Logarithmically proportional objective function for planar surfaces recognition in 3D point cloud

3D laser scanning is becoming a standard technology to generate building models of a facility's as-is condition. Since most constructions are constructed upon planar surfaces, recognition of them paves the way for automation of generating building models. This paper introduces a new logarithmically proportional objective function that can be used in both heuristic and metaheuristic (MH) algorithms to discover planar surfaces in a point cloud without exploiting any prior knowledge about those surfaces. It can also adopt itself to the structural density of a scanned construction. In this paper, a metaheuristic method, genetic algorithm (GA), is used to test this introduced objective function on a synthetic point cloud. The results obtained show the proposed method is capable to find all plane configurations of planar surfaces (with a wide variety of sizes) in the point cloud with a minor distance to the actual configurations. © 2014 IEEE.

Diffuse liver disease classification from ultrasound surface characterization, clinical and laboratorial data

In this work liver contour is semi-automatically segmented and quantified in order to help the identification and diagnosis of diffuse liver disease. The features extracted from the liver contour are jointly used with clinical and laboratorial data in the staging process. The classification results of a support vector machine, a Bayesian and a k-nearest neighbor classifier are compared. A population of 88 patients at five different stages of diffuse liver disease and a leave-one-out cross-validation strategy are used in the classification process. The best results are obtained using the k-nearest neighbor classifier, with an overall accuracy of 80.68%. The good performance of the proposed method shows a reliable indicator that can improve the information in the staging of diffuse liver disease.

Estimation of 3D shapes using active surface models

This paper addresses the estimation of surfaces from a set of 3D points using the unified framework described in [1]. This framework proposes the use of competitive learning for curve estimation, i.e., a set of points is defined on a deformable curve and they all compete to represent the available data. This paper extends the use of the unified framework to surface estimation. It o shown that competitive learning performes better than snakes, improving the model performance in the presence of concavities and allowing to desciminate close surfaces. The proposed model is evaluated in this paper using syntheticdata and medical images (MRI and ultrasound images).

Scaling of the elastic contribution to the surface free energy of a nematic liquid crystal on a sawtoothed substrate

We characterize the elastic contribution to the surface free energy of a nematic liquid crystal in the presence of a sawtooth substrate. Our findings are based on numerical minimization of the Landau-de Gennes model and analytical calculations on the Frank-Oseen theory. The nucleation of disclination lines (characterized by non-half-integer winding numbers) in the wedges and apexes of the substrate induces a leading order proportional to q ln q to the elastic contribution to the surface free-energy density, with q being the wave number associated with the substrate periodicity.

Die Surface Designer System

This paper defines Die Surface Designer (DSD) System for fast draw die in the product development feasibility phase on surfaces coming from styling. We propose a CAD integration, for better support the design process in industry, particularly on the development of new products in automotive sector. The DSD system intends to reduce the lead time by providing and integrating flexible and efficient capabilities for testing early concepts from surface analysis points of view in automotive product development.

Tuning Iris Recognition for Noisy Images

The use of iris recognition for human authentication has been spreading in the past years. Daugman has proposed a method for iris recognition, composed by four stages: segmentation, normalization, feature extraction, and matching. In this paper we propose some modifications and extensions to Daugman's method to cope with noisy images. These modifications are proposed after a study of images of CASIA and UBIRIS databases. The major modification is on the computationally demanding segmentation stage, for which we propose a faster and equally accurate template matching approach. The extensions on the algorithm address the important issue of pre-processing that depends on the image database, being mandatory when we have a non infra-red camera, like a typical WebCam. For this scenario, we propose methods for reflection removal and pupil enhancement and isolation. The tests, carried out by our C# application on grayscale CASIA and UBIRIS images show that the template matching segmentation method is more accurate and faster than the previous one, for noisy images. The proposed algorithms are found to be efficient and necessary when we deal with non infra-red images and non uniform illumination.

Image and color recognition using amorphous silicon p-i-n photodiodes

Large area hydrogenated amorphous silicon single and stacked p-i-n structures with low conductivity doped layers are proposed as monochrome and color image sensors. The layers of the structures are based on amorphous silicon alloys (a-Si(x)C(1-x):H). The current-voltage characteristics and the spectral sensitivity under different bias conditions are analyzed. The output characteristics are evaluated under different read-out voltages and scanner wavelengths. To extract information on image shape, intensity and color, a modulated light beam scans the sensor active area at three appropriate bias voltages and the photoresponse in each scanning position ("sub-pixel") is recorded. The investigation of the sensor output under different scanner wavelengths and varying electrical bias reveals that the response can be tuned, thus enabling color separation. The operation of the sensor is exemplified and supported by a numerical simulation.

Comparison of deposited surface area of airborne ultrafine particles generated from two welding processes

This article describes work performed on the assessment of the levels of airborne ultrafine particles emitted in two welding processes metal-active gas (MAG) of carbon steel and friction-stir welding (FSW) of aluminium in terms of deposited area in alveolar tract of the lung using a nanoparticle surface area monitor analyser. The obtained results showed the dependence from process parameters on emitted ultrafine particles and clearly demonstrated the presence of ultrafine particles, when compared with background levels. The obtained results showed that the process that results on the lower levels of alveolar-deposited surface area is FSW, unlike MAG. Nevertheless, all the tested processes resulted in important doses of ultrafine particles that are to be deposited in the human lung of exposed workers.

