Multi-criteria material selection in engineering design

Almost all material selection problems require that a compromise be sought between some metric of performance and cost. Trade-off methods using utility functions allow optimal solutions to be found for two objective, but for three it is harder. This paper develops and demonstrates a method for dealing with three objectives.

Morphometric studies in Penaeus merguiensis from Ratnagiri waters for selection of the brood stock in genetic improvement programmes

Studies on genetic improvement of penaeid prawns for the character higher tail weight using methods of selective breeding were undertaken. Prior to the actual breeding experiments it was necessary to find out the quantum of available variability in the character tail weight amongst the natural populations of Penaeus merguiensis from the Indian waters. Thirteen morphometric variables were measured and various statistical analyses were carried out. The tail weight showed almost double values of coefficient of variation in the females than the males (C.V. 20.37 and 11.08 respectively). The combination of the characters viz. sixth segment length (SSL), sixth segment depth (SSD) and posterior abdominal circumference (PAC) gave the highest R super(2) values. These variables were easy to measure and gave maximum variation in the character tail weight without sacrificing the breeders in the brood stock. The quantitative character tail weight was influenced by both genetic and environmental factors was statistically ascertained by applying 2-Factor analysis.

Materials selection in mechanical design

A novel materials-selection procedure has been developed and implemented in software. The procedure makes use of Materials Selection Charts: a new way of displaying material property data; and performance indices: combinations of material properties which govern performance. Optimization methods are employed for simultaneous selection of both material and shape.

Face-based Selection of Corners in 3D Substructuring

In most recent substructuring methods, a fundamental role is played by the coarse space. For some of these methods (e.g. BDDC and FETI-DP), its definition relies on a 'minimal' set of coarse nodes (sometimes called corners) which assures invertibility of local subdomain problems and also of the global coarse problem. This basic set is typically enhanced by enforcing continuity of functions at some generalized degrees of freedom, such as average values on edges or faces of subdomains. We revisit existing algorithms for selection of corners. The main contribution of this paper consists of proposing a new heuristic algorithm for this purpose. Considering faces as the basic building blocks of the interface, inherent parallelism, and better robustness with respect to disconnected subdomains are among features of the new technique. The advantages of the presented algorithm in comparison to some earlier approaches are demonstrated on three engineering problems of structural analysis solved by the BDDC method.

Comparison of Camera Motion Estimation Methods for 3D Reconstruction of Infrastructure

Camera motion estimation is one of the most significant steps for structure-from-motion (SFM) with a monocular camera. The normalized 8-point, the 7-point, and the 5-point algorithms are normally adopted to perform the estimation, each of which has distinct performance characteristics. Given unique needs and challenges associated to civil infrastructure SFM scenarios, selection of the proper algorithm directly impacts the structure reconstruction results. In this paper, a comparison study of the aforementioned algorithms is conducted to identify the most suitable algorithm, in terms of accuracy and reliability, for reconstructing civil infrastructure. The free variables tested are baseline, depth, and motion. A concrete girder bridge was selected as the "test-bed" to reconstruct using an off-the-shelf camera capturing imagery from all possible positions that maximally the bridge's features and geometry. The feature points in the images were extracted and matched via the SURF descriptor. Finally, camera motions are estimated based on the corresponding image points by applying the aforementioned algorithms, and the results evaluated.

Optimized selection of key frames for monocular videogrammetric surveying of civil infrastructure

Videogrammetry is an inexpensive and easy-to-use technology for spatial 3D scene recovery. When applied to large scale civil infrastructure scenes, only a small percentage of the collected video frames are required to achieve robust results. However, choosing the right frames requires careful consideration. Videotaping a built infrastructure scene results in large video files filled with blurry, noisy, or redundant frames. This is due to frame rate to camera speed ratios that are often higher than necessary; camera and lens imperfections and limitations that result in imaging noise; and occasional jerky motions of the camera that result in motion blur; all of which can significantly affect the performance of the videogrammetric pipeline. To tackle these issues, this paper proposes a novel method for automating the selection of an optimized number of informative, high quality frames. According to this method, as the first step, blurred frames are removed using the thresholds determined based on a minimum level of frame quality required to obtain robust results. Then, an optimum number of key frames are selected from the remaining frames using the selection criteria devised by the authors. Experimental results show that the proposed method outperforms existing methods in terms of improved 3D reconstruction results, while maintaining the optimum number of extracted frames needed to generate high quality 3D point clouds.© 2012 Elsevier Ltd. All rights reserved.

