Computing-in-memory(CIM)has been a promising candidate for artificial-intelligent applications thanks to the absence of data transfer between computation and storage blocks.Resistive random access memory(RRAM)based CI...Computing-in-memory(CIM)has been a promising candidate for artificial-intelligent applications thanks to the absence of data transfer between computation and storage blocks.Resistive random access memory(RRAM)based CIM has the advantage of high computing density,non-volatility as well as high energy efficiency.However,previous CIM research has predominantly focused on realizing high energy efficiency and high area efficiency for inference,while little attention has been devoted to addressing the challenges of on-chip programming speed,power consumption,and accuracy.In this paper,a fabri-cated 28 nm 576K RRAM-based CIM macro featuring optimized on-chip programming schemes is proposed to address the issues mentioned above.Different strategies of mapping weights to RRAM arrays are compared,and a novel direct-current ADC design is designed for both programming and inference stages.Utilizing the optimized hybrid programming scheme,4.67×programming speed,0.15×power saving and 4.31×compact weight distribution are realized.Besides,this macro achieves a normalized area efficiency of 2.82 TOPS/mm2 and a normalized energy efficiency of 35.6 TOPS/W.展开更多
Abstract Production planning under uncertainty is considered as one of the most important problems in plant-wide optimization. In this article, first, a stochastic programming model with uniform distribution assumptio...Abstract Production planning under uncertainty is considered as one of the most important problems in plant-wide optimization. In this article, first, a stochastic programming model with uniform distribution assumption is developed for refinery production planning under demand uncertainty, and then a hybrid programming model incorporating the linear programming model with the stochastic programming one by a weight factor is proposed. Subsequently, piecewise linear approximation functions are derived and applied to solve the hybrid programming model-under uniform distribution assumption. Case studies show that the linear approximation algorithm is effective to solve.the hybrid programming model, along with an error≤0.5% when the deviatiorgmean≤20%. The simulation results indicate that the hybrid programming model with an appropriate weight factor （0.1-0.2） can effectively improve the optimal operational strategies under demand uncertainty, achieving higher profit than the linear programming model and the stochastic programming one with about 1.3% and 0.4% enhancement, respectavely.展开更多
Matlab has a high performance at engineering calculation.C# is good at interface development.Combining their advantages together,hybrid programming with Matlab and C # will help to improve the reliability analysis sof...Matlab has a high performance at engineering calculation.C# is good at interface development.Combining their advantages together,hybrid programming with Matlab and C # will help to improve the reliability analysis software efficiency and accuracy significantly.Procedures of hybrid programming with Matlab and C# in reliability analysis software are introduced in this paper.Finally a mathematical problem is tested to verify the feasibility of this programming method.展开更多
Male sterility induced by a chemical hybridization agent （CHA） is an important tool for utilizing crop heterosis. Leaves, especially the flag leaves, as CHA initial recipients play a decisive role in inducing male s...Male sterility induced by a chemical hybridization agent （CHA） is an important tool for utilizing crop heterosis. Leaves, especially the flag leaves, as CHA initial recipients play a decisive role in inducing male sterility. To investigate effects of different treatment times of CHA-SQ-1 used, morphological, biochemical and physiological responses of wheat flag leaves were detected in thistudy. CHA induced programmed cell death （PCD） as shown in terminal deoxynucleotidyl transferase-mediated dUTP nick end-labelling （TUNEL） and DNA laddering analysis. In the early phase, CHA-SQ-1 trig- gered organelle changes arid PCD in wheat leaves accompanied by excess production of reactive oxygen species （O2- and H202） and down-regulation of the activities of superoxide dismutase （SOD）, catalase （CAT） and guaiacol peroxidase （POD）. Meanwhile, leaf cell DNAs showed ladder-like patterns on agarose gel, indicating that CHA-SQ-1 led to the activation of the responsible endonuclease. The oxidative stress assays showed that lipid peroxidation was strongly activated and photosynthesis was obviously inhibited in SQ-l-induced leaves. However, CHA contents in wheat leaves gradually reduced along with the time CHA-SQ-1 applied. Young flags returned to an oxidative/antioxidative balance and ultimately developed into mature green leaves. These results provide explanation of the relations between PCD and anther abortion and practical application of CHA for hybrid breeding.展开更多
