Delamination and wear in drilling of carbon-fiber reinforced plastic composites using multilayer TiAlN/TiN PVD-coated tungsten carbide tools

This study aims to investigate drilling process in carbon-fiber reinforced plastic (CFRP) composites with multilayer TiAlN/TiN PVD-coated tungsten carbide drill. The effect of process parameters have been investigated in drilling of Hexcel M21-T700GC. Thrust force and torque were measured online throughout the drilling experiments. Delamination were observed using optical microscope and analyzed via a developed algorithm based on digital image processing technique. Surface roughness of each hole was measured using a surface profilometer. In addition, the progression of tool wear in various surfaces of drill was observed using tool microscope and measured using image software. Our results indicate that the thrust force and torque increased with the increasing cutting speed and feed rate. Delamination and average surface roughness that rose with the increase in feed rate, however, decreased with the increasing cutting speed. The average surface roughness tended to increase with the increase in feed rate and decrease with the increasing cutting speed in drilling of carbon-fiber reinforced plastic (CFRP). Feed rate was found as the predominant factor on the drilling outputs. Abrasive wear was observed on both flank and relief surfaces, which created edge wear on cutting edges. No sign of chipping or plastic deformation has been observed on the surfaces of drills. © 2012 The Author(s).

High-Resolution Microwave Near-Field Imaging Using Resonance Probes

A novel microwave high-resolution near-field imaging technique is proposed and experimentally evaluated in reflectometry imaging scenarios involving planar metal-dielectric structures. Two types of resonance near field probes-a small helix antenna and a loaded subwavelength slot aperture are studied in this paper. These probes enable very tight spatial field localization with the full width at half maximum around one tenth of a wavelength, λ, at λ/100-λ/10 standoff distance. Importantly, the proposed probes permit resonance electromagnetic coupling to dielectric or printed conductive patterns, which leads to the possibility of very high raw image resolution with imaged feature-to-background contrast greater than 10-dB amplitude and 50° phase. In addition, high-resolution characterization of target geometries based on the cross correlation image processing technique is proposed and assessed using experimental data. It is shown that printed elements features with subwavelength size ~λ/15 or smaller can be characterized with at least 10-dB resolution contrast.

Thermal Properties of Polytetrafluoroethylene/ Sr2Ce2Ti5O16 Polymer/Ceramic Composites

Polytetrafluoroethylene (PTFE) composites filled with Sr2Ce2Ti5O16 ceramic were prepared by a powder processing technique. The structures and microstructures of the composites were investigated by X-ray diffraction and scanning electron microscopy techniques. Differential scanning calorimetry showed that the ceramic filler had no effect on the melting point of the PTFE. The effect of the Sr2Ce2Ti5O16 ceramic content [0–0.6 volume fraction (vf)] on the thermal conductivity, coefficient of thermal expansion (CTE), specific heat capacity, and thermal diffusivity were investigated. As the vf of the Sr2Ce2Ti5O16 ceramic increased, the thermal conductivity of the specimen increased, and the CTE decreased. The thermal conductivity and thermal expansion of the PTFE/Sr2Ce2Ti5O16 composites were improved to 1.7 W m21 8C21 and 34 ppm/8C, respectively for 0.6 vf of the ceramics. The experimental thermal conductivity and CTE were compared with different theoretical models.

Avaliação de Riscos : Estimação Qualitativa da Probabilidade e da Gravidade em Contexto de Risco Elevado

