The Effect of Coating Patterns with Spinel-Based Investment on the Castability and Porosity of Titanium Cast into Three Phosphate-Bonded Investments

Purpose: This study evaluated the effect of pattern coating with spinel-based investment Rematitan Ultra (RU) on the castability and internal porosity of commercially pure (CP) titanium invested into phosphate-bonded investments. The apparent porosity of the investment was also measured. Materials and Methods: Square patterns (15 x 15 x 0.3 mm(3)) were either coated with RU, or not and invested into the phosphate-bonded investments: Rematitan Plus (RP), Rema Exakt (RE), Castorit Super C (CA), and RU (control group). The castings were made in an Ar-arc vacuum-pressure machine. The castability area (mm(2)) was measured by an image-analysis system (n = 10). For internal porosity, the casting (12 x 12 x 2 mm(3)) was studied by the X-ray method, and the projected porous area percentage was measured by an image-analysis system (n = 10). The apparent porosity of the investment (n = 10) was measured in accordance with the ASTM C373-88 standard. Results: Analysis of variance (One-way ANOVA) of castability was significant, and the Tukey test indicated that RU had the highest mean but the investing technique with coating increased the castability for all phosphate-bonded investments. The analysis of the internal porosity of the cast by the nonparametric test demonstrated that the RP, RE, and CA with coating and RP without coating did not differ from the control group (RU), while the CA and RE casts without coating were more porous. The one-way ANOVA of apparent porosity of the investment was significant, and the Tukey test showed that the means of RU (36.10%) and CA (37.22%) were higher than those of RP (25.91%) and RE (26.02%). Conclusion: Pattern coating with spinel-based material prior to phosphate-bonded investments can influence the castability and the internal porosity of CP Ti.

Classification of breast masses using a committee machine of artificial neural networks

This work proposes a new approach using a committee machine of artificial neural networks to classify masses found in mammograms as benign or malignant. Three shape factors, three edge-sharpness measures, and 14 texture measures are used for the classification of 20 regions of interest (ROIs) related to malignant tumors and 37 ROIs related to benign masses. A group of multilayer perceptrons (MLPs) is employed as a committee machine of neural network classifiers. The classification results are reached by combining the responses of the individual classifiers. Experiments involving changes in the learning algorithm of the committee machine are conducted. The classification accuracy is evaluated using the area A. under the receiver operating characteristics (ROC) curve. The A, result for the committee machine is compared with the A, results obtained using MLPs and single-layer perceptrons (SLPs), as well as a linear discriminant analysis (LDA) classifier Tests are carried out using the student's t-distribution. The committee machine classifier outperforms the MLP SLP, and LDA classifiers in the following cases: with the shape measure of spiculation index, the A, values of the four methods are, in order 0.93, 0.84, 0.75, and 0.76; and with the edge-sharpness measure of acutance, the values are 0.79, 0.70, 0.69, and 0.74. Although the features with which improvement is obtained with the committee machines are not the same as those that provided the maximal value of A(z) (A(z) = 0.99 with some shape features, with or without the committee machine), they correspond to features that are not critically dependent on the accuracy of the boundaries of the masses, which is an important result. (c) 2008 SPIE and IS&T.

Thermal error evaluation and modelling of a CNC cylindrical grinding machine

With the relentless quest for improved performance driving ever tighter tolerances for manufacturing, machine tools are sometimes unable to meet the desired requirements. One option to improve the tolerances of machine tools is to compensate for their errors. Among all possible sources of machine tool error, thermally induced errors are, in general for newer machines, the most important. The present work demonstrates the evaluation and modelling of the behaviour of the thermal errors of a CNC cylindrical grinding machine during its warm-up period.

Abrasion and corrosion resistance of new Ni-based coating deposited by HVOF thermal spray process

Coatings based on NiCrAlC intermetallic based alloy were applied on AISI 316L stainless steel substrates using a high velocity oxygen fuel torch. The influence of the spray parameters on friction and abrasive wear resistance were investigated using an instrumented rubber wheel abrasion test, able to measure the friction forces. The corrosion behaviour of the coatings were studied with electrochemical techniques and compared with the corrosion resistance of the substrate material. Specimens prepared using lower O(2)/C(3)H(8) ratios showed smaller porosity values. The abrasion wear rate of the NiCrAlC coatings was much smaller than that described in the literature for bulk as cast materials with similar composition and one order of magnitude higher than bulk cast and heat treated (aged) NiCrAlC alloy. All coatings showed higher corrosion resistance than the AISI 316L substrate in HCl (5%) aqueous solution at 40 degrees C.