The purpose of this paper is to develop an implementable strategy of brake energy recovery for a parallel hydraulic hybrid bus. Based on brake process analysis, a dynamic programming algorithm of brake energy recovery...The purpose of this paper is to develop an implementable strategy of brake energy recovery for a parallel hydraulic hybrid bus. Based on brake process analysis, a dynamic programming algorithm of brake energy recovery is established. And then an implementable strategy of brake energy recovery is proposed by the constraint variable trajectories analysis of the dynamic programming algorithm in the typical urban bus cycle. The simulation results indicate the brake energy recovery efficiency of the accumulator can reach 60% in the dynamic programming algorithm. And the hydraulic hybrid system can output braking torque as much as possible.Moreover, the accumulator has almost equal efficiency of brake energy recovery between the implementable strategy and the dynamic programming algorithm. Therefore, the implementable strategy is very effective in improving the efficiency of brake energy recovery.The road tests show the fuel economy of the hydraulic hybrid bus improves by 22.6% compared with the conventional bus.展开更多
The goal of this work is to develop a hybrid electric vehicle model that is suitable for use in a dynamic programming algorithm that provides the benchmark for optimal control of the hybrid powertrain. The benchmark a...The goal of this work is to develop a hybrid electric vehicle model that is suitable for use in a dynamic programming algorithm that provides the benchmark for optimal control of the hybrid powertrain. The benchmark analysis employs dynamic programming by backward induction to determine the globally optimal solution by solving the energy management problem starting at the final timestep and proceeding backwards in time. This method requires the development of a backwards facing model that propagates the wheel speed of the vehicle for the given drive cycle through the driveline components to determine the operating points of the powertrain. Although dynamic programming only searches the solution space within the feasible regions of operation, the benchmarking model must be solved for every admissible state at every timestep leading to strict requirements for runtime and memory. The backward facing model employs the quasi-static assumption of powertrain operation to reduce the fidelity of the model to accommodate these requirements. Verification and validation testing of the dynamic programming algorithm is conducted to ensure successful operation of the algorithm and to assess the validity of the determined control policy against a high-fidelity forward-facing vehicle model with a percent difference of fuel consumption of 1.2%. The benchmark analysis is conducted over multiple drive cycles to determine the optimal control policy that provides a benchmark for real-time algorithm development and determines control trends that can be used to improve existing algorithms. The optimal combined charge sustaining fuel economy of the vehicle is determined by the dynamic programming algorithm to be 32.99 MPG, a 52.6% increase over the stock 3.6 L 2019 Chevrolet Blazer.展开更多
通信感知一体化(Integrated Sensing and Communication,ISAC)系统可以将通信感知功能有机融合,以取得更高的频谱效率和硬件利用率,但传统的大规模集中式天线阵列在平面波假设下无法提供距离维增益,且其混合波束赋形设计为非凸优化问题...通信感知一体化(Integrated Sensing and Communication,ISAC)系统可以将通信感知功能有机融合,以取得更高的频谱效率和硬件利用率,但传统的大规模集中式天线阵列在平面波假设下无法提供距离维增益,且其混合波束赋形设计为非凸优化问题,仍是具有挑战性的难题。为此,提出了一种基于子阵列的混合波束赋形设计方案,在较低的硬件复杂度下通过扩展球面波区域范围提供距离维增益,以在满足感知性能约束和发射功率预算的前提下最大化通信速率。首先提出了一种基于分式规划和最优化最小化方法的算法,将非凸优化问题转化为凸问题后迭代求解得到一个联合波束赋形矩阵;进而提出一种基于流形优化和最小二乘法的算法,迭代求解后将其分解为数字/模拟波束赋形矩阵。仿真结果表明,基于子阵列的算法相较于集中式阵列能够获得更多的距离维信息和感知自由度,通信性能提升40%,且流形优化后混合波束赋形方案能够很好地逼近联合优化的数字波束赋形方案的性能。展开更多
针对城市居民区回收箱布局规划和路径优化问题,首先构建居民区回收箱数量与人口、回收频率、回收阈值的线性函数,并构建双层优化模型,回收总利润最大化作为上层目标,运输成本最小化作为下层目标。其次,为求解具有NP-hard特征的新模型,...针对城市居民区回收箱布局规划和路径优化问题,首先构建居民区回收箱数量与人口、回收频率、回收阈值的线性函数,并构建双层优化模型,回收总利润最大化作为上层目标,运输成本最小化作为下层目标。其次,为求解具有NP-hard特征的新模型,设计加入团体学习算子和自适应选择策略的人类学习优化算法,并与禁忌搜索算法嵌套构建混合人类学习算法(hybrid human learning optimization algorithm,HHLO)。再次,采用不同规模算例,并将新算法与基本人类学习算法、遗传算法、自适应粒子群算法、红嘴蓝鹊算法进行对比分析,验证了模型的可行性和算法的有效性。最后,通过上海杨浦区某实例进行灵敏度分析,探讨回收箱容量、分时定价策略和分区定价策略对回收中心总利润与居民满意度的影响。展开更多
