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%).
Copper zinc tin sulfide selenide, Cu2 ZnSn(S1−x Se x)4 , absorbers are promising earth-abundant and environmentally benign materials for low-cost photovoltaic applications. This study investigates the structural and optical properties of Cu 2 ZnSn(S1−x Se x)4 nanostructured thin films prepared by pulsed laser deposition using melt-quenched targets with selenium compositions x = 0.0–1.0. X-ray diffraction revealed that films with low selenium content remained amorphous, whereas higher selenium incorporation promoted the formation of polycrystalline kesterite–stannite phases with preferred orientations along (112), (200), (220), and (312). The crystallite size increased from 12.3 to 17.9 nm as selenium reached x = 1.0, indicating enha
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Clean energy applications widely recognize Proton Exchange Membrane Fuel Cells (PEMFCs) for their high efficiency and environmental compatibility. Accurate parameter identification of PEMFC models is essential for enhancing system performance and reliability, particularly under dynamic operating conditions. This paper presents a novel optimization-based approach called Heterogeneous Comprehensive Learning-Bald Eagle Search (HCLBES) with enhanced exploration and exploitation capabilities for the effective modeling of PEMFC. The algorithm combines the exploration strength of the Bald Eagle Search with comprehensive learning and heterogeneity mechanisms to achieve a balanced global and local search space. In this algorithm, the number
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Alloys from AgSb(SxSe1-x)2 with different compositions were prepared using quenching from the melt . This was done by put the appropriate amount of Ag, Sb,S and Se in an evaluated quartz ampoule , sealed and left at oven in temperature 1273 for 5 hours. Thin films with different composition were deposited by pulsed deposition technique PLD onto glass substrates at ambient temperature . This paper concerned on the investigate effect of composition on structural morphology, and electrical properties. The structure and morphology of the prepoared thin films were checked using X–ray diffraction and atomic force microscope. The D.C conductivity of the AgSb(SxSe1-x)2thin films with various x content was measured
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In this paper, a method is proposed to increase the compression ratio for the color images by
dividing the image into non-overlapping blocks and applying different compression ratio for these
blocks depending on the importance information of the block. In the region that contain important
information the compression ratio is reduced to prevent loss of the information, while in the
smoothness region which has not important information, high compression ratio is used .The
proposed method shows better results when compared with classical methods(wavelet and DCT).
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