Candidate working set strategy based SMO algorithm in support vector machine

Sequential minimal optimization (SMO) is quite an efficient algorithm for training the support vector machine. The most important step of this algorithm is the selection of the working set, which greatly affects the training speed. The feasible direction strategy for the working set selection can decrease the objective function, however, may augment to the total calculation for selecting the working set in each of the iteration. In this paper, a new candidate working set (CWS) Strategy is presented considering the cost on the working set selection and cache performance. This new strategy can select several greatest violating samples from Cache as the iterative working sets for the next several optimizing steps, which can improve the efficiency of the kernel cache usage and reduce the computational cost related to the working set selection. The results of the theory analysis and experiments demonstrate that the proposed method can reduce the training time, especially on the large-scale datasets.

Inferring minimal feasible metabolic networks of Escherichia coli

Since the organism contains many redundant reactions, the minimal feasible metabolic network that contains the basic growth function is not the collection of reactions that associate the essential genes. To identify minimal metabolic reaction set is a challenging work in theoretical approach. A new method is presented here to identify the smallest required reaction set of growth-sustaining metabolic networks. The content and number of the minimal reactions for growth are variable in different random processes. Though the different carbon sources also vary the content of the reactions in the minimal metabolic networks, most essential reactions locate in the same metabolic subsystems, such as cofactor and prosthetic group biosynthesis, cell envelope biosynthesis, and membrane lipid metabolism.

The association between the investment opportunity set and corporate financing and dividend decisions: some Australian evidence

Summarizes previous research on the investment opportunity set (IOS) using price-based and investment-based proxies and variance measures; and develops hypotheses on the relationship between IOS, debt/equity ratios and dividend policies. Tests them on 1990-1998 data from listed Australian companies and explains the methodology, which builds on Gover and Gover (1993) by including more recent proxy variables. Finds no significant results from low growth firms, although some high growth firms show lower debt/equity ratios and dividends. Questions the robustness of existing IOS proxies in the Australian context and calls for further research.

Selected Ranked Set Sampling

This paper proposes a sampling procedure called selected ranked set sampling (SRSS), in which only selected observations from a ranked set sample (RSS) are measured. This paper describes the optimal linear estimation of location and scale parameters based on SRSS, and for some distributions it presents the required tables for optimal selections. For these distributions, the optimal SRSS estimators are compared with the other popular simple random sample (SRS) and RSS estimators. In every situation the estimators based on SRSS are found advantageous at least in some respect, compared to those obtained from SRS or RSS. The SRSS method with errors in ranking is also described. The relative precision of the estimator of the population mean is investigated for different degrees of correlations between the actual and erroneous ranking. The paper reports the minimum value of the correlation coefficient between the actual and the erroneous ranking required for achieving better precision with respect to the usual SRS estimator and with respect to the RSS estimator.

Sensory adaptability of foods with added Lupin (Lupinus angustifolius) kernel fibre using pre-set criteria

Fiber-enriched white bread, muffin. pasta, orange juice, and breakfast bar were prepared with lupin (Lupin us angusti/olius) kernel fiber. Consumer panelists (n = 44) determined that all these fiber-enriched foods, except orange juice, fulfilled pre-set acceptability criteria. Fiber enrichment did not change overall acceptability (p> 0.05) of the bread and pasta, but reduced overall acceptability (p < 0.05) of the muffin, orange juice, and breakfast bar. In all fiber-enriched products, flavor was the attribute most highly correlated with overall acceptability (p < 0.05). The lupin kernel fiber used in this study therefore appears to have potential as a 'nonintrusive' ingredient in some processed cereal-based foods_ For other applications, fiber modification appears worthy of investigation to accomplish 'nonintrusive' fiber enrichment.

The influence of object-image velocity change on perceived heading in minimal environments

When human observers move forward and rotate their eyes, a complex pattern of light flows across the retina. This pattern is referred to as retinal flow. A model has been proposed to explain how humans perceive their direction of self-movement (or heading) from (1) static depth, (2) direction of image motion, and (3) whether image velocity undergoes acceleration or deceleration (Wang & Cutting, 1999). However, findings from past research in which sparse or minimalist stimuli were used have suggested that not all of the information to which participants are sensitive is captured within the scope of this model. In particular it has been suggested that the magnitude or size of image velocity change may be of significance beyond simply whether image velocity could be categorized as speeding up (i.e., accelerating) or slowing down (i.e., decelerating). In two experiments, the influence of this factor on heading judgments under minimal conditions was investigated. Evidence was found in support of the idea that the rate of image velocity change can influence judgments of the direction of self-movement in minimalist conditions.

