Enhancement of ion dynamics in PMMA-based gels with addition of TiO2 nano-particles

Solvent and ion dynamics in PMMA based gels have been investigated as a function of the loading of nanosized TiO₂ particles. The gels have a molar ratio of 46.5:19:4.5:30 of ethylene carbonate (EC), propylene carbonate (PC), lithium perchlorate and PMMA, respectively. A series of samples with 0, 4, 6 and 8 wt.% TiO₂ filler were investigated. The diffusion coefficients for the lithium ions and for the two solvents (EC and PC) were investigated by pfg-NMR. It was shown that the addition of filler to the gel electrolytes enhances the diffusion of the cations, while the diffusion of the solvents remains constant. Raman measurements show no significant changes in ion–ion interactions with the addition of fillers, while the ionic conductivity is seen to decrease. However, the sample with 8 wt.% TiO₂ had a conductivity close to that of the unfilled sample.

The enhancement of lithium ion dissociation in polyelectrolyte gels on the addition of ceramic nano-fillers

Nano-particle oxide fillers including TiO₂, SiO₂ and Al₂O₃ have previously been shown to have a significant affect on the properties of both polymer and polymer gel electrolytes. In some cases, conductivity increases of one order of magnitude have been reported in crystalline PEO–base complexes. In this work, we report the effects of TiO₂ and SiO₂ on a poly(Li-AMPS)-based gel polyelectrolyte. Impedance spectroscopy and pfg-NMR spectroscopy indicates an increase in the number of available charge carriers with the addition of filler. An ideal amount of ceramic filler has been identified, with additional filler only saturating the system and reducing the conductivity below that of the pristine polyelectrolyte system. SEM micrographs suggest a model whereby the filler interacts readily with the sulfonate group; the surface area of the filler being an important factor.

Enhancement of ion dissociation in polyelectrolyte gels

High conductivity in single ion conducting polymer electrolytes is still the ultimate aim for many electrochemical devices such as secondary lithium batteries. Achieving effective ion dissociation in these cases remains a challenge since the active ion tends to remain in close proximity to the backbone charge as a result of a low degree of ion dissociation. A unique aspect of this dissociation problem in polyelectrolytes is the repulsion between the backbone charges created by dissociation. One way of enhancing ion dissociation in polyelectrolyte systems is to use copolymers in which only a fraction (<20%) of the mer units are charged and where the comonomer is itself chosen to be polar and preferably to be compatible with potential solvents. We have also found that certain dissociation enhancers based on ionic liquids or boroxine ring compounds can lead to high ionic conductivity. In the cases where an ionic liquid is used as the solvent in a polyelectrolyte gel, the viscosity of the ionic liquid and its hydrophilicity are critical to achieving high conductivity. Compounds based on the dicyanamide anion appear to be very effective ionic solvents; polyelectrolyte gels incorporating such ionic liquids exhibit conductivities as high as 10⁻² S/cm at room temperature. In the case of boroxine ring dissociation enhancers, gels based on poly(lithium-2-acrylamido-2-methyl-1-propanesulfonate) and ethylene carbonate produce conductivities approaching 10⁻³ S/cm. This paper will discuss these approaches for achieving higher conductivity in polyelectrolyte materials and suggest future directions to ensure single ion transport.

Effective pseudonoise sequence and decoding function for imperceptibility and robustness enhancement in time-spread echo-based audio watermarking

This paper proposes an effective pseudonoise (PN) sequence and the corresponding decoding function for time-spread echo-based audio watermarking. Different from the traditional PN sequence used in time-spread echo hiding, the proposed PN sequence has two features. Firstly, the echo kernel resulting from the new PN sequence has frequency characteristics with smaller magnitudes in perceptually significant region. This leads to higher perceptual quality. Secondly, the correlation function of the new PN sequence has three times more large peaks than that of the existing PN sequence. Based on this feature, we propose a new decoding function to improve the robustness of time-spread echo-based audio watermarking. The effectiveness of the proposed PN sequence and decoding function is illustrated by theoretical analysis, simulation examples, and listening test.

Machine learning approaches for modeling spammer behavior

Spam is commonly known as unsolicited or unwanted email messages in the Internet causing potential threat to Internet Security. Users spend a valuable amount of time deleting spam emails. More importantly, ever increasing spam emails occupy server storage space and consume network bandwidth. Keyword-based spam email filtering strategies will eventually be less successful to model spammer behavior as the spammer constantly changes their tricks to circumvent these filters. The evasive tactics that the spammer uses are patterns and these patterns can be modeled to combat spam. This paper investigates the possibilities of modeling spammer behavioral patterns by well-known classification algorithms such as Naïve Bayesian classifier (Naive Bayes), Decision Tree Induction (DTI) and Support Vector Machines (SVMs). Preliminary experimental results demonstrate a promising detection rate of around 92%, which is considerably an enhancement of performance compared to similar spammer behavior modeling research.

ATR FT-IR absorption enhancement of a thin film under the photon-tunneling condition

A simple, yet very powerful technique for the spectral acquisition of an extremely thin film with enhanced absorption was explored. An infrared absorption of an extremely thin film confined between media of high refractive indices was greater than that of its bulk when the spectrum was acquired under the attenuated total reflection (ATR) condition with parallel (p) polarized radiation. The absorption enhancement was not observed under perpendicular (s) polarized radiation. Theoretical investigations indicated that the absorption enhancement was proportional to the integration of the mean square evanescent field within the film. The field integration under p-polarized radiation increased, while that under s-polarized radiation decreased as the thickness of the confined film became thinner. The maximum enhancement was observed when the film was sufficiently thinner than the penetration depth. The phenomena were experimentally investigated, and the results agreed very well with theoretical predictions.

