Product intelligence in warehouse management: A case study

The need for more flexible, adaptable and customer-oriented warehouse operations has been increasingly identified as an important issue by today's warehouse companies due to the rapidly changing preferences of the customers that use their services. Motivated by manufacturing and other logistics operations, in this paper we argue on the potential application of product intelligence in warehouse operations as an approach that can help warehouse companies address these issues. We discuss the opportunities of such an approach using a real example of a third-party-logistics warehouse company and we present the benefits it can bring in their warehouse management systems. © 2013 Springer-Verlag.

Dry oxidation and vacuum annealing treatments for tuning the wetting properties of carbon nanotube arrays.

In this article, we describe a simple method to reversibly tune the wetting properties of vertically aligned carbon nanotube (CNT) arrays. Here, CNT arrays are defined as densely packed multi-walled carbon nanotubes oriented perpendicular to the growth substrate as a result of a growth process by the standard thermal chemical vapor deposition (CVD) technique.(1,2) These CNT arrays are then exposed to vacuum annealing treatment to make them more hydrophobic or to dry oxidation treatment to render them more hydrophilic. The hydrophobic CNT arrays can be turned hydrophilic by exposing them to dry oxidation treatment, while the hydrophilic CNT arrays can be turned hydrophobic by exposing them to vacuum annealing treatment. Using a combination of both treatments, CNT arrays can be repeatedly switched between hydrophilic and hydrophobic.(2) Therefore, such combination show a very high potential in many industrial and consumer applications, including drug delivery system and high power density supercapacitors.(3-5) The key to vary the wettability of CNT arrays is to control the surface concentration of oxygen adsorbates. Basically oxygen adsorbates can be introduced by exposing the CNT arrays to any oxidation treatment. Here we use dry oxidation treatments, such as oxygen plasma and UV/ozone, to functionalize the surface of CNT with oxygenated functional groups. These oxygenated functional groups allow hydrogen bond between the surface of CNT and water molecules to form, rendering the CNT hydrophilic. To turn them hydrophobic, adsorbed oxygen must be removed from the surface of CNT. Here we employ vacuum annealing treatment to induce oxygen desorption process. CNT arrays with extremely low surface concentration of oxygen adsorbates exhibit a superhydrophobic behavior.

Reversible tuning of the wettability of carbon nanotube arrays: the effect of ultraviolet/ozone and vacuum pyrolysis treatments.

Among diverse types of synthetic materials, arrays of vertically aligned carbon nanotubes have attracted the most attention, mainly because of their exceptional mechanical, electrical, optical, and thermal properties. However, their wetting properties are yet to be understood. In this present study, oxygenated surface functional groups have been identified as a vital factor in controlling the wetting properties of carbon nanotube arrays. The results presented herein indeed show that a combination of ultraviolet/ozone and vacuum pyrolysis treatments can be used to vary the surface concentration of these functional groups such that the carbon nanotube array can be repeatedly switched between hydrophilic and hydrophobic.

Bayesian parameter identification for vibro-acoustic models with nonparametric uncertainty

Vibration and acoustic analysis at higher frequencies faces two challenges: computing the response without using an excessive number of degrees of freedom, and quantifying its uncertainty due to small spatial variations in geometry, material properties and boundary conditions. Efficient models make use of the observation that when the response of a decoupled vibro-acoustic subsystem is sufficiently sensitive to uncertainty in such spatial variations, the local statistics of its natural frequencies and mode shapes saturate to universal probability distributions. This holds irrespective of the causes that underly these spatial variations and thus leads to a nonparametric description of uncertainty. This work deals with the identification of uncertain parameters in such models by using experimental data. One of the difficulties is that both experimental errors and modeling errors, due to the nonparametric uncertainty that is inherent to the model type, are present. This is tackled by employing a Bayesian inference strategy. The prior probability distribution of the uncertain parameters is constructed using the maximum entropy principle. The likelihood function that is subsequently computed takes the experimental information, the experimental errors and the modeling errors into account. The posterior probability distribution, which is computed with the Markov Chain Monte Carlo method, provides a full uncertainty quantification of the identified parameters, and indicates how well their uncertainty is reduced, with respect to the prior information, by the experimental data. © 2013 Taylor & Francis Group, London.

Embodied Artificial Intelligence

This book is devoted to the rapidly growing highly interdisciplinary field of embodied artificial intelligence involving researchers from areas as diverse as computer science, engineering, cognitive science, neuroscience, biology, ...

Finding resonance: Adaptive frequency oscillators for dynamic legged locomotion

There is much to gain from providing walking machines with passive dynamics, e.g. by including compliant elements in the structure. These elements can offer interesting properties such as self-stabilization, energy efficiency and simplified control. However, there is still no general design strategy for such robots and their controllers. In particular, the calibration of control parameters is often complicated because of the highly nonlinear behavior of the interactions between passive components and the environment. In this article, we propose an approach in which the calibration of a key parameter of a walking controller, namely its intrinsic frequency, is done automatically. The approach uses adaptive frequency oscillators to automatically tune the intrinsic frequency of the oscillators to the resonant frequency of a compliant quadruped robot The tuning goes beyond simple synchronization and the learned frequency stays in the controller when the robot is put to halt. The controller is model free, robust and simple. Results are presented illustrating how the controller can robustly tune itself to the robot, as well as readapt when the mass of the robot is changed. We also provide an analysis of the convergence of the frequency adaptation for a linearized plant, and show how that analysis is useful for determining which type of sensory feedback must be used for stable convergence. This approach is expected to explain some aspects of developmental processes in biological and artificial adaptive systems that "develop" through the embodied system-environment interactions. © 2006 IEEE.

Embodied artificial intelligence: Trends and challenges

The field of Artificial Intelligence, which started roughly half a century ago, has a turbulent history. In the 1980s there has been a major paradigm shift towards embodiment. While embodied artificial intelligence is still highly diverse, changing, and far from "theoretically stable", a certain consensus about the important issues and methods has been achieved or is rapidly emerging. In this non-technical paper we briefly characterize the field, summarize its achievements, and identify important issues for future research. One of the fundamental unresolved problems has been and still is how thinking emerges from an embodied system. Provocatively speaking, the central issue could be captured by the question "How does walking relate to thinking?" © Springer-Verlag Berlin Heidelberg 2004.

Pixel-level tunable liquid crystal lenses for auto-stereoscopic display

Mobile video and gaming are now widely used, and delivery of a glass-free 3D experience is of both research and development interest. The key drawbacks of a conventional 3D display based on a static lenticular lenslet array and parallax barriers are low resolution, limited viewing angle and reduced brightness, mainly because of the need of multiple-pixels for each object point. This study describes the concept and performance of pixel-level cylindrical liquid crystal (LC) lenses, which are designed to steer light to the left and right eye sequentially to form stereo parallax. The width of the LC lenses can be as small as 20-30 μm, so that the associated auto-stereoscopic display will have the same resolution as the 2D display panel in use. Such a thin sheet of tunable LC lens array can be applied directly on existing mobile displays, and can deliver 3D viewing experience while maintaining 2D viewing capability. Transparent electrodes were laser patterned to achieve the single pixel lens resolution, and a high birefringent LC material was used to realise a large diffraction angle for a wide field of view. Simulation was carried out to model the intensity profile at the viewing plane and optimise the lens array based on the measured LC phase profile. The measured viewing angle and intensity profile were compared with the simulation results. © 2014 SPIE.