Exploring value-added benefits to enhance wider adoption of chipless RFID system

Radio-frequency identification technology (RFID) is a popular modern technology proven to deliver a range of value-added benefits to achieve system and operational efficiency, as well as cost-effectiveness. The operational characteristics of RFID outperform barcodes in many aspects. Despite its well-perceived benefits, a definite rationale for larger scale adoption is still not so promising. One of the key reasons is high implementation cost, especially the cost of tags for applications involving item-level tagging. This has resulted in the development of chipless RFID tags which cost much less than conventional chip-based tags. Despite the much lower tag cost, the uptake of chipless RFID system in the market is still not as widespread as predicted by RFID experts. This chapter explores the value-added applications of chipless RFID system to promote wider adoption. The chipless technology's technical and operational characteristics, benefits, limitations and current uses will also be examined. The merit of this chapter is to contribute fresh propositions to the promising applications of chipless RFID to increase its adoption in the industries that are currently not (or less popular in) utilising it, such as retail, logistics, manufacturing, healthcare, and service sectors. © 2013, IGI Global.

Identification and molecular mechanisms of the rapid tonicity-induced relocalization of the aquaporin 4 channel

The aquaporin family of integral membrane proteins is comprised of channels that mediate cellular water flow. Aquaporin 4 (AQP4) is highly expressed in the glial cells of the central nervous system and facilitates the osmotically-driven pathological brain swelling associated with stroke and traumatic brain injury. Here we show that AQP4 cell surface expression can be rapidly and reversibly regulated in response to changes of tonicity in primary cortical rat astrocytes and in transfected HEK293 cells. The translocation mechanism involves protein kinase A (PKA) activation, influx of extracellular calcium and activation of calmodulin. We identify five putative PKA phosphorylation sites and use site-directed mutagenesis to show that only phosphorylation at one of these sites, serine- 276, is necessary for the translocation response. We discuss our findings in the context of the identification of new therapeutic approaches to treating brain oedema.

TATPred:a Bayesian method for the identification of twin arginine translocation pathway signal sequences

The twin arginine translocation (TAT) system ferries folded proteins across the bacterial membrane. Proteins are directed into this system by the TAT signal peptide present at the amino terminus of the precursor protein, which contains the twin arginine residues that give the system its name. There are currently only two computational methods for the prediction of TAT translocated proteins from sequence. Both methods have limitations that make the creation of a new algorithm for TAT-translocated protein prediction desirable. We have developed TATPred, a new sequence-model method, based on a Nave-Bayesian network, for the prediction of TAT signal peptides. In this approach, a comprehensive range of models was tested to identify the most reliable and robust predictor. The best model comprised 12 residues: three residues prior to the twin arginines and the seven residues that follow them. We found a prediction sensitivity of 0.979 and a specificity of 0.942.

An agent approach to improving radio frequency identification enabled Returnable Transport Equipment

Returnable transport equipment (RTE) such as pallets form an integral part of the supply chain and poor management leads to costly losses. Companies often address this matter by outsourcing the management of RTE to logistics service providers (LSPs). LSPs are faced with the task to provide logistical expertise to reduce RTE related waste, whilst differentiating their own services to remain competitive. In the current challenging economic climate, the role of the LSP to deliver innovative ways to achieve competitive advantage has never been so important. It is reported that radio frequency identification (RFID) application to RTE enables LSPs such as DHL to gain competitive advantage and offer clients improvements such as loss reduction, process efficiency improvement and effective security. However, the increased visibility and functionality of RFID enabled RTE requires further investigation in regards to decision‐making. The distributed nature of the RTE network favours a decentralised decision‐making format. Agents are an effective way to represent objects from the bottom‐up, capturing the behaviour and enabling localised decision‐making. Therefore, an agent based system is proposed to represent the RTE network and utilise the visibility and data gathered from RFID tags. Two types of agents are developed in order to represent the trucks and RTE, which have bespoke rules and algorithms in order to facilitate negotiations. The aim is to create schedules, which integrate RTE pick‐ups as the trucks go back to the depot. The findings assert that: - agent based modelling provides an autonomous tool, which is effective in modelling RFID enabled RTE in a decentralised utilising the real‐time data facility. ‐ the RFID enabled RTE model developed enables autonomous agent interaction, which leads to a feasible schedule integrating both forward and reverse flows for each RTE batch. ‐ the RTE agent scheduling algorithm developed promotes the utilisation of RTE by including an automatic return flow for each batch of RTE, whilst considering the fleet costs andutilisation rates. ‐ the research conducted contributes an agent based platform, which LSPs can use in order to assess the most appropriate strategies to implement for RTE network improvement for each of their clients.