Hygroexpansivity profiles on a commercial paper machine

Paper products show dimensional changes when subjected to moisture content modification. Hygroexpansivity was investigated in a commercial paper machine operating at 1256 m/min by a set of measurements on 75 g/m(2) reprographic bleached eucalyptus pulp paper samples. The present work shows hygroexpansivity development in different sections of the paper machine along the manufacturing direction. The measurement results demonstrate the effects of papermaking process operations on paper hygroexpansivity and lead to the confirmation of fiber orientation degree, drying restraint and shrinkage and paper tension as significant influencing factors. Structural, strength and elastic properties of paper were also measured as a function of machine direction position and presented for discussion purposes.

Scheduling in a two-machine flowshop for the minimization of the mean absolute deviation from a common due date

This paper addresses the minimization of the mean absolute deviation from a common due date in a two-machine flowshop scheduling problem. We present heuristics that use an algorithm, based on proposed properties, which obtains an optimal schedule fora given job sequence. A new set of benchmark problems is presented with the purpose of evaluating the heuristics. Computational experiments show that the developed heuristics outperform results found in the literature for problems up to 500 jobs. (C) 2007 Elsevier Ltd. All rights reserved.

Minimizing total tardiness in a stochastic single machine scheduling problem using approximate dynamic programming

This paper addresses the non-preemptive single machine scheduling problem to minimize total tardiness. We are interested in the online version of this problem, where orders arrive at the system at random times. Jobs have to be scheduled without knowledge of what jobs will come afterwards. The processing times and the due dates become known when the order is placed. The order release date occurs only at the beginning of periodic intervals. A customized approximate dynamic programming method is introduced for this problem. The authors also present numerical experiments that assess the reliability of the new approach and show that it performs better than a myopic policy.

Improved moisture and hydrocarbons barrier of epoxy resin-based coating

To improve the surface characteristics of epoxy resin coatings, a treatment by fluorine-containing plasma was used to develop a coating with low surface free energy and improved chemical resistance. Through the coating analysis it was possible to verify information about the CF(n) bond formation and the fluorination depth. The best plasma process parameters presented the best fluorination depth, 90 nm, and fluorine concentration was nearly 30%. The improvement in contact angle of water was 50% and of raw petroleum was 130%. Salt spray test proves that the coating fluorination decreases the chance of substrate corrosion.

The single machine earliness and tardiness scheduling problem: lower bounds and a branch-and-bound algorithm

This paper addresses the single machine scheduling problem with a common due date aiming to minimize earliness and tardiness penalties. Due to its complexity, most of the previous studies in the literature deal with this problem using heuristics and metaheuristics approaches. With the intention of contributing to the study of this problem, a branch-and-bound algorithm is proposed. Lower bounds and pruning rules that exploit properties of the problem are introduced. The proposed approach is examined through a computational comparative study with 280 problems involving different due date scenarios. In addition, the values of optimal solutions for small problems from a known benchmark are provided.

Evaluation of Automotive Varnish as a Coating for Density Measurements of Soil Clods

Saran F-310 resin (Dow Chemical Co, Midland, MI) has been widely used to coat soil clods for density and size measurements; however, the manufacturer has recently stopped producing this resin and supplies are difficult to obtain. Hence, we evaluated the feasibility of using Lazzudur 7502 (Sherwin-Williams, Cleveland, OH) automotive varnish to coat soil clods for density measurement. Preliminary evaluations showed that immersion of clods in the varnish did nor affect clod cohesion and that a single immersion in Lazzudur with 30 min of post-immersion drying produced density results nor significantly (P < 0.05) different to those obtained using saran. This technique was tested across seven soils and no significant (P < 0.05) difference was found in the density of the clods measured using the two coating methods. This work suggests that automotive varnish can he used as an alternative to saran resin for clod density measurements.

