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The research aims to design a system that cuts the cancerous area in the esophageal tissue that is often detected in late stages, using the FCM algorithm. This algorithm has achieved impressive results in determining the tumour area, which is; (sensitivity of 0.98, Accuracy of 0.95, and specificity of 0.92). The proposed system was tested on 200 images, which were downloaded from the Kaggle website. This research showed that is not possible to improve the images before using them in segmentation, due to the type of noise experienced by the data set is not uniform, because the images uploaded to the mentioned site are in JPG format (compressed images), which are losing many their features. [ABSTRACT FROM AUTHOR]

The paper examines the application of systematic and risk-based approaches to problem solving in the agro-industrial complex, which generally prompted research in the field of various model-based methodologies. Of particular interest to this study is the Quality by Design initiative in the agro-industrial complex. Motivated by their need, this paper reports some of the contributions to analysing the existence and availability of the experimental plan. The analysis of the feasibility and adaptation of the nested sampling algorithm for the probabilistic characteristics of the design space is considered. There is described an initial adaptation of the nested sampling algorithm, common for large Bayesian calculations, for the probabilistic characterization of spatial design, which is a key work for practitioners in the agro-industrial complex. The choice-based approach has been found to be effective with the optimization approach, allowing practitioners to take advantage of the choice-based approach with other methods. A step-by-step technology is given for complex and one-time implementations of the original nested sample for spatial design, which further reduces the computational load, thereby allowing solutions of more complex problems. Design-centring methodology is shown as an alternative coding method for methodological choice, providing the practitioner with a convenient format for communicating with process operators. A particular attention is paid to several pronounced problems that arise in the special design of experiments when there are various levels of model uncertainty, which are often encountered in the early stages of model development. The paper presents the results of the study obtained by developing optimal experimental queries in the presence of restrictions. [ABSTRACT FROM AUTHOR]

Motivated by problems in random continued fraction expansions, this research describes the design and implementation on θ-expansions of a real number, x in (0, θ) where 0 < θ < 1. Initially, for such a number θ, the convergent of θ-expansions is computed with comparison to the regular continued fraction (RCF)-convergent based on the samples of the approximated value, x. θ-expansions algorithm and continued fraction algorithm are applied in a Maple software to compute the θ-convergent and RCF-convergent. In this respect, the purpose of this research is to examine the growth rate of convergent for both expansions and provide the theoretical behaviours of θ-convergent in θ-expansions. Numerical results based on these samples show 3 conditions of convergence growth rate, which are C2 and C4 give the best decimal approximations in θ-expansions, whereas, Cn be the best approximations in RCF expansions. Therefore, this research reveals that various value of θ affect the performance on their growth rate of convergent for these two expansions. As θ approaching to 1, it reduces their convergence errors. The analysis of the experimental results reveals the RCF-convergent give a better performance compared to θ-convergent as its yield to less convergence errors. In addition, the value of convergent do converge to the approximated value, x and that is how the name of convergent comes. [ABSTRACT FROM AUTHOR]

To validate a model of guided wave propagation from acoustic emission on real aerospace structures a large amount of experimental data must be collected. It is desirable to take measurements over large areas at a small spacing between measurement points and this is very time consuming. To reduce the experimental effort, the HilomotDoE algorithm has been adapted to provide a black box method of selecting the data points to be collected. It chooses points which do not fit well to local hinging plane models. For example this includes the drop in amplitude of a guided wave as it crosses a stringer. The algorithm has been tested on a simulated structure and experimentally on a real structure. On the simulated structure, which had a relatively low feature density, using the algorithm reduces the number of data points required to 17.3% of the number of points in a full raster scan to reach a sufficiently good representation of the full raster scan. On the experimental structure, the algorithm did not reduce the number of points collected significantly and this was due to the much higher feature density in this structure. This highlights that the algorithm will only reduce the number of collection points required where appropriate. This algorithm has potential in reducing the number of data points collected in other NDT applications where measurement time is large and parts of the response are predictable. [ABSTRACT FROM AUTHOR]

Cryosurgery is a medical technique that uses a cryoprobe to apply extreme cold to undesirable tissue such as cancers. Precooled Mixed Gas Joule-Thomson (pMGJT) cycles with Hampson-style recuperators are integrated with the latest generation of cryoprobes to create more powerful and compact instruments. Selection of gas mixtures for these cycles is not a trivial process; the focus of this research is the development of a detailed model that can be integrated with an optimization algorithm to select optimal gas mixtures. A test facility has been constructed to experimentally tune and verify this model. The facility uses a commercially available cryoprobe system that was modified to integrate measurement instrumentation sufficient to determine the performance of the system and its component parts. Spatially resolved temperature measurements allow detailed measurements of the heat transfer within the recuperator and therefore computation of the spatially resolved conductance. These data can be used to study the multiphase, multicomponent heat transfer process in the complicated recuperator geometry. The optimization model has been expanded to model the pressure drop associated with the flow to more accurately predict the performance of the system. The test facility has been used to evaluate the accuracy and usefulness of this improvement. [ABSTRACT FROM AUTHOR]