Fully probabilistic control for stochastic nonlinear control systems with input dependent noise

Robust controllers for nonlinear stochastic systems with functional uncertainties can be consistently designed using probabilistic control methods. In this paper a generalised probabilistic controller design for the minimisation of the Kullback-Leibler divergence between the actual joint probability density function (pdf) of the closed loop control system, and an ideal joint pdf is presented emphasising how the uncertainty can be systematically incorporated in the absence of reliable systems models. To achieve this objective all probabilistic models of the system are estimated from process data using mixture density networks (MDNs) where all the parameters of the estimated pdfs are taken to be state and control input dependent. Based on this dependency of the density parameters on the input values, explicit formulations to the construction of optimal generalised probabilistic controllers are obtained through the techniques of dynamic programming and adaptive critic methods. Using the proposed generalised probabilistic controller, the conditional joint pdfs can be made to follow the ideal ones. A simulation example is used to demonstrate the implementation of the algorithm and encouraging results are obtained.

Probabilistic DHP adaptive critic for nonlinear stochastic control systems

Following the recently developed algorithms for fully probabilistic control design for general dynamic stochastic systems (Herzallah & Káarnáy, 2011; Kárný, 1996), this paper presents the solution to the probabilistic dual heuristic programming (DHP) adaptive critic method (Herzallah & Káarnáy, 2011) and randomized control algorithm for stochastic nonlinear dynamical systems. The purpose of the randomized control input design is to make the joint probability density function of the closed loop system as close as possible to a predetermined ideal joint probability density function. This paper completes the previous work (Herzallah & Kárnáy, 2011; Kárný, 1996) by formulating and solving the fully probabilistic control design problem on the more general case of nonlinear stochastic discrete time systems. A simulated example is used to demonstrate the use of the algorithm and encouraging results have been obtained.

Influence of QT correction on temporal and amplitude features for human identification via ECG

Identification of humans via ECG is being increasingly studied because it can have several advantages over the traditional biometric identification techniques. However, difficulties arise because of the heartrate variability. In this study we analysed the influence of QT interval correction on the performance of an identification system based on temporal and amplitude features of ECG. In particular we tested MLP, Naive Bayes and 3-NN classifiers on the Fantasia database. Results indicate that QT correction can significantly improve the overall system performance. © 2013 IEEE.

Generalised Riccati solution and pinning control of complex stochastic networks

This paper considers the global synchronisation of a stochastic version of coupled map lattices networks through an innovative stochastic adaptive linear quadratic pinning control methodology. In a stochastic network, each state receives only noisy measurement of its neighbours' states. For such networks we derive a generalised Riccati solution that quantifies and incorporates uncertainty of the forward dynamics and inverse controller in the derivation of the stochastic optimal control law. The generalised Riccati solution is derived using the Lyapunov approach. A probabilistic approximation type algorithm is employed to estimate the conditional distributions of the state and inverse controller from historical data and quantifying model uncertainties. The theoretical derivation is complemented by its validation on a set of representative examples.