Nanofiltration of surface water for the removal of endocrine disruptors

The assessment of surface water nanofiltration (NF) for the removal of endocrine disruptors (EDs) Nonylphenol Ethoxylate (IGEPAL), 4-Nonylphenol (NP) and 4-Octylphenol (OP) was carried out with three commercial NF membranes - NF90, NF200, NF270. The permeation experiments were conducted in laboratory flat-cell units of 13.2 x 10(-4) m(2) of surface area and in a DSS Lab-unit M20 with a membrane surface area of 0.036 m2. The membranes hydraulic permeabilities ranged from 3.7 to 15.6 kg/h/m(2)/bar and the rejection coefficients to NaCl, Na2SO4 and Glucose are for NF90: 97%, 99% and 97%, respectively; for NF200: 66%, 98% and 90%, respectively and for NF270: 48%, 94% and 84%, respectively. Three sets of nanofiltration experiments were carried out: i) NF of aqueous model solutions of NP, IGEPAL and OP running in total recirculation mode; ii) NF of surface water from Rio Sado (Settibal, Portugal) running in concentration mode; iii) NF of surface water from Rio Sado inoculated with NP, IGEPAL and OP running in concentration mode. The results of model solutions experiments showed that the EDs rejection coefficients are approximately 100% for all the membranes. The results obtained for the surface water showed that the rejection coefficients to natural organic Matter (NOM) are 94%, 82% and 78% for NF90, NF200 and NF 270 membranes respectively, with and without inoculation of EDs. The rejection coefficients to EDs in surface water with and without inoculation of EDs are 100%, showing that there is a fraction of NOM of high molecular weight that retains the EDs in the concentrate and that there is a fraction of NOM of low molecular weight that permeates through the NF membranes free of EDs.

Liquid crystal necklaces: cholesteric drops threaded by thin cellulose fibres

Liquid crystals in confined geometries exhibit numerous complex structures often including topological defects that are controlled by the nematic elasticity, chirality and surface anchoring. In this work, we study the structures of cholesteric droplets pierced by cellulose fibres with planar anchoring at droplet and fibre surfaces. By varying the temperature we demonstrate the role of twisting power and droplet diameter on the equilibrium structures. The observed structures are complemented by detailed numerical simulations of possible director fields decorated by defects. Three distinct structures, a bipolar and two ring configurations, are identified experimentally and numerically. Designing cholesteric liquid crystal microdroplets on thin long threads opens new routes to produce fibre waveguides decorated with complex microresonators.

Embedded platform for ECG biometric recognition

Trabalho Final de Mestrado para obtenção do grau de Mestre em Engenharia de Electrónica e Telecomunicações

Monitorization of alveolar deposited surface area of nanoparticles and ultrafine particles in different environments

Nanotechnology is an important emerging industry with a projected annual market of around one trillion dollars by 2015. It involves the control of atoms and molecules to create new materials with a variety of useful functions. Although there are advantages on the utilization of these nano-scale materials, questions related with its impact over the environment and human health must be addressed too, so that potential risks can be limited at early stages of development. At this time, occupational health risks associated with manufacturing and use of nanoparticles are not yet clearly understood. However, workers may be exposed to nanoparticles through inhalation at levels that can greatly exceed ambient concentrations. Current workplace exposure limits are based on particle mass, but this criteria could not be adequate in this case as nanoparticles are characterized by very large surface area, which has been pointed out as the distinctive characteristic that could even turn out an inert substance into another substance exhibiting very different interactions with biological fluids and cells. Therefore, it seems that, when assessing human exposure based on the mass concentration of particles, which is widely adopted for particles over 1 μm, would not work in this particular case. In fact, nanoparticles have far more surface area for the equivalent mass of larger particles, which increases the chance they may react with body tissues. Thus, it has been claimed that surface area should be used for nanoparticle exposure and dosing. As a result, assessing exposure based on the measurement of particle surface area is of increasing interest. It is well known that lung deposition is the most efficient way for airborne particles to enter the body and cause adverse health effects. If nanoparticles can deposit in the lung and remain there, have an active surface chemistry and interact with the body, then, there is potential for exposure. It was showed that surface area plays an important role in the toxicity of nanoparticles and this is the metric that best correlates with particle-induced adverse health effects. The potential for adverse health effects seems to be directly proportional to particle surface area. The objective of the study is to identify and validate methods and tools for measuring nanoparticles during production, manipulation and use of nanomaterials.

Does Independent Component Analysis Play a Role in Unmixing Hyperspectral Data?

Chapter in Book Proceedings with Peer Review First Iberian Conference, IbPRIA 2003, Puerto de Andratx, Mallorca, Spain, JUne 4-6, 2003. Proceedings

Uma análise das diferenças em termos da cultura e dos interesses profissionais a partir do projeto de substituiçao das IAS 39: Financial Instruments - Recognition and Measurement

Mestrado em Contabilidade

Enhancing Multimodal Silent Speech Interfaces With Feature Selection

In research on Silent Speech Interfaces (SSI), different sources of information (modalities) have been combined, aiming at obtaining better performance than the individual modalities. However, when combining these modalities, the dimensionality of the feature space rapidly increases, yielding the well-known "curse of dimensionality". As a consequence, in order to extract useful information from this data, one has to resort to feature selection (FS) techniques to lower the dimensionality of the learning space. In this paper, we assess the impact of FS techniques for silent speech data, in a dataset with 4 non-invasive and promising modalities, namely: video, depth, ultrasonic Doppler sensing, and surface electromyography. We consider two supervised (mutual information and Fisher's ratio) and two unsupervised (meanmedian and arithmetic mean geometric mean) FS filters. The evaluation was made by assessing the classification accuracy (word recognition error) of three well-known classifiers (knearest neighbors, support vector machines, and dynamic time warping). The key results of this study show that both unsupervised and supervised FS techniques improve on the classification accuracy on both individual and combined modalities. For instance, on the video component, we attain relative performance gains of 36.2% in error rates. FS is also useful as pre-processing for feature fusion. Copyright © 2014 ISCA.