A critical analysis of loudness calculation methods

The physical meaning and methods of determining loudness were reviewed Loudness is a psychoacoustic metric which closely corresponds to the perceived intensity of a sound stimulus. It can be determined by graphical procedures, numerical methods, or by commercial software. These methods typically require the consideration of the 1/3 octave band spectrum of the sound of interest. The sounds considered in this paper are a 1 kHz tone and pink noise. The loudness of these sounds was calculated in eight ways using different combinations of input data and calculation methods. All the methods considered are based on Zwicker loudness. It was determined that, of the combinations considered, only the commercial software dBSonic and the loudness calculation procedure detailed in DIN 45631 using 1/3 octave band levels filtered using ANSI S1.11-1986 gave the correct values of loudness for a 1 kHz tone. Comparing the results between the sources also demonstrated the difference between sound pressure level and loudness. It was apparent that the calculation and filtering methods must be considered together, as a given calculation will produce different results for different 1/3 octave band input. In the literature reviewed, no reference provided a guide to the selection of the type of filtering that should be used in conjunction with the loudness computation method.

Retention of the developmental pluripotency in medaka embryonic stem cells after gene transfer and long-term drug selection for gene targeting in fish

Embryonic stem (ES) cells provide a unique tool for introducing random or targeted genetic alterations, because it is possible that the desired, but extremely rare recombinant genotypes can be screened by drug selection. ES cell-mediated transgenesis has so far been limited to the mouse. In the fish medaka (Oryzias latipes) several ES cell lines have been made available. Here we report the optimized conditions for gene transfer and drug selection in the medaka ES cell line MES1 as a prelude for gene targeting in fish. MES1 cells gave rise to a moderate to high transfection efficiency by the calcium phosphate co-precipitation (5%), commercial reagents Fugene (11%), GeneJuice (21%) and electroporation (>30%). Transient gene transfer and CAT reporter assay revealed that several enhancers/promoters and their combinations including CMV, RSV and ST (the SV40 virus early gene enhancer linked to the thymidine kinase promoter) were suitable regulatory sequences to drive transgene expression in the MES1 cells. We show that neo, hyg or pac conferred resistance to G418, hygromycin or puromycin for positive selection, while the HSV-tk generated sensitivity to ganciclovir for negative selection. The positive-negative selection procedure that is widely used for gene targeting in mouse ES cells was found to be effective also in MES1 cells. Importantly, we demonstrate that MES1 cells after gene transfer and long-term drug selection retained the developmental pluripotency, as they were able to undergo induced differentiation in vitro and to contribute to various tissues and organs during chimeric embryogenesis.

Variable selection by orthogonal descriptors and prediction of R-f value of phenol and aniline derivatives

Orthogonal descriptors is a viable method for variable selection, but this method strongly depend on the orthogonalisation ordering of the descriptors. In this paper, we compared the different methods used for order the descriptors. It showed that better results could be achieved with the use of backward elimination ordering. We predicted R-f value of phenol and aniline derivatives by this method, and compared it with classical algorithms such as forward selection, backward elimination, and stepwise procedure. Some interesting hints were obtained.

Model Selection Methodology in Supervised Learning with Evolutionary Computation

Rowland, J.J. (2003) Model Selection Methodology in Supervised Learning with Evolutionary Computation. BioSystems 72, 1-2, pp 187-196, Nov

Generalisation and Model Selection in Supervised Learning with Evolutionary Computation

Rowland, J. J. (2003) Generalisation and Model Selection in Supervised Learning with Evolutionary Computation. European Workshop on Evolutionary Computation in Bioinformatics: EvoBio 2003. Lecture Notes in Computer Science (Springer), Vol 2611, pp 119-130

Fuzzy-Rough Sets Assisted Attribute Selection

R. Jensen and Q. Shen. Fuzzy-Rough Sets Assisted Attribute Selection. IEEE Transactions on Fuzzy Systems, vol. 15, no. 1, pp. 73-89, 2007.

Rough set feature selection and rule induction for prediction of malignancy degree in brain glioma

X. Wang, J. Yang, R. Jensen and X. Liu, 'Rough Set Feature Selection and Rule Induction for Prediction of Malignancy Degree in Brain Glioma,' Computer Methods and Programs in Biomedicine, vol. 83, no. 2, pp. 147-156, 2006.