Increased downscaling of CMOS circuits with respect to feature size and threshold voltage has a result of dramatically increasing in leakage current. So, leakage power reduction is an important design issue for active and standby modes as long as the technology scaling increased. In this paper, a simultaneous active and standby energy optimization methodology is proposed for 22 nm sub-threshold CMOS circuits. In the first phase, we investigate the dual threshold voltage design for active energy per cycle minimization. A slack based genetic algorithm is proposed to find the optimal reverse body bias assignment to set of noncritical paths gates to ensure low active energy per cycle with the maximum allowable frequency at the optimal supply voltage. The second phase, determine the optimal reverse body bias that can be applied to all gates for standby power optimization at the optimal supply voltage determined from the first phase. Therefore, there exist two sets of gates and two reverse body bias values for each set. The reverse body bias is switched between these two values in response to the mode of operation. Experimental results are obtained for some ISCAS-85 benchmark circuits such as 74L85, 74283, ALU74181, and 16 bit RCA. The optimized circuits show significant energy saving ranged (from 14.5% to 42.28%) and standby power saving ranged (from 62.8% to 67%).
An innovative desalination method called electrosorption or capacitive deionization (CDI) has significant benefits for wastewater treatment. This process is performed by using a carbon fiber electrode as a working electrode to remove hexavalent chromium ions from an aqueous solution. The pH, NaCl concentration, and cell voltage were optimized using the Box-Behnken experimental design (BDD) in response surface methodology (RSM) to study the effects and interactions of selected variables. To attain the relationship between the process variables and chromium removal, the experimental data were subjected to an analysis of variance and fitted with a quadratic model. The optimum conditions to remove Cr(VI) ions were: pH of 2, a cell voltage of 4.
... Show MoreIn today's world, the science of bioinformatics is developing rapidly, especially with regard to the analysis and study of biological networks. Scientists have used various nature-inspired algorithms to find protein complexes in protein-protein interaction (PPI) networks. These networks help scientists guess the molecular function of unknown proteins and show how cells work regularly. It is very common in PPI networks for a protein to participate in multiple functions and belong to many complexes, and as a result, complexes may overlap in the PPI networks. However, developing an efficient and reliable method to address the problem of detecting overlapping protein complexes remains a challenge since it is considered a complex and har
... Show MoreIn this paper a comparison of the experimental of evacuated tube solar water heater systems with and without mirror flat reflector. The aim of using the reflector to improve thermal efficiency, and the data gathered which are (temperature, solar irradiation and time) for three days were compared. the results from compared data the temperature lower increase in evacuated tube solar water heater system without reflector than the temperature increase in evacuated tube solar water heater system with reflector .The results show (53, 39, 35) % for three days respectively that the evacuated tube solar water heater system with reflector has higher thermal efficiencies than the results (47, 28, 30) % for three days respectively thermal efficiencies
... Show MoreThis study was attempted to determine optimum conditions, for Glutathione s-Transferase enzyme, in sera of three groups diabetic patients type1 depending on duration of disease without complications compared with control group. The aim of this study was to find optimum conditions were determined such as (pH, Substrate Concentration, Temperature, Incubation time, Enzyme concentration, and effect of(0.15M)(0.25M) of mono divalent compounds). And to find the kinetics parameters in the three groups of diabetic patients when compared with control. It was found optimum pH(8.5,4.5,2.5,6.5).Temperatures(20cº,40cº,50cº,30cº). Incubation times (7min, 4min, 4min, 5min) substrate concentrations (12µl, 10µl, 5µl, 10µl) enzyme concentra
... Show MoreThe energy aimed at examining the mode of energy drinks consumption among athletes in
Baghdad and assessing their drinks were spread greatly among the athletes and students. This
study impression toward such drinks. The study sample comprised of 102 mal athletes aged
between 19-27 years and selected randomly .The obtained results showed that football was
most practiced among the test samples at 40.54% based on twice daily .The athletes
consumed one can each day at 41.18% .As the data on energy drinks was supplied from
friends .The prefared period for drinking was before or during exercise .The athletes thought
that there products can provide energy ,vitamins ,tell ale materials ,does not affect
appetite.The most f
The method of predicting the electricity load of a home using deep learning techniques is called intelligent home load prediction based on deep convolutional neural networks. This method uses convolutional neural networks to analyze data from various sources such as weather, time of day, and other factors to accurately predict the electricity load of a home. The purpose of this method is to help optimize energy usage and reduce energy costs. The article proposes a deep learning-based approach for nonpermanent residential electrical ener-gy load forecasting that employs temporal convolutional networks (TCN) to model historic load collection with timeseries traits and to study notably dynamic patterns of variants amongst attribute par
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