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With progressing CMOS technology miniaturization, the leakage power consumption starts to dominate the dynamic power consumption. The recent technology trends have equipped the modern embedded processors with the several sleep states and reduced their overhead (energy/time) of the sleep transition. The dynamic voltage frequency scaling (DVFS) potential to save energy is diminishing due to efficient (low overhead) sleep states and increased static (leakage) power consumption. The state-of-the-art research on static power reduction at system level is based on assumptions that cannot easily be integrated into practical systems. We propose a novel enhanced race-to-halt approach (ERTH) to reduce the overall system energy consumption. The exhaustive simulations demonstrate theeffectiveness of our approach showing an improvement of up to 8 % over an existing work. Abstract-With progressing CMOS technology miniaturization, the leakage power consumption starts to dominate the dynamic power consumption. The recent technology trends have equipped the modern embedded processors with the several sleep states and reduced their overhead (energy/time) of the sleep transition. The dynamic voltage frequency scaling (DVFS) potential to save energy is diminishing due to efficient (low overhead) sleep states and increased static (leakage) power consumption. The state-ofthe-art research on static power reduction at system level is based on assumptions that cannot easily be integrated into practical systems. We propose a novel enhanced raceto-halt approach (ERTH) to reduce the overall system energy consumption. The exhaustive simulations demonstrate the effectiveness of our approach showing an improvement of up to 8 % over an existing work.

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Modern multicore processors for the embedded market are often heterogeneous in nature. One feature often available are multiple sleep states with varying transition cost for entering and leaving said sleep states. This research effort explores the energy efficient task-mapping on such a heterogeneous multicore platform to reduce overall energy consumption of the system. This is performed in the context of a partitioned scheduling approach and a realistic power model, which improves over some of the simplifying assumptions often made in the state-ofthe-art. The developed heuristic consists of two phases, in the first phase, tasks are allocated to minimise their active energy consumption, while the second phase trades off a higher active energy consumption for an increased ability to exploit savings through more efficient sleep states. Extensive simulations demonstrate the effectiveness of the approach.

The study describes the removal of fluoride from drinking water using modified immobilized activated alumina (MIAA) prepared by sol-gel method. The modification was done by adding a specific amount of alum during the sol formation step. The fluoride removal efficiency of MIAA was 1.35 times higher as compared to normal immobilized activated alumina. A batch adsorption study was performed as a function of adsorbent dose, contact time, stirring rate, and initial fluoride concentration. More than 90% removal of fluoride was achieved within 60 minutes of contact time. The adsorption potential of MIAA was compared with activated charcoal which showed that the removal efficiency was about 10% more than the activated charcoal. Both the Langmuir and Freundlich adsorption isotherms fitted well for the fluoride adsorption on MIAA with the regression coefficientR2of 0.99 and 0.98, respectively. MIAA can both be regenerated thermally and chemically. Adsorption experiments using MIAA were employed on real drinking water samples from a fluoride affected area. The study showed that modified immobilized activated alumina is an effective adsorbent for fluoride removal.

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Comparative photocatalytic degradation of polythene films was investigated with undoped and metal (Fe, Ag, and Fe/Ag mix) doped TiO2nanoparticles under three different conditions such as UV radiation, artificial light, and darkness. Prepared photocatalysts were characterized by XRD, SEM, and EDS techniques. Photocatalytic degradation of the polythene films was determined by monitoring their weight reduction, SEM analysis, and FTIR spectroscopy. Weight of PE films steadily decreased and led to maximum of 14.34% reduction under UV irradiation with Fe/Ag mix doped TiO2nanoparticles and maximum of 14.28% reduction under artificial light with Ag doped TiO2nanoparticles in 300 hrs. No weight reduction was observed under darkness. Results reveal that polythene-TiO2compositing with metal doping has the potential to degrade the polythene waste under irradiation without any pollution.