对已有梯级水电站进行融合改造,增建抽水蓄能机组形成梯级混合式抽水蓄能电站,是加快抽水蓄能发展的有效途径之一。梯级混合式抽水蓄能电站相较于常规梯级电站,新增具备抽水运行工况,相较于传统抽水蓄能电站,又具有更加复杂梯级水力联系...对已有梯级水电站进行融合改造,增建抽水蓄能机组形成梯级混合式抽水蓄能电站,是加快抽水蓄能发展的有效途径之一。梯级混合式抽水蓄能电站相较于常规梯级电站,新增具备抽水运行工况,相较于传统抽水蓄能电站,又具有更加复杂梯级水力联系,灵活的运行模式需要更为精细化的调度建模方法。为探索其典型调峰运行模式,提出了梯级混合式抽水蓄能电站短期调峰优化模型。该模型以电网剩余负荷峰谷差最小为目标,以机组为最小调度单元,针对不同类型机组的抽-发运行工况采用差异化建模。在模型求解方面,通过线性转换方法将原有非线性模型转化为混合整数线性规划(mixed integer linear programming,MILP)模型,然后在JAVA环境中运用CPLEX数学工具进行求解。以西南某梯级水电站为实例的分析结果表明,梯级混合式抽水蓄能电站相较于常规梯级电站电网剩余负荷峰谷差减少4.6%。展开更多
To implement structural hybrid simulation independent of the control system of any testing equipment in civil engineering, an external command control approach is put forward. Several setup technologies and the corres...To implement structural hybrid simulation independent of the control system of any testing equipment in civil engineering, an external command control approach is put forward. Several setup technologies and the corresponding API approaches are investigated to simultaneously combine numerical simulation with physical testing. Hybrid program technology is put forward and described in detail, using Visual C++ program to effectively and accurately control testing equipment and MATLAB program to implement numerical simulation with easy extension. The control program of testing equipment and numerical simulation program are integrated by calling MATLAB engine in Visual C++. A hybrid simulation about a full-scale six-story masonry structure is carried out. The testing results manifest that the external command control approach has the versatility because of simple hardware connection and control program independent on control software of testing equipment; powerful program function of Visual C++ and flexible program of MATLAB are integrated by hybrid program technology; hybrid simulation system provides a realistic and cost-effective testing platform that enables earthquake engineer researchers to accurately and efficiently capture the seismic performance of large or complex structures without having to carry out physical testing of the entire structure.展开更多
基金supported in part by the National Natural Science Foundation of China (62422405, 62025111,62495100, 92464302)the STI 2030-Major Projects(2021ZD0201200)+1 种基金the Shanghai Municipal Science and Technology Major Projectthe Beijing Advanced Innovation Center for Integrated Circuits
文摘Computing-in-memory(CIM)has been a promising candidate for artificial-intelligent applications thanks to the absence of data transfer between computation and storage blocks.Resistive random access memory(RRAM)based CIM has the advantage of high computing density,non-volatility as well as high energy efficiency.However,previous CIM research has predominantly focused on realizing high energy efficiency and high area efficiency for inference,while little attention has been devoted to addressing the challenges of on-chip programming speed,power consumption,and accuracy.In this paper,a fabri-cated 28 nm 576K RRAM-based CIM macro featuring optimized on-chip programming schemes is proposed to address the issues mentioned above.Different strategies of mapping weights to RRAM arrays are compared,and a novel direct-current ADC design is designed for both programming and inference stages.Utilizing the optimized hybrid programming scheme,4.67×programming speed,0.15×power saving and 4.31×compact weight distribution are realized.Besides,this macro achieves a normalized area efficiency of 2.82 TOPS/mm2 and a normalized energy efficiency of 35.6 TOPS/W.
基金the Specialized Research Fund for Doctoral Program of Higher Education of China(20060003087)
文摘Abstract Production planning under uncertainty is considered as one of the most important problems in plant-wide optimization. In this article, first, a stochastic programming model with uniform distribution assumption is developed for refinery production planning under demand uncertainty, and then a hybrid programming model incorporating the linear programming model with the stochastic programming one by a weight factor is proposed. Subsequently, piecewise linear approximation functions are derived and applied to solve the hybrid programming model-under uniform distribution assumption. Case studies show that the linear approximation algorithm is effective to solve.the hybrid programming model, along with an error≤0.5% when the deviatiorgmean≤20%. The simulation results indicate that the hybrid programming model with an appropriate weight factor （0.1-0.2） can effectively improve the optimal operational strategies under demand uncertainty, achieving higher profit than the linear programming model and the stochastic programming one with about 1.3% and 0.4% enhancement, respectavely.
