Mobile Learning

Works in progress from selected papers presented at the 2006 IADIS International Conference on Mobile Learning provide an overview of the diverse research being conducted in this field.     

Polycarbonate films metalized with a single component molecular conductor suited to strain and stress sensing applications

The paper reports all-organic strain and stress sensitive films that use electrical monitoring approach. The films were prepared by self-metallizing polycarbonate films with the single component molecular conductor [Au(α-tpdt)₂]⁰ (tpdt = 2,3-thiophenedithiolate). It was shown that [Au(α-tpdt)₂]⁰ by its nature is able to form metallic solid material with low crystallinity. Electromechanical tests demonstrated that the developed films are strain-resistive materials with advanced elastic properties: their electrical resistance varies linearly with uniaxial elongation up to relative strain being of 1.0% that is about five times larger than that for conventional metals. The gauge factor of the films is 4.4 and stress sensitivity is 30 Ω/bar. The processing characteristics of polycarbonate films, self-metalized with a metallic [Au(α-tpdt)₂]⁰-based layer, make them potentially useful for engineering flexible, lightweight, strain and pressure sensors. Due to electromechanical characteristics these films are suited to strain sensing applications requiring miniature strain control in a wide deformation range.     

Long‐Term Electrical and Mechanical Function Monitoring of a Human‐on‐a‐Chip System

The goal of human‐on‐a‐chip systems is to capture multiorgan complexity and predict the human response to compounds within physiologically relevant platforms. The generation and characterization of such systems is currently a focal point of research given the long‐standing inadequacies of conventional techniques for predicting human outcome. Functional systems can measure and quantify key cellular mechanisms that correlate with the physiological status of a tissue, and can be used to evaluate therapeutic challenges utilizing many of the same endpoints used in animal experiments or clinical trials. Culturing multiple organ compartments in a platform creates a more physiologic environment (organ–organ communication). Here is reported a human 4‐organ system composed of heart, liver, skeletal muscle, and nervous system modules that maintains cellular viability and function over 28 days in serum‐free conditions using a pumpless system. The integration of noninvasive electrical evaluation of neurons and cardiac cells and mechanical determination of cardiac and skeletal muscle contraction allows the monitoring of cellular function, especially for chronic toxicity studies in vitro. The 28‐day period is the minimum timeframe for animal studies to evaluate repeat dose toxicity. This technology can be a relevant alternative to animal testing by monitoring multiorgan function upon long‐term chemical exposure.     

An anisotropic microsphere-based approach for fiber orientation adaptation in soft tissue

Evolutionary processes in biological tissue, such as adaptation or remodeling, represent an enterprising area of research. In this paper, we present a multiscale model for the remodeling of fibered structures, such as bundles of collagen fibrils. With this aim, we introduce a von Mises statistical distribution function to account for the directional dispersion of the fibrils, and we remodel the underlying fibrils by changing their orientation. To numerically compute this process, we make use of the microsphere approach, which provides a useful multiscale tool for homogenizing the microstructure behavior, related to the fibrils of the bundle, in the macroscale of the problem. The results show how the fibrils respond to the stimulus by reorientation of their structure. This process leads to a stiffer material eventually reaching a stationary state. These results are in agreement with those reported in the literature, and they characterize the adaptation of biological tissue to external stimuli.     

Light‐Fueled,Spatiotemporal Modulation of Mechanical Properties and Rapid Self‐Healing of Graphene‐Doped Supramolecular Elastomers

Gaining spatially resolved control over the mechanical properties of materials in a remote, programmable, and fast‐responding way is a great challenge toward the design of adaptive structural and functional materials. Reversible, temperature‐sensitive systems, such as polymers equipped with supramolecular units, are a good model system to gain detailed information and target large‐scale property changes by exploiting reversible crosslinking scenarios. Here, it is demonstrated that coassembled elastomers based on polyglycidols functionalized with complementary cyanuric acid and diaminotriazine hydrogen bonding couples can be remotely modulated in their mechanical properties by spatially confined laser irradiation after hybridization with small amounts of thermally reduced graphene oxide (TRGO). The TRGO provides an excellent photothermal effect, leads to light‐adaptive steady‐state temperatures, and allows local breakage/de‐crosslinking of the hydrogen bonds. This enables fast self‐healing and spatiotemporal modulation of mechanical properties, as demonstrated by digital image correlation. This study opens pathways toward light‐fueled and light‐adaptive graphene‐based nanocomposites employing molecularly controlled thermal switches.     

