An Efficient Classification of Hyperspectral Remotely Sensed Data Using Support Vector Machine

This work present an efficient hardware architecture of Support Vector Machine (SVM) for the classification of Hyperspectral remotely sensed data using High Level Synthesis (HLS) method. The high classification time and power consumption in traditional classification of remotely sensed data is the main motivation for this work. Therefore presented work helps to classify the remotely sensed data in real-time and to take immediate action during the natural disaster. An embedded based SVM is designed and implemented on Zynq SoC for classification of hyperspectral images. The data set of remotely sensed data are tested on different platforms and the performance is compared with existing works. Novelty in our proposed work is extend the HLS based FPGA implantation to the onboard classification system in remote sensing. The experimental results for selected data set from different class shows that our architecture on Zynq 7000 implementation generates a delay of 11.26 µs and power consumption of 1.7 Watts, which is extremely better as compared to other Field Programmable Gate Array (FPGA) implementation using Hardware description Language (HDL)  and Central Processing Unit (CPU) implementation

Antimicrobial lubricant formulations containing poly(hydroxybenzene)-trimethoprim conjugates synthesized by tyrosinase

Poly(hydroxybenzene)-trimethoprim conjugates were prepared using methylparaben as substrate of the oxida- tive enzyme tyrosinase. MALDI-TOF MS analysis showed that the enzymatic oxidation of methylparaben alone leads to the poly(hydroxybenzene) formation. In the presence of tri- methoprim, the methylparaben tyrosinase oxidation leads poly(hydroxybenzene)-trimethoprim conjugates. All of these compounds were incorporated into lubricant hydroxyethyl cellulose/glycerol mixtures. Poly(hydroxybenzene)-trimetho- prim conjugates were the most effective phenolic structures against the bacterial growth reducing by 96 and 97 % of Escherichia coli and Staphylococcus epidermidis suspen- sions, respectively (after 24 h). A novel enzymatic strategy to produce antimicrobial poly(hydroxybenzene)-antibiotic conjugates is proposed here for a wide range of applications on the biomedical field.The authors Idalina Gonçalves and Cláudia Botelho would like to acknowledge the NOVO project (FP7-HEALTH- 2011.2.3.1- 5) for funding. Loïc Hilliou acknowledges the financial support by FCT – Foundation for Science and Technology, Portugal (501100001871), through Grant PEst-C/CTM/LA0025/2013 - Strategic Project - LA 25 - 2013–2014, and by Programa Operacional Regional do Norte (ON.2) through the project BMatepro – Optimizing Materials and Processes^, with reference NORTE-07-0124-FEDER-000037 FEDER COMPETE