Behavior of square concrete columns reinforced with Prefabricated Cage System

Behavior of normal strength concrete columns reinforced with a new reinforcement, termed Prefabricated Cage System (PCS) is investigated. A total of 16 small-scale PCS and rebar reinforced column specimens were constructed and tested under monotonic axial displacement. The experimental results indicate that the overall behavior of rebar and PCS reinforced specimens are comparable prior to achieving the peak column load. In general, PCS specimens are more ductile and absorb more energy than similar rebar specimens after the peak load is reached. The effect of different parameters, such as the steel tube thickness, number of longitudinal reinforcements, transverse steel spacing, and crossties on the specimens’ strength and deformation capacity are investigated. A confined concrete model is proposed and used to predict the load–displacement response. The theoretical load–displacement relations obtained from the proposed model are compared with those obtained from the Mander et al. (J Struct Eng 114(8):1804–1826, 1988) confinement model.     

Optimization of abrasive water jet cutting of ductile materials

Full factorial design of experiments was developed in order to investigate the effects of jet pressure, abrasive mixing rate, cutting feed, and plate thickness upon three response variables, surface finish of cutting wear zone, percentage proportion of striation free area, and maximum width of cut. The set of sixteen experiments was performed on each of the following two ductile materials: AISI 4340 (high strength low alloy steel, hardened to 49HRc) and Aluminum 2219. Analysis of Variance (ANOVA) was performed on experimental data in order to determine the significance of effects of different parameters on the performance measures. It was found that cutting feed and thickness were highly influential parameters, while abrasive mixing rate is influential upon surface roughness only. Strong interaction was found between jet pressure and workpiece material. Multi-criteria numerical optimization was performed in order to simultaneously maximize/minimize different combinations of performance measures.     

DCAF: An MPEG-21 Dynamic Content Adaptation Framework

Universal Multimedia Access aims at providing a gratifying end user-experience by either adapting the content, be it static or dynamic, to suit the usage environment or adapting the usage environment, be it client- or server-centric, to suit content. This paper presents our MPEG-21 Dynamic Content Adaptation Framework, acronym DCAF, which uses a fusion of Genetic Algorithms and Strength Pareto Optimality to adapt content in order to suit the usage environment.

Subharmonic Resonance Behavior for the Classical Hydrogen Atomic System

Previously unexplored resonance conditions are shown to exist for the classical hydrogen atomic system, where the electron is treated as a classical charged point particle following the nonrelativistic Lorentz-Dirac equation of motion about a stationary nucleus of opposite charge. For circularly polarized (CP) light directed normal to the orbit, very pronounced subharmonic resonance behavior is shown to occur with a variety of interesting properties. In particular, only if the amplitude of the CP light exceeds a critical value, will the resonance continue without radius and energy decay. A perturbation analysis is carried out to illustrate the main features of the behavior. The present phenomena adds to a growing list of other nonlinear dynamical behaviors of this simple system, that may well be important for more deeply understanding classical and quantum connections.     

Artistic features extraction from chinese calligraphy works via regional guided filter with reference image

Chinese calligraphy is a unique visual art, and and is one of the material basis of China’s traditional cultural heritage. However, time had caused the old calligraphy works to weathering and damages, so it is necessary to utilize advanced technologies to protect those works. One of those technologies is digital imaging, and the obtained images by digital imaging can preserve the visual information of calligraphy works better, furthermore, they can be used in further researches. While the basic works for those researches are to extract the artistic features which include two elements, i.e., form and spirit. However, most of the existing methods only extract the form and ignore the characters’ spirit, especially they are insensitive to the slight variation in complex ink strokes. To solve these problems, this paper proposes an extraction method based on regional guided flter (RGF) with reference images, which is generated by KNN matting and used as the input image for RGF. Since RGF is sensitive to the slight variation of ink, so the detailed information of the inside of strokes can be detected better. Besides, unlike the past works, which filter the whole strokes, RGF filters the inside of strokes and edges in different windows respectively, which results in that the edges are preserved accurately. Results from a deployment of several famous Chinese calligraphy works demonstrate that our method can extract more accurate and complete form and spirit with lower error rate.     

Approximation Algorithms for <Emphasis Type="Italic">k</Emphasis>-hurdle Problems

The polynomial-time solvable k-hurdle problem is a natural generalization of the classical s-t minimum cut problem where we must select a minimum-cost subset S of the edges of a graph such that |p∩S|≥k for every s-t path p. In this paper, we describe a set of approximation algorithms for “k-hurdle” variants of the NP-hard multiway cut and multicut problems. For the k-hurdle multiway cut problem with r terminals, we give two results, the first being a pseudo-approximation algorithm that outputs a (k−1)-hurdle solution whose cost is at most that of an optimal solution for k hurdles. Secondly, we provide a 2(1-\frac1r)2(1-\frac{1}{r})-approximation algorithm based on rounding the solution of a linear program, for which we give a simple randomized half-integrality proof that works for both edge and vertex k-hurdle multiway cuts that generalizes the half-integrality results of Garg et al. for the vertex multiway cut problem. We also describe an approximation-preserving reduction from vertex cover as evidence that it may be difficult to achieve a better approximation ratio than 2(1-\frac1r)2(1-\frac{1}{r}). For the k-hurdle multicut problem in an n-vertex graph, we provide an algorithm that, for any constant ε>0, outputs a ⌈(1−ε)k⌉-hurdle solution of cost at most O(log n) times that of an optimal k-hurdle solution, and we obtain a 2-approximation algorithm for trees.     

Is my model any good: differentially private regression diagnostics

Linear and logistic regression are popular statistical techniques for analyzing multi-variate data. Typically, analysts do not simply posit a particular form of the regression model, estimate its parameters, and use the results for inference or prediction. Instead, they first use a variety of diagnostic techniques to assess how well the model fits the relationships in the data and how well it can be expected to predict outcomes for out-of-sample records, revising the model as necessary to improve fit and predictive power. In this article, we develop \(\epsilon \)-differentially private diagnostics tools for regression, beginning to fill a gap in privacy-preserving data analysis. Specifically, we create differentially private versions of residual plots for linear regression and of receiver operating characteristic (ROC) curves as well as binned residual plot for logistic regression. The residual plot and binned residual plot help determine whether or not the data satisfy the assumptions underlying the regression model, and the ROC curve is used to assess the predictive power of the logistic regression model. These diagnostics improve the usefulness of algorithms for computing differentially private regression output, which alone does not allow analysts to assess the quality of the posited model. Our empirical studies show that these algorithms can be effective tools for allowing users to evaluate the quality of their models.     

Early bankruptcy prediction using ENPC

Bankruptcy prediction has long time been an active research field in finance. One of the main approaches to this issue is dealing with it as a classification problem. Among the range of instruments available, we focus our attention on the Evolutionary Nearest Neighbor Classifier (ENPC). In this work we assess the performance of the ENPC comparing it to six alternatives. The results suggest that this algorithm might be considered a good choice.