Automatic contour extraction from 2D neuron images

This work describes a novel methodology for automatic contour extraction from 2D images of 3D neurons (e.g. camera lucida images and other types of 2D microscopy). Most contour-based shape analysis methods cannot be used to characterize such cells because of overlaps between neuronal processes. The proposed framework is specifically aimed at the problem of contour following even in presence of multiple overlaps. First, the input image is preprocessed in order to obtain an 8-connected skeleton with one-pixel-wide branches, as well as a set of critical regions (i.e., bifurcations and crossings). Next, for each subtree, the tracking stage iteratively labels all valid pixel of branches, tip to a critical region, where it determines the suitable direction to proceed. Finally, the labeled skeleton segments are followed in order to yield the parametric contour of the neuronal shape under analysis. The reported system was successfully tested with respect to several images and the results from a set of three neuron images are presented here, each pertaining to a different class, i.e. alpha, delta and epsilon ganglion cells, containing a total of 34 crossings. The algorithms successfully got across all these overlaps. The method has also been found to exhibit robustness even for images with close parallel segments. The proposed method is robust and may be implemented in an efficient manner. The introduction of this approach should pave the way for more systematic application of contour-based shape analysis methods in neuronal morphology. (C) 2008 Elsevier B.V. All rights reserved.

An algorithm for automatic checking of exercises in a dynamic geometry system: iGeom

One of the key issues in e-learning environments is the possibility of creating and evaluating exercises. However, the lack of tools supporting the authoring and automatic checking of exercises for specifics topics (e.g., geometry) drastically reduces advantages in the use of e-learning environments on a larger scale, as usually happens in Brazil. This paper describes an algorithm, and a tool based on it, designed for the authoring and automatic checking of geometry exercises. The algorithm dynamically compares the distances between the geometric objects of the student`s solution and the template`s solution, provided by the author of the exercise. Each solution is a geometric construction which is considered a function receiving geometric objects (input) and returning other geometric objects (output). Thus, for a given problem, if we know one function (construction) that solves the problem, we can compare it to any other function to check whether they are equivalent or not. Two functions are equivalent if, and only if, they have the same output when the same input is applied. If the student`s solution is equivalent to the template`s solution, then we consider the student`s solution as a correct solution. Our software utility provides both authoring and checking tools to work directly on the Internet, together with learning management systems. These tools are implemented using the dynamic geometry software, iGeom, which has been used in a geometry course since 2004 and has a successful track record in the classroom. Empowered with these new features, iGeom simplifies teachers` tasks, solves non-trivial problems in student solutions and helps to increase student motivation by providing feedback in real time. (c) 2008 Elsevier Ltd. All rights reserved.

Automatic camera control in virtual environments augmented using multiple sparse videos

Automated virtual camera control has been widely used in animation and interactive virtual environments. We have developed a multiple sparse camera based free view video system prototype that allows users to control the position and orientation of a virtual camera, enabling the observation of a real scene in three dimensions (3D) from any desired viewpoint. Automatic camera control can be activated to follow selected objects by the user. Our method combines a simple geometric model of the scene composed of planes (virtual environment), augmented with visual information from the cameras and pre-computed tracking information of moving targets to generate novel perspective corrected 3D views of the virtual camera and moving objects. To achieve real-time rendering performance, view-dependent textured mapped billboards are used to render the moving objects at their correct locations and foreground masks are used to remove the moving objects from the projected video streams. The current prototype runs on a PC with a common graphics card and can generate virtual 2D views from three cameras of resolution 768 x 576 with several moving objects at about 11 fps. (C)2011 Elsevier Ltd. All rights reserved.

New Improvements in Automatic Structure Elucidation Using the LSD (Logic for Structure Determination) and the SISTEMAT Expert Systems

This article describes the integration of the LSD (Logic for Structure Determination) and SISTEMAT expert systems that were both designed for the computer-assisted structure elucidation of small organic molecules. A first step has been achieved towards the linking of the SISTEMAT database with the LSD structure generator. The skeletal descriptions found by the SISTEMAT programs are now easily transferred to LSD as substructural constraints. Examples of the synergy between these expert systems are given for recently reported natural products.

Automatic devices for monitoring environmentally induced auto-oxidative degradation of artistic materials in conservation sites

This paper describes an automatic device for in situ and continuous monitoring of the ageing process occurring in natural and synthetic resins widely used in art and in the conservation and restoration of cultural artefacts. The results of tests carried out under accelerated ageing conditions are also presented. This easy-to-assemble palm-top device, essentially consists of oscillators based on quartz crystal resonators coated with films of the organic materials whose response to environmental stress is to be addressed. The device contains a microcontroller which selects at pre-defined time intervals the oscillators and records and stores their oscillation frequency. The ageing of the coatings, caused by the environmental stress and resulting in a shift in the oscillation frequency of the modified crystals, can be straightforwardly monitored in this way. The kinetics of this process reflects the level of risk damage associated with a specific microenvironment. In this case, natural and artificial resins, broadly employed in art and restoration of artistic and archaeological artefacts (dammar and Paraloid B72), were applied onto the crystals. The environmental stress was represented by visible and UV radiation, since the chosen materials are known to be photochemically active, to different extents. In the case of dammar, the results obtained are consistent with previous data obtained using a bench-top equipment by impedance analysis through discrete measurements and confirm that the ageing of this material is reflected in the gravimetric response of the modified quartz crystals. As for Paraloid B72, the outcome of the assays indicates that the resin is resistant to visible light, but is very sensitive to UV irradiation. The use of a continuous monitoring system, apart from being obviously more practical, is essential to identify short-term (i.e. reversible) events, like water vapour adsorption/desorption processes, and to highlight ageing trends or sudden changes of such trends. (C) 2007 Elsevier B.V. All rights reserved.