O processo de gestão de risco consiste, no estudo estruturado de todos os aspetos inerentes ao trabalho e é composto pela análise de risco, avaliação de risco e controlo de risco. Na análise de risco, é efetuada a identificação de todos os perigos presentes e a estimação da probabilidade e da gravidade, de acordo com o método de avaliação de risco escolhido. Este estudo centra-se na primeira etapa do processo de avaliação de risco, mais especificamente na análise de risco e nos marcadores de informação necessários para se efetuar a estimação de risco na industria extrativa a céu aberto (atividade de risco elevado). Considerando que o nível de risco obtido, depende fundamentalmente da estimação da probabilidade e da gravidade, ajustada a cada situação de risco, procurou-se identificar os marcadores e compreender a sua influência nos resultados da avaliação de risco (magnitude). O plano de trabalhos de investigação foi sustentado por uma metodologia qualitativa de recolha, registo e análise dos dados. Neste estudo, a recolha de informação foi feita com recurso às seguintes técnicas de investigação: - Observação estruturada e planeada do desmonte da rocha com recurso a explosivos; - Entrevista individual de formadores e gestores de risco (amostragem de casos típicos); Na análise e discussão qualitativa dos dados das entrevistas recorreu-se às seguintes técnicas: - Triangulação de analistas e tratamento de dados cognitiva (técnicas complementares); - Aposição dos marcadores de informação, versus, três métodos de avaliação de risco validados. Os resultados obtidos apontam no sentido das hipóteses de investigação formuladas, ou seja, o tipo de risco influi da seleção da informação e, existem diferenças significativas no nível de risco obtido, quando na estimação da probabilidade e da gravidade são utilizados marcadores de informação distintos.

A novel spectral representation of electromyographic signals

Time/frequency and temporal analyses have been widely used in biomedical signal processing. These methods represent important characteristics of a signal in both time and frequency domain. In this way, essential features of the signal can be viewed and analysed in order to understand or model the physiological system. Historically, Fourier spectral analyses have provided a general method for examining the global energy/frequency distributions. However, an assumption inherent to these methods is the stationarity of the signal. As a result, Fourier methods are not generally an appropriate approach in the investigation of signals with transient components. This work presents the application of a new signal processing technique, empirical mode decomposition and the Hilbert spectrum, in the analysis of electromyographic signals. The results show that this method may provide not only an increase in the spectral resolution but also an insight into the underlying process of the muscle contraction.

EMG signal filtering based on Empirical Mode Decomposition

This paper introduces a procedure for filtering electromyographic (EMG) signals. Its key element is the Empirical Mode Decomposition, a novel digital signal processing technique that can decompose my time-series into a set of functions designated as intrinsic mode functions. The procedure for EMG signal filtering is compared to a related approach based on the wavelet transform. Results obtained from the analysis of synthetic and experimental EMG signals show that Our method can be Successfully and easily applied in practice to attenuation of background activity in EMG signals. (c) 2006 Elsevier Ltd. All rights reserved.

Sub-surface terahertz imaging through uneven surfaces: visualizing Neolithic wall paintings in Çatalhöyük

Pulsed terahertz imaging is being developed as a technique to image obscured mural paintings. Due to significant advances in terahertz technology, portable systems are now capable of operating in unregulated environments and this has prompted their use on archaeological excavations. August 2011 saw the first use of pulsed terahertz imaging at the archaeological site of Çatalhöyük, Turkey, where mural paintings dating from the Neolithic period are continuously being uncovered by archaeologists. In these particular paintings the paint is applied onto an uneven surface, and then covered by an equally uneven surface. Traditional terahertz data analysis has proven unsuccessful at sub-surface imaging of these paintings due to the effect of these uneven surfaces. For the first time, an image processing technique is presented, based around Gaussian beam-mode coupling, which enables the visualization of the obscured painting.

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.

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.