Performance modelling of speculative prefetching for compound requests in low bandwidth networks

To improve the accuracy of access prediction, a prefetcher for web browsing should recognize the fact that a web page is a compound. By this term we mean that a user request for a single web page may require the retrieval of several multimedia items. Our prediction algorithm builds an access graph that captures the dynamics of web navigation rather than merely attaching probabilities to hypertext structure. When it comes to making prefetch decisions, most previous studies in speculative prefetching resort to simple heuristics, such as prefetching an item with access probabilities larger than a manually tuned threshold. The paper takes a different approach. Specifically, it models the performance of the prefetcher and develops a prefetch policy based on a theoretical analysis of the model. In the analysis, we derive a formula for the expected improvement in access time when prefetch is performed in anticipation for a compound request. We then develop an algorithm that integrates prefetch and cache replacement decisions so as to maximize this improvement. We present experimental results to demonstrate the effectiveness of compound-based prefetching in low bandwidth networks.

Distributed audio network for speech enhancement in challenging noise backgrounds

This paper presents a new approach to enhance speech based on a distributed microphone network. Each microphone is used to simultaneously classify the input into either one of the noise types or as speech. For enhancing the speech signal a modified spectral subtraction approach is used that utilise the sound information of the entire network to update the noise model even during speech. This improves the reduction of the ambient noise, especially for non-stationary noise types such as street or beach noise. Experiments demonstrate the effectiveness of the proposed system.

Adaptive speech enhancement with varying noise backgrounds

We present a new approach for speech enhancement in the presence of non-stationary and rapidly changing background noise. A distributed microphone system is used to capture the acoustic characteristics of the environment. The input of each microphone is then classified either as speech or one of the predetermined noise types. Further enhancement of speech in respective microphones is carried out using a modified spectral subtraction algorithm that incorporates multiple noise models to quickly adapt to rapid background noise changes. Tests on real world speech captured under diverse conditions demonstrate the effectiveness of this method.

Model-based combined tracking and resolution enhancement

Wide area surveillance requires high-resolution images of the object of interest derived possibly from only low-resolution video of the whole scene. We propose a combined tracking and resolution enhancement approach that increases the resolution of the object of interest during tracking. The key idea is the use of an object-specific 3D mesh model with which we are able to track non-planar objects across a large number of frames. This model is subdivided such that every triangle is smaller than a pixel when projected into the image to facilitate super-resolution on the model rather than on the image. We apply our approach to faces and show that it outperforms interpolation methods by achieving resolution enhancement, while being less blurred.

Investigation of a prefetch model for low bandwidth networks

We investigate speculative prefetching under a model in which prefetching is neither aborted nor preempted by demand fetch but instead gets equal priority in network bandwidth utilisation. We argue that the non-abortive assumption is appropriate for wireless networks where bandwidth is low and latency is high, and the non-preemptive assumption is appropriate for Internet where prioritization is not always possible. This paper assumes the existence of an access model to provide some knowledge about future accesses and investigates analytically the performance of a prefetcher that utilises this knowledge. In mobile computing, because resources are severely constrained, performance prediction is as important as access prediction. For uniform retrieval time, we derive a theoretical limit of improvement in access time due to prefetching. This leads to the formulation of an optimal algorithrn for prefetching one access ahead. For non-uniform retrieval time, two different types of prefetching of multiple documents, namely mainline and branch prefetch, are evaluated against prefetch of single document. In mainline prefetch, the most probable sequence of future accesses is prefetched. In branch prefetch, a set of different alternatives for future accesses is prefetched. Under some conditions, mainline prefetch may give slight improvement in user-perceived access time over single prefetch with nominal extra retrieval cost, where retrieval cost is defined as the expected network time wasted in non-useful prefetch. Branch prefetch performs better than mainline prefetch but incurs more retrieval cost.

Illness burden and medical comorbidity in the systematic treatment enhancement program for bipolar disorder

Objective:  Coexisting chronic medical conditions are common in bipolar disorder. Here, we report the prevalence and correlates of medical comorbidity in patients enrolled in the Systematic Treatment Enhancement Program for Bipolar Disorder (STEP-BD). We were particularly interested in associations between variables reflecting illness chronicity and burden with comorbid medical conditions.

Method:  We used intake data from the open-label component of the STEP-BD. History of medical comorbidity was obtained from the affective disorders evaluation, and its presence was the outcome of interest. The sample size in analyses varied from 3399 to 3534. We used multiple Poisson regression to obtain prevalence ratios.

Results:  The prevalence of any medical comorbidity in the sample was 58.8%. In addition to demographic variable, several clinical characteristics were associated with the frequency of medical comorbidity. Having more than 10 previous mood episodes, childhood onset, smoking, lifetime comorbidity with anxiety, and substance use disorders were independently associated with having a medical comorbidity in the final multivariate model.

Conclusion:  The results presented here reveal strong associations between variables related to illness chronicity and medical burden in bipolar disorder. This lends further support to recent multidimensional models incorporating medical morbidity as a core feature of bipolar disorder.