A comparative study of some computer algebra packages which determine the lie point symmetries of differential equations

The study seeks to determine which of five computer algebra packages is best at finding the Lie point symmetries of systems of partial differential equations with minimal user intervention. The chosen packages are LIEPDE and DIMSYM for REDUCE, LIE and BIGLIE for MUMATH, DESOLV for MAPLE, and MATHLIE for MATHEMATICA. A series of systems of partial differential equations are used in the study. The paper concludes that while all of the computer packages are useful, DESOLV appears to be the most successful system at determining the complete set of Lie point symmetries of systems of partial differential equations.

Using geometric shape variations to create an inverse model for a sheet metal process

The output of the sheet metal forming process is subject to much variation. This paper develops a method to measure shape variation in channel forming and relate this back to the corresponding process parameter levels of the manufacturing set-up to create an inverse model. The shape variation in the channels is measured using a modified form of the point distribution model (also known as the active shape model). This means that channels can be represented by a weighting vector of minimal linear dimension that contains all the shape variation information from the average formed channel.

The inverse models were created using classifiers that related the weighting vectors to the process parameter levels for the blank holder force (BHF), die radii (DR) and tool gap (TG) of the parameters. Several classifiers were tested: linear, quadratic Gaussian and artificial neural networks. The quadratic Gaussian classifiers were the most accurate and the most consistent type of classifier over all the parameters.

The determination of all syzygies for the dependent polynomial invariants of the Riemann Tensor. II. mixed invariants of Eeven degree in the Ricci Spinor

We continue our analysis of the polynomial invariants of the Riemann tensor in a four-dimensional Lorentzian space. We concentrate on the mixed invariants of even degree in the Ricci spinor Φ_ABȦḂ and show how, using constructive graph-theoretic methods, arbitrary scalar contractions between copies of the Weyl spinor ψ_ABCD, its conjugate ψ_ȦḂĊḊ and an even number of Ricci spinors can be expressed in terms of paired contractions between these spinors. This leads to an algorithm for the explicit expression of dependent invariants as polynomials of members of the complete set. Finally, we rigorously prove that the complete set as given by Sneddon [J. Math. Phys. 39, 1659-1679 (1998)] for this case is both complete and minimal.

A set of patterns for the web-based interfaces of an employee services system

The provision of Human Resource (HR), especially payroll, is a core function in every organization. Previously, providers of HR/payroll have offered their services to their clients via conventional modes of communication, such as telephones, facsimile, and courier services. In recent years, with the advent of the Internet and the emergence of web-based electronic commerce, there has been a rise in the adoption of web-based technology and information
systems by service providers, thereby enabling them to interact with their clients through this medium. This development necessitates the use of web-based user interfaces as workspaces between the HR/payroll providers and their clients, and thus, raises certain concerns that determine the effectiveness of web-based workflow systems. These concerns, related to the use of web interfaces, form the basis of the patterns discussed in this paper

An email classification model based on rough set theory

The communication via email is one of the most popular services of the Internet. Emails have brought us great convenience in our daily work and life. However, unsolicited messages or spam, flood our email boxes, which results in bandwidth, time and money wasting. To this end, this paper presents a rough set based model to classify emails into three categories - spam, no-spam and suspicious, rather than two classes (spam and non-spam) in most currently used approaches. By comparing with popular classification methods like Naive Bayes classification, the error ratio that a non-spam is discriminated to spam can be reduced using our proposed model.

Investigation of processing conditions of melded parts to determine process boundaries

Melding, a novel method for producing seamless joints in thermosetting composites utilising the Quickstep™ process, is explored in this paper. The effect of processing conditions on the quality of melded joins is examined and a set of processing boundaries defined so that the strength of melded joints is optimized. HexPly® 914c pre-preg material was exposed to a range of processing temperatures prior to joining via the melding process. Differential Scanning Calorimetry analysis was carried out to investigate the degree of cure of material prior to final joining, and it was found that minimal cure occurs at temperatures below 120°C. After consolidation and cure of the melded parts, short beam shear testing was conducted to evaluate the strength of the melded interface. Exposure temperatures between 65°C and 120°C were found to optimize short beam shear join strength. Mode I double cantilever beam and mode II end notched flexural tests showed no detrimental effect of elevated exposure temperatures prior to joining.