Fingerprint Segmentation

In this thesis, a new algorithm has been proposed to segment the foreground of the fingerprint from the image under consideration. The algorithm uses three features, mean, variance and coherence. Based on these features, a rule system is built to help the algorithm to efficiently segment the image. In addition, the proposed algorithm combine split and merge with modified Otsu. Both enhancements techniques such as Gaussian filter and histogram equalization are applied to enhance and improve the quality of the image. Finally, a post processing technique is implemented to counter the undesirable effect in the segmented image. Fingerprint recognition system is one of the oldest recognition systems in biometrics techniques. Everyone have a unique and unchangeable fingerprint. Based on this uniqueness and distinctness, fingerprint identification has been used in many applications for a long period. A fingerprint image is a pattern which consists of two regions, foreground and background. The foreground contains all important information needed in the automatic fingerprint recognition systems. However, the background is a noisy region that contributes to the extraction of false minutiae in the system. To avoid the extraction of false minutiae, there are many steps which should be followed such as preprocessing and enhancement. One of these steps is the transformation of the fingerprint image from gray-scale image to black and white image. This transformation is called segmentation or binarization. The aim for fingerprint segmentation is to separate the foreground from the background. Due to the nature of fingerprint image, the segmentation becomes an important and challenging task. The proposed algorithm is applied on FVC2000 database. Manual examinations from human experts show that the proposed algorithm provides an efficient segmentation results. These improved results are demonstrating in diverse experiments.

Atenuação de ruídos coerentes utilizando decomposição em modos empíricos

The seismic processing technique has the main objective to provide adequate picture of geological structures from subsurface of sedimentary basins. Among the key steps of this process is the enhancement of seismic reflections by filtering unwanted signals, called seismic noise, the improvement of signals of interest and the application of imaging procedures. The seismic noise may appear random or coherent. This dissertation will present a technique to attenuate coherent noise, such as ground roll and multiple reflections, based on Empirical Mode Decomposition method. This method will be applied to decompose the seismic trace into Intrinsic Mode Functions. These functions have the properties of being symmetric, with local mean equals zero and the same number of zero-crossing and extremes. The developed technique was tested on synthetic and real data, and the results were considered encouraging

Electrical and Optical Properties of Conductive and Transparent ITO@PMMA Nanocomposites

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

Study of Densification Process and Microstructure for Highly Dense Doped MgB2 Bulk Samples

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

Apparent digestibility of different ingredients in diets for bullfrog Rana catesbeiana tadpoles

The objective of this study was to determine apparent digestibility of protein and energy of ingredients commonly present in rations fed to bullfrog tadpoles Rana catesbeiana such as corn, soybean meal, wheat meal, rice bran, poultry by-product meal, blood meal, fish meal, corn starch and soybean oil. A completely randomized design was used to test ten experimental diets with four replicates. About 30% of the reference diet was replaced by the test ingredients, except for soybean oil that was used at 10% ratio and 0.5% of chromium oxide as inert marker. The values of apparent digestibility coefficient of crude protein (ADCCP) and gross energy (ADCGE) of the protein ingredients were, respectively: fish meal, 81 and 95%; poultry byproduct meal, 82 and 87%; blood meal, 64 and 53%; and soybean meal, 93 and 90%. While for the energetic ingredients, ADCCP and ADCGE, were, respectively: wheat meal, 100 and 72%; rice bran, 57 and 24%; and corn, 84 and 92%. Soybean oil and cornstarch ADCGE values were 70 and 96%, respectively; cornstarch digestibility is highly dependent on feed processing technique. The results showed that the ing redients of plant origin, except for rice bran, had good digestibility, thus indicating that tadpoles can effectively use plant protein. In this trial, the least digestible ingredients were blood meal and rice bran, thus indicating that the use of such ingredients in bullfrog tadpole diets should be limited. © Copyright by the World Aquaculture Society 2005.

JSEG-based image segmentation in computer vision for agricultural mobile robot navigation

This project aims to apply image processing techniques in computer vision featuring an omnidirectional vision system to agricultural mobile robots (AMR) used for trajectory navigation problems, as well as localization matters. To carry through this task, computational methods based on the JSEG algorithm were used to provide the classification and the characterization of such problems, together with Artificial Neural Networks (ANN) for pattern recognition. Therefore, it was possible to run simulations and carry out analyses of the performance of JSEG image segmentation technique through Matlab/Octave platforms, along with the application of customized Back-propagation algorithm and statistical methods in a Simulink environment. Having the aforementioned procedures been done, it was practicable to classify and also characterize the HSV space color segments, not to mention allow the recognition of patterns in which reasonably accurate results were obtained.