The aircraft sheet metal part is the important component of aircraft structures and the rubber forming is one of the main forming method for aircraft sheet metal part, the prediction of initial blank sheet shape is a difficult problem for rubber forming. A fast prediction method for initial blank outline of rubber forming based on one-step inverse forming is proposed. Firstly, the designed sheet metal part is treated as the final configuration. Then the quick reverse simulation is carried out to obtain the initial blank outline by the one-step inverse analysis. Finally, the outline from the above method is applied into real rubber forming manufacture. The experimental results are well demonstrated that this method is an effective way to predict the initial blank shape for rubber forming process. [ABSTRACT FROM AUTHOR]

Optical coherence tomography (OCT) is a non-invasive low coherent interferometric technique that provides cross-sectional images of turbid media. OCT is based on the classical Michelson interferometer where the mirror of the reference arm is oscillating and the signal arm contains a biological sample. In this work, we analyzed theoretically the heterodyne optical signal adopting the so called extended Huygens-Fresnel principle (EHFP). We use simulated OCT images with known optical properties to test an algorithm developed by ourselves to recover the scattering coefficient and we recovered the scattering coefficient with a relative error less than 5% for noisy signals. In addition, we applied this algorithm to OCT images from phantoms of known optical properties; in this case curves were indistinguishable. A revision of the validity of the analytical model applied to our system should be done. [ABSTRACT FROM AUTHOR]

Based on the basic principles of group search optimizer (GSO) algorithm, an optimal algorithm, aimed at improving the efficiency of structural optimization, named quick group search optimizer (QGSO), is presented and successfully applied to the optimal design of a large double layer grid shell structure. The calculation result is compared with that of GSO algorithm and heuristic particle swarm optimizer (HPSO) algorithm. Three improvements, including increasing the number of ‘ranger’ when the target stops going forward, using the search strategy of particle swarm optimizer (PSO) by considering the best group member and the best personal member, employing the step search strategy to replace the visual search strategy, and reproducing the ‘ranger’ with hybrid of the best group member and the best personal member, were introduced. The results show that the QGSO has preferable convergence rate and accuracy. It is desired for QGSO to be used effectively for practical structural optimal design problems. [ABSTRACT FROM AUTHOR]

Polymer extrusion is one of the most important manufacturing methods used today. A flat die, is commonly used to extrude thin thermoplastics sheets. If the channel geometry in a flat die is not designed properly, the velocity at the die exit may be perturbed, which can affect the thickness across the width of the die. The ultimate goal of this work is to optimize the die channel geometry in a way that a uniform velocity distribution is obtained at the die exit. While optimizing the exit velocity distribution, we have coupled three-dimensional extrusion simulation software Rem3D®, with an automatic constraint optimization algorithm to control the maximum allowable pressure drop in the die; according to this constraint we can control the pressure in the die (decrease the pressure while minimizing the velocity dispersion across the die exit). For this purpose, we investigate the effect of the design variables in the objective and constraint function by using Taguchi method. In the second study we use the global response surface method with Kriging interpolation to optimize flat die geometry. Two optimization results are presented according to the imposed constraint on the pressure. The optimum is obtained with a very fast convergence (2 iterations). To respect the constraint while ensuring a homogeneous distribution of velocity, the results with a less severe constraint offers the best minimum. © 2007 American Institute of Physics [ABSTRACT FROM AUTHOR]

This paper describes an efficient method that integrates finite element analysis (FEA), mesh morphing and response surface based optimization in order to implement an automated and flexible software tool to optimize stamping tool and process design. For FEA, a robust and extremely fast inverse solver is chosen. For morphing, a state of the art mesh morpher that interactively generates shape variables for optimization studies is used. The optimization algorithm utilized in this study enables a global search for a multitude of parameters and is highly flexible with regards to the choice of objective functions. A quality function that minimizes formability defects resulting from stretching and compression is implemented. © 2004 American Institute of Physics [ABSTRACT FROM AUTHOR]

Getting the proper combination of different process parameters such as injection speed, melt temperature and mold temperature is important in getting a part that minimizes warpage and has the desired mechanical properties. Very often a successful design in injection molding comes at the end of a long trial and error process. Design Sensitivity Analysis (DSA) can help molders improve the design and can produce substantial investment savings in both time and money. This paper investigates the ability of the sensitivity analysis to drive an optimization tool in order to improve the quality of the injected part. The paper presents the solution of the filling stage of the injection molding process by a 3D finite element solution algorithm. The sensitivity of the solution with respect to different process parameters is computed using the continuous sensitivity equation method. Solutions are shown for the non-isothermal filling of a rectangular plate with a polymer melt behaving as a non-Newtonian fluid. The paper presents the equations for the sensitivity of the velocity, pressure and temperature and their solution by finite elements. Sensitivities of the solution with respect to the injection speed, the melt and mold temperatures are shown. © 2004 American Institute of Physics [ABSTRACT FROM AUTHOR]