Effect of process variables on fluiddynamics and adhesion efficiency during spouted bed coating of hard gelatine capsules

This article presents an evaluation of the effects of the spouted bed design and operating conditions on system fluiddynamics and process performance during enteric coating of hard gelatine capsules. The design parameters studied were the column diameter (150 mm and 200 mm), the included angle of the conical base, gamma (60 degrees or 40 degrees) and the presence or absence of a Venturi inserted before the inlet air orifice. The process variables studied were the ratio between the feed flow rate of the coating suspension to the spouting gas flow rate (W(s)/W(g)), the mass of capsules loaded to the equipment (M(0)), and the ratio between the Spouting gas flow rate to the gas flow rate at minimum spouting condition (Q/Q(ms)). The response variables were the rate of increase of the capsules mass (K(1)), and the adhesion efficiency (eta). The linear regression equation for the dependent variable K, in terms of the independent variables adequately described the process with an r(2) value of 0.872. Analysis of variance (ANOVA) revealed that increasing of W(s)/W(g), Q/Q(ms) and gamma significantly increased the adhesion efficiency. Adhesion efficiencies higher than 90% were achieved by selecting precise coating conditions, indicating the feasibility of the process for coating of hard gelatine capsules. (C) 2008 Elsevier B.V. All rights reserved.

Improving Alzheimer`s Disease Diagnosis with Machine Learning Techniques

There is not a specific test to diagnose Alzheimer`s disease (AD). Its diagnosis should be based upon clinical history, neuropsychological and laboratory tests, neuroimaging and electroencephalography (EEG). Therefore, new approaches are necessary to enable earlier and more accurate diagnosis and to follow treatment results. In this study we used a Machine Learning (ML) technique, named Support Vector Machine (SVM), to search patterns in EEG epochs to differentiate AD patients from controls. As a result, we developed a quantitative EEG (qEEG) processing method for automatic differentiation of patients with AD from normal individuals, as a complement to the diagnosis of probable dementia. We studied EEGs from 19 normal subjects (14 females/5 males, mean age 71.6 years) and 16 probable mild to moderate symptoms AD patients (14 females/2 males, mean age 73.4 years. The results obtained from analysis of EEG epochs were accuracy 79.9% and sensitivity 83.2%. The analysis considering the diagnosis of each individual patient reached 87.0% accuracy and 91.7% sensitivity.

Histological analysis of cobalt-chromium stents with and without Camouflage (R) polymer coating: experimental porcine carotid artery model

This study evaluated the arterial response to cobalt-chromium stents with and without polymer coating (Camouflage (R), Hemoteq AG, Wuerselen, Germany) implanted in pigs. Cobalt-chromium balloon-expandable stents (4 x 16 mm) were implanted in the common carotid arteries of nine pigs. Histological analysis of endothelialization, inflammation and injury was performed one month later. All stents were successfully deployed, and all but one animal survived the 30 study days. All arteries were patent. Endothelialization was nearly complete in most sections of all carotid stents in both groups. There were mild inflammatory infiltrate and mild-to-moderate injury, which were associated with the stent shafts and not significantly different between groups. Our findings suggest that, in porcine carotid arteries, the histological response to balloon-expandable cobalt-chromium stents coated with polymer (Camouflage (R), Hemoteq AG) is similar to the response to non-coated cobalt-chromium stents.

Comparing machine learning classifiers in potential distribution modelling

Species` potential distribution modelling consists of building a representation of the fundamental ecological requirements of a species from biotic and abiotic conditions where the species is known to occur. Such models can be valuable tools to understand the biogeography of species and to support the prediction of its presence/absence considering a particular environment scenario. This paper investigates the use of different supervised machine learning techniques to model the potential distribution of 35 plant species from Latin America. Each technique was able to extract a different representation of the relations between the environmental conditions and the distribution profile of the species. The experimental results highlight the good performance of random trees classifiers, indicating this particular technique as a promising candidate for modelling species` potential distribution. (C) 2010 Elsevier Ltd. All rights reserved.

Numerical simulation of the liquid phase in SnO(2) thin film deposition by sol-gel-dip-coating

The fluid flow of the liquid phase in the sol-gel-dip-coating process for SnO(2) thin film deposition is numerically simulated. This calculation yields useful information on the velocity distribution close to the substrate, where the film is deposited. The fluid modeling is done by assuming Newtonian behavior, since the linear relation between shear stress and velocity gradient is observed. Besides, very low viscosities are used. The fluid governing equations are the Navier-Stokes in the two dimensional form, discretized by the finite difference technique. Results of optical transmittance and X-ray diffraction on films obtained from colloidal suspensions with regular viscosity, confirm the substrate base as the thickest part of the film, as inferred from the numerical simulation. In addition, as the viscosity increases, the fluid acquires more uniform velocity distribution close to the substrate, leading to more homogenous and uniform films.