The modified Max-Log-MAP turbo decoding algorithm by extrinsic information scaling for wireless applications

The iterative nature of turbo-decoding algorithms increases their complexity compare to conventional FEC decoding algorithms. Two iterative decoding algorithms, Soft-Output-Viterbi Algorithm (SOVA) and Maximum A posteriori Probability (MAP) Algorithm require complex decoding operations over several iteration cycles. So, for real-time implementation of turbo codes, reducing the decoder complexity while preserving bit-error-rate (BER) performance is an important design consideration. In this chapter, a modification to the Max-Log-MAP algorithm is presented. This modification is to scale the extrinsic information exchange between the constituent decoders. The remainder of this chapter is organized as follows: An overview of the turbo encoding and decoding processes, the MAP algorithm and its simplified versions the Log-MAP and Max-Log-MAP algorithms are presented in section 1. The extrinsic information scaling is introduced, simulation results are presented, and the performance of different methods to choose the best scaling factor is discussed in Section 2. Section 3 discusses trends and applications of turbo coding from the perspective of wireless applications.

In-situ development of self-defensive antibacterial biomaterials: phenol-g-keratin-EC based bio-composites with characteristics for biomedical applications

Recently, the development of highly inspired biomaterials with multi-functional characteristics has gained considerable attention, especially in biomedical, and other health-related areas of the modern world. It is well-known that the lack of antibacterial potential has significantly limited biomaterials for many challenging applications such as infection free wound healing and/or tissue engineering etc. In this perspective, herein, a series of novel bio-composites with natural phenols as functional entities and keratin-EC as a base material were synthesised by laccase-assisted grafting. Subsequently, the resulting composites were removed from their respective casting surfaces, critically evaluated for their antibacterial and biocompatibility features and information is also given on their soil burial degradation profile. In-situ synthesised phenol-g-keratin-EC bio-composites possess strong anti-bacterial activity against Gram-positive and Gram-negative bacterial strains i.e., B. subtilis NCTC 3610, P. aeruginosa NCTC 10662, E. coli NTCT 10418 and S. aureus NCTC 6571. More specifically, 10HBA-g-keratin-EC and 20T-g-keratin-EC composites were 100% resistant to colonisation against all of the aforementioned bacterial strains, whereas, 15CA-g-keratin-EC and 15GA-g-keratin-EC showed almost negligible colonisation up to a variable extent. Moreover, at various phenolic concentrations used, the newly synthesised composites remained cytocompatible with human keratinocyte-like HaCaT, as an obvious cell ingrowth tendency was observed and indicated by the neutral red dye uptake assay. From the degradation point of view, an increase in the degradation rate was recorded during their soil burial analyses. Our investigations could encourage greater utilisation of natural materials to develop bio-composites with novel and sophisticated characteristics for potential applications.

Perceptual user interface framework for immersive information retrieval environments (An experimental framework for testing and rapid iteration)

The use of perceptual inputs is an emerging area within HCI that suggests a developing Perceptual User Interface (PUI) that may prove advantageous for those involved in mobile serious games and immersive social network environments. Since there are a large variety of input devices, software platforms, possible interactions, and myriad ways to combine all of the above elements in pursuit of a PUI, we propose in this paper a basic experimental framework that will be able to standardize study of the wide range of interactive applications for testing efficacy in learning or information retrieval and also suggest improvements to emerging PUIs by enabling quick iteration. This rapid iteration will start to define a targeted range of interactions that will be intuitive and comfortable as perceptual inputs, and enhance learning and information retention in comparison to traditional GUI systems. The work focuses on the planning of the technical development of two scenarios, and the first steps in developing a framework to evaluate these and other PUIs for efficacy and pedagogy.