We present a deterministic algorithm for large-scale VLSI module placement. Following the less flexibility first (LFF) principle,we simulate a manual packing process in which the concept of placement by stages is in...We present a deterministic algorithm for large-scale VLSI module placement. Following the less flexibility first (LFF) principle,we simulate a manual packing process in which the concept of placement by stages is introduced to reduce the overall evaluation complexity. The complexity of the proposed algorithm is (N1 + N2 ) × O( n^2 ) + N3× O(n^4lgn) ,where N1, N2 ,and N3 denote the number of modules in each stage, N1 + N2 + N3 = n, and N3〈〈 n. This complexity is much less than the original time complexity of O(n^5lgn). Experimental results indicate that this approach is quite promising.展开更多
Influence of silicon oxide(SiO_2) and aluminum oxide(Al_2O_3) nanoparticles on the stability of nanoparticles and sodium dodecyl sulfate(SDS) mixed solution foams was studied at bulk and bubble-scale. Foam apparent vi...Influence of silicon oxide(SiO_2) and aluminum oxide(Al_2O_3) nanoparticles on the stability of nanoparticles and sodium dodecyl sulfate(SDS) mixed solution foams was studied at bulk and bubble-scale. Foam apparent viscosity was also determined in Hele-Shaw cell In order to investigate the foam performance at static and dynamic conditions. Results show that the maximum adsorption of surfactant on the nanoparticles occurs at 3 wt% surfactant concentration. Foam stability increases while the foamability decreases with the increasing nanoparticle concentration. However, optimum nanoparticle concentration corresponding to maximum foam stability was obtained at 1.0 wt% nanoparticle concentration for the hydrophilic SiO_2/SDS and Al_2O_3/SDS foams. Foam performance was enhanced with increasing nanoparticles hydrophobicity. Air-foams were generally more stable than CO_2 foams.Foam apparent viscosity increased in the presence of nanoparticles from 20.34 mPa·s to 84.84 mPa·s while the film thickness increased from 27.5 μm to 136 μm. This study suggests that the static and dynamic stability of conventional foams could be improved with addition of appropriate concentration of nanoparticles into the surfactant solution. The nanoparticles improve foam stability by their adsorption and aggregation at the foam lamellae to increase film thickness and dilational viscoelasticity. This prevents liquid drainage and film thinning and improves foam stability both at the bulk and bubble scale.展开更多
Linear programming models have been widely used in input-output analysis for analyzing the interdependence of industries in economics and in environmental science.In these applications,some of the entries of the coeff...Linear programming models have been widely used in input-output analysis for analyzing the interdependence of industries in economics and in environmental science.In these applications,some of the entries of the coefficient matrix cannot be measured physically or there exists sampling errors.However,the coefficient matrix can often be low-rank.We characterize the robust counterpart of these types of linear programming problems with uncertainty set described by the nuclear norm.Simulations for the input-output analysis show that the new paradigm can be helpful.展开更多
文摘We present a deterministic algorithm for large-scale VLSI module placement. Following the less flexibility first (LFF) principle,we simulate a manual packing process in which the concept of placement by stages is introduced to reduce the overall evaluation complexity. The complexity of the proposed algorithm is (N1 + N2 ) × O( n^2 ) + N3× O(n^4lgn) ,where N1, N2 ,and N3 denote the number of modules in each stage, N1 + N2 + N3 = n, and N3〈〈 n. This complexity is much less than the original time complexity of O(n^5lgn). Experimental results indicate that this approach is quite promising.
基金the Ministry of Higher Education(Vot no.Q.J130000.2542.08H61)Universiti Teknologi(UTM)Malaysia,for supporting this research through research management grant
文摘Influence of silicon oxide(SiO_2) and aluminum oxide(Al_2O_3) nanoparticles on the stability of nanoparticles and sodium dodecyl sulfate(SDS) mixed solution foams was studied at bulk and bubble-scale. Foam apparent viscosity was also determined in Hele-Shaw cell In order to investigate the foam performance at static and dynamic conditions. Results show that the maximum adsorption of surfactant on the nanoparticles occurs at 3 wt% surfactant concentration. Foam stability increases while the foamability decreases with the increasing nanoparticle concentration. However, optimum nanoparticle concentration corresponding to maximum foam stability was obtained at 1.0 wt% nanoparticle concentration for the hydrophilic SiO_2/SDS and Al_2O_3/SDS foams. Foam performance was enhanced with increasing nanoparticles hydrophobicity. Air-foams were generally more stable than CO_2 foams.Foam apparent viscosity increased in the presence of nanoparticles from 20.34 mPa·s to 84.84 mPa·s while the film thickness increased from 27.5 μm to 136 μm. This study suggests that the static and dynamic stability of conventional foams could be improved with addition of appropriate concentration of nanoparticles into the surfactant solution. The nanoparticles improve foam stability by their adsorption and aggregation at the foam lamellae to increase film thickness and dilational viscoelasticity. This prevents liquid drainage and film thinning and improves foam stability both at the bulk and bubble scale.
基金supported by National Social Science Foundation of China (Grant No. 11BGL053)National Natural Science Foundation of China (Grant Nos. 11101434,10971122 and 11101274)+4 种基金Scientific and Technological Projects of Shandong Province (Grant No. 2009GG10001012)Excellent Young Scientist Foundation of Shandong Province (Grant No. 2010BSE06047)the Doctoral Program of Higher Education of China (Grant No. 20110073120069)Shandong Province Natural Science Foundation (Grant No. ZR2012GQ004)Independent Innovation Foundation of Shandong University (Grant No. 12120083399170)
文摘Linear programming models have been widely used in input-output analysis for analyzing the interdependence of industries in economics and in environmental science.In these applications,some of the entries of the coefficient matrix cannot be measured physically or there exists sampling errors.However,the coefficient matrix can often be low-rank.We characterize the robust counterpart of these types of linear programming problems with uncertainty set described by the nuclear norm.Simulations for the input-output analysis show that the new paradigm can be helpful.