The dynamic contact area of elastomers at different velocities

The friction in tribo-systems that contain viscoelastic materials, such as elastomers, is relevant for a large number of applications. Examples include tyres, hoses, transmission and conveyor belts. To quantify the friction in these applications, one must first understand the contact behaviour of such viscoelastic materials, both in static and in dynamic situations. This work discusses an experimental study into the change of the contact area with the sliding velocity and relates the change in contact area with the mechanical properties of the elastomer. The results show that for a tribo-system containing an elastomer, there is a threshold velocity, above which the size of the contact area significantly reduces.     

Fine grinding of thermoplastics by high speed friction grinding assisted by guar gum

High speed friction grinding has been used to grind plant and food substances in water but never been explored for grinding of thermoplastics like polylactic acid (PLA), low and high density polyethylene and polypropylene. Such grinding was investigated in this work and was made possible by using 0.5% guar gum solution instead of just water because increasing the viscosity of water reduced their settling and the speed of passing through the grinder. Tensile, flexural, and impact strengths of the plastics were studied and higher grinding efficiency of PLA could be explained by its low elongation-at-break compared to low density polyethylene, high density polyethylene, and polypropylene. The microplastics (2000–45 μm) were studied for mass and particle size distributions and by scanning electron microscopy, ¹³C CP/MAS NMR, Fourier transform infrared spectroscopy, differential scanning calorimetry, and thermogravimetric analysis. In addition, viscosity of guar gum and contact angles was measured. This new technology can produce finely ground microplastics (710–45 μm) for a variety of applications.     

On the evaluation of unsupervised outlier detection: measures,datasets, and an empirical study

The evaluation of unsupervised outlier detection algorithms is a constant challenge in data mining research. Little is known regarding the strengths and weaknesses of different standard outlier detection models, and the impact of parameter choices for these algorithms. The scarcity of appropriate benchmark datasets with ground truth annotation is a significant impediment to the evaluation of outlier methods. Even when labeled datasets are available, their suitability for the outlier detection task is typically unknown. Furthermore, the biases of commonly-used evaluation measures are not fully understood. It is thus difficult to ascertain the extent to which newly-proposed outlier detection methods improve over established methods. In this paper, we perform an extensive experimental study on the performance of a representative set of standard k nearest neighborhood-based methods for unsupervised outlier detection, across a wide variety of datasets prepared for this purpose. Based on the overall performance of the outlier detection methods, we provide a characterization of the datasets themselves, and discuss their suitability as outlier detection benchmark sets. We also examine the most commonly-used measures for comparing the performance of different methods, and suggest adaptations that are more suitable for the evaluation of outlier detection results.     

Patchy solution of a Francis–Byrnes–Isidori partial differential equation

The solution to the nonlinear output regulation problem requires one to solve a first‐order partial differential equation, known as the Francis–Byrnes–Isidori equations. In this paper, we propose a method to compute approximate solutions to the Francis–Byrnes–Isidori equations when the zero dynamics of the plant are hyperbolic and the exosystem is two dimensional. With our method, we are able to produce approximations that converge uniformly to the true solution. Our method relies on the periodic nature of two‐dimensional analytic center manifolds. Copyright © 2012 John Wiley & Sons, Ltd.     

A survey on enhanced subspace clustering

Subspace clustering finds sets of objects that are homogeneous in subspaces of high-dimensional datasets, and has been successfully applied in many domains. In recent years, a new breed of subspace clustering algorithms, which we denote as enhanced subspace clustering algorithms, have been proposed to (1) handle the increasing abundance and complexity of data and to (2) improve the clustering results. In this survey, we present these enhanced approaches to subspace clustering by discussing the problems they are solving, their cluster definitions and algorithms. Besides enhanced subspace clustering, we also present the basic subspace clustering and the related works in high-dimensional clustering.     

Realization of robust nonlinear model predictive control by offline optimisation

This paper describes a new method for increasing the computational efficiency of nonlinear robust model-based predictive control. It is based on the application of neuro-fuzzy networks and improves the computation efficiency by arranging the online optimisation to be done offline. The offline optimisation is realized by offline training a neuro-fuzzy network, consisting of zero-order T–S fuzzy rules, which is designed to approximate the input–output relationship of a robust model-based predictive controller. The design and the training of the neuro-fuzzy network are described, and the corresponding control algorithm is developed. Experiment results performed on the temperature control loop of an experimental air-handling unit (AHU) demonstrate the effectiveness of this approach.     

X as a Service, Cloud Computing, and the Need for Good Judgment

The paper talks about the spreading "X as a service" phenomenon in the IT arena, cloud computing, and SLA. In the article, the author mentioned that "X as a Service" has entered the vocabulary in many forms, mostly in computing aspect. Also, cloud computing can lead to significant savings as well as significant service improvements. Cloud computing vendors would like to reap most of those benefits.It can change this by bringing past experiences and good judgment into play and adapt them to new situation. That is the mark of being a "professional" in IT field. Experience, understanding, and thoughtfulness can help the contract people write an effective service level agreement (SLA) that puts its needs in good legal form. Ideally the SLA will include all needed services and none that aren't needed.