10-15 mu m thickness, and were deacrylated. The sections were rehydrated and were submitted to the primary polyclonal antibody anti-NF-kB on a 1:75 dilution for 12 hours at room temperature. Results: Microscopy showed that the Group 2 presented positive reaction to NF-kB, diffuse reactions for NSPG and SPBE, and no reaction for the NC group. Conclusion: The results obtained support the feasibility of the developed immunohistochemistry technique.

Topological triangle characterization with application to object detection from images

A novel mathematical framework inspired on Morse Theory for topological triangle characterization in 2D meshes is introduced that is useful for applications involving the creation of mesh models of objects whose geometry is not known a priori. The framework guarantees a precise control of topological changes introduced as a result of triangle insertion/removal operations and enables the definition of intuitive high-level operators for managing the mesh while keeping its topological integrity. An application is described in the implementation of an innovative approach for the detection of 2D objects from images that integrates the topological control enabled by geometric modeling with traditional image processing techniques. (C) 2008 Published by Elsevier B.V.

A Road Following Approach Using Artificial Neural Networks Combinations

Navigation is a broad topic that has been receiving considerable attention from the mobile robotic community over the years. In order to execute autonomous driving in outdoor urban environments it is necessary to identify parts of the terrain that can be traversed and parts that should be avoided. This paper describes an analyses of terrain identification based on different visual information using a MLP artificial neural network and combining responses of many classifiers. Experimental tests using a vehicle and a video camera have been conducted in real scenarios to evaluate the proposed approach.

Design of associative memories using cellular neural networks

Cellular neural networks (CNNs) have locally connected neurons. This characteristic makes CNNs adequate for hardware implementation and, consequently, for their employment on a variety of applications as real-time image processing and construction of efficient associative memories. Adjustments of CNN parameters is a complex problem involved in the configuration of CNN for associative memories. This paper reviews methods of associative memory design based on CNNs, and provides comparative performance analysis of these approaches.