Machine vision for the automatic classification of images acquired from Non-destructive tests

This project is based on Artificial Intelligence (A.I) and Digital Image processing (I.P) for automatic condition monitoring of sleepers in the railway track. Rail inspection is a very important task in railway maintenance for traffic safety issues and in preventing dangerous situations. Monitoring railway track infrastructure is an important aspect in which the periodical inspection of rail rolling plane is required.Up to the present days the inspection of the railroad is operated manually by trained personnel. A human operator walks along the railway track searching for sleeper anomalies. This monitoring way is not more acceptable for its slowness and subjectivity. Hence, it is desired to automate such intuitive human skills for the development of more robust and reliable testing methods. Images of wooden sleepers have been used as data for my project. The aim of this project is to present a vision based technique for inspecting railway sleepers (wooden planks under the railway track) by automatic interpretation of Non Destructive Test (NDT) data using A.I. techniques in determining the results of inspection.

Classification of Parkinson’s Disease using MultiPass Lvq,Logistic Model Tree,K-Star for Audio Data set : Classification of Parkinson Disease using Audio Dataset

Parkinson's disease (PD) is a degenerative illness whose cardinal symptoms include rigidity, tremor, and slowness of movement. In addition to its widely recognized effects PD can have a profound effect on speech and voice.The speech symptoms most commonly demonstrated by patients with PD are reduced vocal loudness, monopitch, disruptions of voice quality, and abnormally fast rate of speech. This cluster of speech symptoms is often termed Hypokinetic Dysarthria.The disease can be difficult to diagnose accurately, especially in its early stages, due to this reason, automatic techniques based on Artificial Intelligence should increase the diagnosing accuracy and to help the doctors make better decisions. The aim of the thesis work is to predict the PD based on the audio files collected from various patients.Audio files are preprocessed in order to attain the features.The preprocessed data contains 23 attributes and 195 instances. On an average there are six voice recordings per person, By using data compression technique such as Discrete Cosine Transform (DCT) number of instances can be minimized, after data compression, attribute selection is done using several WEKA build in methods such as ChiSquared, GainRatio, Infogain after identifying the important attributes, we evaluate attributes one by one by using stepwise regression.Based on the selected attributes we process in WEKA by using cost sensitive classifier with various algorithms like MultiPass LVQ, Logistic Model Tree(LMT), K-Star.The classified results shows on an average 80%.By using this features 95% approximate classification of PD is acheived.This shows that using the audio dataset, PD could be predicted with a higher level of accuracy.

Determination of Thermal and Blue Light Photochemical Hazard Protection needed by Automatic Welding filters

Recent developments in biological research, has shown that the initial maximum permissible exposure (MPE) limits for protection of workers from risks associated with artificial optical radiations were more stringent than needed. Using the most recent MPE limits for artificial optical radiation this piece of work was focused on the investigation of the level of visible light attenuation needed by automatic welding filters in case of switching failure. Results from the comparison of different exposure standards were employed in investigating the need of Vis/IR and blue light transmittance requirement for automatic welding filters. Real and arbitrary spectra were taken into consideration for the worst and best case scenarios of artificial optical radiations. An excel worksheet developed during the execution of this project took into consideration the exposure from different light sources and the precision of the spectrometer used in measuring the transmittances of a welding filter. The worksheet was developed and tested with known product properties to investigate the validity of its formulation. The conclusion drawn from this project was that attenuation in the light state will be needed for products with the darkest state shade 11 or higher. Also shown is that current welding filter protects the eye well enough even in the case of switching failure.

Automatic layout generation of static CMOS circuits targeting delay and power

The evolution of integrated circuits technologies demands the development of new CAD tools. The traditional development of digital circuits at physical level is based in library of cells. These libraries of cells offer certain predictability of the electrical behavior of the design due to the previous characterization of the cells. Besides, different versions of each cell are required in such a way that delay and power consumption characteristics are taken into account, increasing the number of cells in a library. The automatic full custom layout generation is an alternative each time more important to cell based generation approaches. This strategy implements transistors and connections according patterns defined by algorithms. So, it is possible to implement any logic function avoiding the limitations of the library of cells. Tools of analysis and estimate must offer the predictability in automatic full custom layouts. These tools must be able to work with layout estimates and to generate information related to delay, power consumption and area occupation. This work includes the research of new methods of physical synthesis and the implementation of an automatic layout generation in which the cells are generated at the moment of the layout synthesis. The research investigates different strategies of elements disposition (transistors, contacts and connections) in a layout and their effects in the area occupation and circuit delay. The presented layout strategy applies delay optimization by the integration with a gate sizing technique. This is performed in such a way the folding method allows individual discrete sizing to transistors. The main characteristics of the proposed strategy are: power supply lines between rows, over the layout routing (channel routing is not used), circuit routing performed before layout generation and layout generation targeting delay reduction by the application of the sizing technique. The possibility to implement any logic function, without restrictions imposed by a library of cells, allows the circuit synthesis with optimization in the number of the transistors. This reduction in the number of transistors decreases the delay and power consumption, mainly the static power consumption in submicrometer circuits. Comparisons between the proposed strategy and other well-known methods are presented in such a way the proposed method is validated.

Automatic model selection for forecasting brazilian stock returns

This study aims to contribute on the forecasting literature in stock return for emerging markets. We use Autometrics to select relevant predictors among macroeconomic, microeconomic and technical variables. We develop predictive models for the Brazilian market premium, measured as the excess return over Selic interest rate, Itaú SA, Itaú-Unibanco and Bradesco stock returns. We nd that for the market premium, an ADL with error correction is able to outperform the benchmarks in terms of economic performance. For individual stock returns, there is a trade o between statistical properties and out-of-sample performance of the model.