Loading Rate Effect on Nanohardness of Soda-Lime-Silica Glass

To understand how hardness, the key design parameter for applications of brittle solids such as glass concerning contact deformation, is affected by loading rate variation, nanoindentation with a Berkovich tip was used to measure the nanohardness of a 330-μm-thick soda-lime-silica glass as a function of loading rate (1 to 1000 mN·s⁻¹). The results showed for the very first time that, with variations in the loading rate, there was a 6 to 9 pct increase in the nanohardness of glass up to a threshold loading rate (TLR), whereafter it did not appreciably increase with further increase in loading rate. Further, the nanohardness data showed an indentation size effect (ISE) that obeyed the Meyer’s law. These observations were explained in terms of a strong shear stress component developed just beneath the nanoindenter and the related shear-induced deformation processes at local microstructural scale weak links. The significant or insignificant presence of shear-induced serrations in load depth plots and corresponding scanning electron microscopic evidence of a strong or mild presence of shear deformation bands in and around the nanoindentation cavity supported such a rationalization. Finally, a qualitative picture was developed for different deformation processes induced at various loading rates in glass.     

Data warehousing and data mining techniques for intrusion detection systems

This paper describes data mining and data warehousing techniques that can improve the performance and usability of Intrusion Detection Systems (IDS). Current IDS do not provide support for historical data analysis and data summarization. This paper presents techniques to model network traffic and alerts using a multi-dimensional data model and star schemas. This data model was used to perform network security analysis and detect denial of service attacks. Our data model can also be used to handle heterogeneous data sources (e.g. firewall logs, system calls, net-flow data) and enable up to two orders of magnitude faster query response times for analysts as compared to the current state of the art. We have used our techniques to implement a prototype system that is being successfully used at Army Research Labs. Our system has helped the security analyst in detecting intrusions and in historical data analysis for generating reports on trend analysis. Recommended by: Ashfaq Khokhar     

Approximate MLEs for the location and scale parameters of thehalf-logistic distribution with type-II right-censoring

For the half-logistic distribution the maximum likelihood method does not provide an explicit estimator for the scale parameter based on either complete or right-censored samples. The authors provide a simple method of deriving an explicit estimator by approximating the likelihood function. The bias and variance of this estimator are studied, and it is shown that this estimator is as efficient as the best linear unbiased estimator. An example to illustrate the method is presented     

Some more sensitive measures of sensitivity and response bias.

In this article, the author proposes a new pair of sensitivity and response bias indices and compares them to other measures currently available, including d′ and β of signal detection theory. Unlike d′ and β, these new performance measures do not depend on specific distributional assumptions or assumptions about the transformation from stimulus information to a discrimination judgment. With simulated and empirical data, the new sensitivity index is shown to be more accurate than d′ and 16 other indices when these measures are used to compare the sensitivity levels of 2 experimental conditions. Results from a perceptual discrimination experiment demonstrate the feasibility of the new distribution-free bias index and suggest that biases of the type defined within the signal detection theory framework (i.e., the placement of a decision criterion) do not exist, even under an asymmetric payoff manipulation. (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

Preparation and characterization of poly(ethylene/tetramethylene terephthalate) copolyesters

Random copolyesters were prepared from dimethyl terephthalate (DMT), ethylene glycol (EG) and butane 1,4-diol (BD) by melt-polycondensation techniques, using varying amounts of EG and BD. Compositions have been established by ¹H n.m.r. spectroscopy. Intrinsic viscosity and number average molecular weight ($\text{M}\text{?}{}_{\mathrm{n}}$) were measured. Thermal properties have been studied by differential thermal analysis. Melting and crystallization temperatures and thermodynamic parameters are discussed in terms of structural differences, particularly the effect of composition and chain flexibility. The degree of crystallinity from differential thermal analysis, i.r. and wide angle X-ray scattering (WAXS) are discussed.     

Optimum difference mode excitations for monopulse arrays

A technique has been developed to obtain optimum difference mode excitations for monopulse arrays. In addition, a direct interpolation scheme has been devised for situations where near-optimum results would suffice. A parameter designated asu_{0}is identified with every optimum difference pattern. The choice of this parameteru_{0}determines the sidelobe level of the optimum pattern. The problem of obtaining the optimum excitations has been shown to be reducible to one of finding out the best approximation that minimizes the maximum deviation (minimax) from the real line (u = betad cos varpaxis), over a range determined byu_{0}. This latter problem has been solved using a modified Remez exchange algorithm. An extensive set of design curves has also been presented.     

A Mixed Integer Stochastic Optimization Model for Settlement Risk in Retail Electric Power Markets

Recent changes in the U.S. electric power markets have contributed to volatility in hourly prices and loads. In this paper we consider the position of the electric power retailer who typically contracts with suppliers and end-users and must provide future load requirements to the suppliers. As part of this energy supply chain, the retailer is faced with great uncertainty in both market prices as well as end-user loads. Based on actual data for the PJM market covering Pennsylvania, New Jersey, and Maryland, we develop a probabilistic optimization model to optimize the net profits for the retailer for a forecast time horizon (typically one or more hours) given the cumulative performance in previous time periods (hours). The resulting model is formulated as a mixed integer linear program with binary variables due to the disjunctive nature of certain forward load estimation bandwidth tolerance constraints. In addition, we also provide an existence result to this optimization model. Lastly, we present a numerical example of the optimization model to validate its workings and provide some insight into model sensitivities.     

An Acknowledgment-Based Approach for the Detection of Routing Misbehavior in MANETs

We study routing misbehavior in MANETs (mobile ad hoc networks) in this paper. In general, routing protocols for MANETs are designed based on the assumption that all participating nodes are fully cooperative. However, due to the open structure and scarcely available battery-based energy, node misbehaviors may exist. One such routing misbehavior is that some selfish nodes will participate in the route discovery and maintenance processes but refuse to forward data packets. In this paper, we propose the 2ACK scheme that serves as an add-on technique for routing schemes to detect routing misbehavior and to mitigate their adverse effect. The main idea of the 2ACK scheme is to send two-hop acknowledgment packets in the opposite direction of the routing path. In order to reduce additional routing overhead, only a fraction of the received data packets are acknowledged in the 2ACK scheme. Analytical and simulation results are presented to evaluate the performance of the proposed scheme     

T-Ray Sensing and Imaging

T-ray wavelengths are long enough to pass through dry, nonpolar objects opaque at visible wavelengths, but short enough to be manipulated by optical components to form an image. Sensing in this band potentially provides advantages in a number of areas of interest to security and defense such as screening of personnel for hidden objects and the retection of chemical and biological agents. Several private companies are developing smaller, reliable cheaper systems allowing for commercialization and this motivates us to review a number of promising applications within this paper. While there are a number of challenges to be overcome there is little doubt that T-ray technology will play a significant role in the near future for advancement of security, public health, and defense.     

Differences in physical phenomena governing laser machining of structural ceramics

Several structural ceramics such as alumina, silicon nitride, silicon carbide and magnesia were machined using a pulsed Nd:YAG laser. Laser processing conditions and temperature dependent thermo-physical properties govern the physical phenomena that machine these ceramics. Melting, dissociation and evaporation are some of the vital mechanisms associated with material removal. Discrimination and incorporation of these physical processes into a hydrodynamic machining model to predict different machining parameters was conducted. The model provides an outstanding tool for advance prediction of thermal energy and time required for machining desired depth of material.