Analysis and identification of spamming behaviors in Sina Weibo microblog

Spamming has been a widespread problem for social networks. In recent years there is an increasing interest in the analysis of anti-spamming for microblogs, such as Twitter. In this paper we present a systematic research on the analysis of spamming in Sina Weibo platform, which is currently a dominant microblogging service provider in China. Our research objectives are to understand the specific spamming behaviors in Sina Weibo and find approaches to identify and block spammers in Sina Weibo based on spamming behavior classifiers. To start with the analysis of spamming behaviors we devise several effective methods to collect a large set of spammer samples, including uses of proactive honeypots and crawlers, keywords based searching and buying spammer samples directly from online merchants. We processed the database associated with these spammer samples and interestingly we found three representative spamming behaviors: Aggressive advertising, repeated duplicate reposting and aggressive following. We extract various features and compare the behaviors of spammers and legitimate users with regard to these features. It is found that spamming behaviors and normal behaviors have distinct characteristics. Based on these findings we design an automatic online spammer identification system. Through tests with real data it is demonstrated that the system can effectively detect the spamming behaviors and identify spammers in Sina Weibo.

Maximising the efficiency of logistics operations with radio frequency identification technology

Radio frequency identification (RFID) technology has gained increasing popularity in businesses to improve operational efficiency and maximise costs saving. However, there is a gap in the literature exploring the enhanced use of RFID to substantially add values to the supply chain operations, especially beyond what the RFID vendors could offer. This paper presents a multi-agent system, incorporating RFID technology, aimed at fulfilling the gap. The system is developed to model supply chain activities (in particular, logistics operations) and is comprised of autonomous and intelligent agents representing the key entities in the supply chain. With the advanced characteristics of RFID incorporated, the agent system examines ways logistics operations (i.e. distribution network) particular) can be efficiently reconfigured and optimised in response to dynamic changes in the market, production and at any stage in the supply chain. © 2012 IEEE.

Dynamics of cholesteric liquid crystals in the presence of a random magnetic field:stochastic dynamics of cholesteric liquid crystal

Based on dynamic renormalization group techniques, this letter analyzes the effects of external stochastic perturbations on the dynamical properties of cholesteric liquid crystals, studied in presence of a random magnetic field. Our analysis quantifies the nature of the temperature dependence of the dynamics; the results also highlight a hitherto unexplored regime in cholesteric liquid crystal dynamics. We show that stochastic fluctuations drive the system to a second-ordered Kosterlitz-Thouless phase transition point, eventually leading to a Kardar-Parisi-Zhang (KPZ) universality class. The results go beyond quasi-first order mean-field theories, and provides the first theoretical understanding of a KPZ phase in distorted nematic liquid crystal dynamics.

Stochastic anti-resonance in a fibre Raman amplifier

Stochastic anti-resonance, that is resonant enhancement of randomness caused by polarization mode beatings, is analyzed both numerically and analytically on an example of fibre Raman amplifier with randomly varying birefringence. As a result of such anti-resonance, the polarization mode dispersion growth causes an escape of the signal state of polarization from a metastable state corresponding to the pulling of the signal to the pump state of polarization.This phenomenon reveals itself in abrupt growth of gain fluctuations as well as in dropping of Hurst parameter and Kramers length characterizing long memory in a system and noise induced escape from the polarization pulling state. The results based on analytical multiscale averaging technique agree perfectly with the numerical data obtained by direct numerical simulations of underlying stochastic differential equations. This challenging outcome would allow replacing the cumbersome numerical simulations for real-world extra-long high-speed communication systems.

Radio frequency identification and its application in e-commerce

This chapter presents Radio Frequency Identification (RFID), which is one of the Automatic Identification and Data Capture (AIDC) technologies (Wamba and Boeck, 2008) and discusses the application of RFID in E-Commerce. Firstly RFID is defined and the tag and reader components of the RFID system are explained. Then historical context of RFID is briefly discussed. Next, RFID is contrasted with other AIDC technologies, especially the use of barcodes which are commonly applied in E-Commerce. Lastly, RFID applications in E-Commerce are discussed with the focus on achievable benefits and obstacles to successful applications of RFID in E-Commerce, and ways to alleviate them.