Support vector regression for determining the minimum zone sphericity

Several methods have been investigated to determine the deviation of manufactured spherical parts from ideal geometry. One of the most popular is the least squares technique, which is still widely employed in coordinate measuring machines used by industries. The least squares algorithm is optimal under the assumption that the data set is very large and has the inherent disadvantage of overestimating the minimum tolerance zone, resulting sometimes in the rejection of good parts. In addition, it requires that the data be distributed normally. The support vector regression approach alleviates the necessity for these assumptions. While most fitting algorithms in practice today require that the sampled data accurately represent the surface being inspected, support vector regression provides a generalization over the surface. We describe how the concepts of support vector regression can be applied to the determination of tolerance zones of nonlinear surfaces; to demonstrate the unique potential of support vector machine algorithms in the area of coordinate metrology. In specific, we address part quality inspection of spherical geometries.     

A computational algorithm for minimizing total variation in imagerestoration

A reliable and efficient computational algorithm for restoring blurred and noisy images is proposed. The restoration process is based on the minimal total variation principle introduced by Rudin et al. For discrete images, the proposed algorithm minimizes a piecewise linear l (1) function (a measure of total variation) subject to a single 2-norm inequality constraint (a measure of data fit). The algorithm starts by finding a feasible point for the inequality constraint using a (partial) conjugate gradient method. This corresponds to a deblurring process. Noise and other artifacts are removed by a subsequent total variation minimization process. The use of the linear l(1) objective function for the total variation measurement leads to a simpler computational algorithm. Both the steepest descent and an affine scaling Newton method are considered to solve this constrained piecewise linear l(1) minimization problem. The resulting algorithm, when viewed as an image restoration and enhancement process, has the feature that it can be used in an adaptive/interactive manner in situations when knowledge of the noise variance is either unavailable or unreliable. Numerical examples are presented to demonstrate the effectiveness of the proposed iterative image restoration and enhancement process.     

Extraction of physical Schottky parameters using the Lambert function in Ni/AlGaN/GaN HEMT devices with defined conduction phenomena

Electrical characterization analyses are proposed in this work using the Lambert function on Schottky junctions in GaN wide band gap semiconductor devices for extraction of physical parameters. The Lambert function is used to give an explicit expression of the current in the Schottky junction. This function is applied with defined conduction phenomena, whereas other work presented arbitrary (or undefined) conduction mechanisms in such parameters'' extractions. Based upon AlGaN/GaN HEMT structures, extractions of parameters are undergone in order to provide physical characteristics. This work highlights a new expression of current with defined conduction phenomena in order to quantify the physical properties of Schottky contacts in AlGaN/GaN HEMT transistors.     

A modified sorting task to investigate consumer perceptions of extra virgin olive oils

A two-stage sorting task was used to probe Californian consumers’ opinions of twenty-five extra virgin olive oils based on visual assessments of the bottles. The modification of the simple sorting task aimed to encourage consumers to further discriminate products through sub-groupings of products within the groups they had already made. Sorting data were analyzed using a 3-way extension of classical multidimensional scaling called DISTATIS which explores the level of consumer agreement as well as the structure of the extra virgin olive oil products. Consumer agreements were explained by 46% of the variances found in the ways consumers sorted the bottles. Decreased amount of explained variance from the first stage to the second stage of the sorting task was observed in the olive oil product structures. Consumers were asked to describe the characteristics defining each group formed. Consumer comments were analyzed qualitatively prior to statistical analysis and were later used to understand the sorting results. Despite background differences in the usage of olive oil products, the majority of the consumers perceived the product set similarly. The two-stage sorting task allowed subjects to provide more criteria or multidimensional views of their perception of the products.     

Plug-load densities for energy analysis: K-12 schools

Benchmarking plug-load densities is essential to bypass arbitrary and/or incorrect inputs used in building energy analysis. As more building simulationists play a decision-making role for the design team, they tend to lean on building energy standards and guidelines for preliminary inputs such as plug-load densities. It is necessary for building energy standards and rating systems to implement plug-load density benchmarks to reward design teams in their efforts to reduce plug-load energy use. Using case study buildings, this paper establishes benchmark plug-load densities for K-12 schools under two new categories – classrooms with computers and classrooms without computers. Eighteen K-12 schools including 9 elementary, 2 middle, and 7 high schools are assessed for actual plug-load densities. For the same case study buildings, four existing approaches – NREL, COMNET, ASHRAE 90.1-1989, and Title-24 are evaluated for plug-load densities. Results show under- and over-estimation of plug-load densities over actual densities. The development of benchmark for K-12 schools will pave way for instituting targets for trimming plug-load densities in new and retrofit building projects.     

Influence of alumina nanoparticles additives into biofuel (water hyacinth)-diesel mixture on diesel engine performance and emissions

The using diesel and biodiesel blends as a fuel has been a recent field of study especially with nanoparticles additives. The addition of alumina nanoparticles to biodiesel was verified to reduce emissions, while engine performance was not given great attention to evaluate the effect of blending alumina nanoparticles with the diesel and biodiesel mixture on the performance characteristics of the diesel engine. Then performance and emission tests were carried out by using different fuel samples in a single cylinder diesel engine. The brake thermal efficiency for the alumina nanoparticles (50 ppm, 100 ppm) and biodiesel blends were lower than that of biofuel (D80B20) blends, it was decreased by 2.5 %, 6.05 % respectively as compared to the blend (D80B20). The rate of carbon monoxide emissions for the two biodiesel and alumina blends were lower than that of the biodiesel blend (D80B20) and the best reduction was for the blend (D80B20N50) and was 76.3 % as compared with the biodiesel blend (D80B20). Also, the nitrogen oxides emissions for all the blends with nanoparticles were lower than that of the blend D80B20 due to shortened ignition delay and less fuel was added during the combustion which lead to reduction in nitrogen oxides emissions.     

Bending collapse of thin-walled beams with ultralight filler: numerical simulation and weight optimization

Summary A study on the bending collapse of thin-walled beams filled with aluminum foam or aluminum honeycomb was carried out. The strengthening effects of ultralight metal fillers were quantified numerically and experimentally. The moment-rotation characteristics of filled sections were derived, and the results were then incorporated with structural optimization technique to develop a methodology for crashworthiness optimization of filled members. The proposed methodology requires relatively simple computations and is suitable for early stage design of crash members. Finally, the optimization problem of filled sections under combined compression/bending loading was formulated and solved. The optimization results showed potentials of significant weight saving and volume reduction by utilizing ultralight metal filler.