Robustness of optimal channel reservation using handover prediction in multiservice wireless networks

The aim of our study is to obtain theoretical limits for the gain that can be expected when using handover prediction and to determine the sensitivity of the system performance against different parameters. We apply an average-reward reinforcement learning approach based on afterstates to the design of optimal admission control policies in mobile multimedia cellular networks where predictive information related to the occurrence of future handovers is available. We consider a type of predictor that labels active mobile terminals in the cell neighborhood a fixed amount of time before handovers are predicted to occur, which we call the anticipation time. The admission controller exploits this information to reserve resources efficiently. We show that there exists an optimum value for the anticipation time at which the highest performance gain is obtained. Although the optimum anticipation time depends on system parameters, we find that its value changes very little when the system parameters vary within a reasonable range. We also find that, in terms of system performance, deploying prediction is always advantageous when compared to a system without prediction, even when the system parameters are estimated with poor precision.     

On the use of 2-D coding techniques for ECG signals.

This paper discusses the convenience of using two-dimensional (2-D) coding techniques for the compression of electrocardiogram (ECG) signals. These signals present a very clear periodicity that can be exploited by the use of a 2-D time/frequency transform to decorrelate it as much as possible. A brief theoretical approach is given to justify the use of this technique, and a comparison is made between a 2-D and a one-dimensional (1-D) uniform quantization scenarios. The influence of the error as well as the frame size on the estimation of the fundamental period is studied.     

A rolling horizon simulation approach for managing demand with lead time variability

This paper proposes a rolling horizon (RH) approach to deal with management problems under dynamic demand in planning horizons with variable lead times using system dynamics (SD) simulation. Thus, the nature of dynamic RH solutions entails no inconveniences to contemplate planning horizons with unpredictable demands. This is mainly because information is periodically updated and replanning is done in time. Therefore, inventory and logistic costs may be lower. For the first time, an RH is applied for demand management with variable lead times along with SD simulation models, which allowed the use of lot-sizing techniques to be evaluated (Wagner-Whitin and Silver-Meal). The basic scenario is based on a real-world example from an automotive single-level SC composed of a first-tier supplier and a car assembler that contemplates uncertain demands while planning the RH and 216 subscenarios by modifying constant and variable lead times, holding costs and order costs, combined with lot-sizing techniques. Twenty-eight more replications comprising 504 new subscenarios with variable lead times are generated to represent a relative variation coefficient of the initial demand. We conclude that our RH simulation approach, along with lot-sizing techniques, can generate more sustainable planning results in total costs, fill rates and bullwhip effect terms.     

Inverse material identification in coupled acoustic-structure interaction using a modified error in constitutive equation functional

This work focuses on the identification of heterogeneous linear elastic moduli in the context of frequency-domain, coupled acoustic-structure interaction (ASI), using either solid displacement or fluid pressure measurement data. The approach postulates the inverse problem as an optimization problem where the solution is obtained by minimizing a modified error in constitutive equation (MECE) functional. The latter measures the discrepancy in the constitutive equations that connect kinematically admissible strains and dynamically admissible stresses, while incorporating the measurement data as additional quadratic error terms. We demonstrate two strategies for selecting the MECE weighting coefficient to produce regularized solutions to the ill-posed identification problem: 1) the discrepancy principle of Morozov, and 2) an error-balance approach that selects the weight parameter as the minimizer of another functional involving the ECE and the data misfit. Numerical results demonstrate that the proposed methodology can successfully recover elastic parameters in 2D and 3D ASI systems from response measurements taken in either the solid or fluid subdomains. Furthermore, both regularization strategies are shown to produce accurate reconstructions when the measurement data is polluted with noise. The discrepancy principle is shown to produce nearly optimal solutions, while the error-balance approach, although not optimal, remains effective and does not need a priori information on the noise level.     

Synthesis and electrochemical properties of polyaniline nanofibers by interfacial polymerization

Polyaniline nanofibers were prepared by interfacial polymerization with different organic solvents such as chloroform and carbon tetrachloride. Field emission scanning electron microscopy and transmission electron microscopy were used to study the morphological properties of polyaniline nanofibers. Chemical characterization was carried out using Fourier transform infrared spectroscopy, UV-Vis spectroscopy, and X-ray diffraction spectroscopy and surface area was measured using BET isotherm. Polyaniline nanofibers doped with lithium hexafluorophosphate were prepared and their electrochemical properties were evaluated.