文摘Matlab has a high performance at engineering calculation.C# is good at interface development.Combining their advantages together,hybrid programming with Matlab and C # will help to improve the reliability analysis software efficiency and accuracy significantly.Procedures of hybrid programming with Matlab and C# in reliability analysis software are introduced in this paper.Finally a mathematical problem is tested to verify the feasibility of this programming method.
基金supported by the National High Technology Research and Development Program of China (2011AA10A106)the National Natural Science Foundation of China (31171611, 31371697)+1 种基金the Technological Innovation and Over Planning Projects of Shaanxi Province, China (2014KTZB02-01-02, 2011KTZB02-01-01)the Projects Opening Up New Function of Precision Instrument of Northwest A&F University, China (dysb130210)
文摘Male sterility induced by a chemical hybridization agent （CHA） is an important tool for utilizing crop heterosis. Leaves, especially the flag leaves, as CHA initial recipients play a decisive role in inducing male sterility. To investigate effects of different treatment times of CHA-SQ-1 used, morphological, biochemical and physiological responses of wheat flag leaves were detected in thistudy. CHA induced programmed cell death （PCD） as shown in terminal deoxynucleotidyl transferase-mediated dUTP nick end-labelling （TUNEL） and DNA laddering analysis. In the early phase, CHA-SQ-1 trig- gered organelle changes arid PCD in wheat leaves accompanied by excess production of reactive oxygen species （O2- and H202） and down-regulation of the activities of superoxide dismutase （SOD）, catalase （CAT） and guaiacol peroxidase （POD）. Meanwhile, leaf cell DNAs showed ladder-like patterns on agarose gel, indicating that CHA-SQ-1 led to the activation of the responsible endonuclease. The oxidative stress assays showed that lipid peroxidation was strongly activated and photosynthesis was obviously inhibited in SQ-l-induced leaves. However, CHA contents in wheat leaves gradually reduced along with the time CHA-SQ-1 applied. Young flags returned to an oxidative/antioxidative balance and ultimately developed into mature green leaves. These results provide explanation of the relations between PCD and anther abortion and practical application of CHA for hybrid breeding.
基金supported by Shanghai Science and Technology Committee(No.0904H155100)
文摘The purpose of this paper is to develop an implementable strategy of brake energy recovery for a parallel hydraulic hybrid bus. Based on brake process analysis, a dynamic programming algorithm of brake energy recovery is established. And then an implementable strategy of brake energy recovery is proposed by the constraint variable trajectories analysis of the dynamic programming algorithm in the typical urban bus cycle. The simulation results indicate the brake energy recovery efficiency of the accumulator can reach 60% in the dynamic programming algorithm. And the hydraulic hybrid system can output braking torque as much as possible.Moreover, the accumulator has almost equal efficiency of brake energy recovery between the implementable strategy and the dynamic programming algorithm. Therefore, the implementable strategy is very effective in improving the efficiency of brake energy recovery.The road tests show the fuel economy of the hydraulic hybrid bus improves by 22.6% compared with the conventional bus.
文摘The goal of this work is to develop a hybrid electric vehicle model that is suitable for use in a dynamic programming algorithm that provides the benchmark for optimal control of the hybrid powertrain. The benchmark analysis employs dynamic programming by backward induction to determine the globally optimal solution by solving the energy management problem starting at the final timestep and proceeding backwards in time. This method requires the development of a backwards facing model that propagates the wheel speed of the vehicle for the given drive cycle through the driveline components to determine the operating points of the powertrain. Although dynamic programming only searches the solution space within the feasible regions of operation, the benchmarking model must be solved for every admissible state at every timestep leading to strict requirements for runtime and memory. The backward facing model employs the quasi-static assumption of powertrain operation to reduce the fidelity of the model to accommodate these requirements. Verification and validation testing of the dynamic programming algorithm is conducted to ensure successful operation of the algorithm and to assess the validity of the determined control policy against a high-fidelity forward-facing vehicle model with a percent difference of fuel consumption of 1.2%. The benchmark analysis is conducted over multiple drive cycles to determine the optimal control policy that provides a benchmark for real-time algorithm development and determines control trends that can be used to improve existing algorithms. The optimal combined charge sustaining fuel economy of the vehicle is determined by the dynamic programming algorithm to be 32.99 MPG, a 52.6% increase over the stock 3.6 L 2019 Chevrolet Blazer.
文摘通信感知一体化(Integrated Sensing and Communication,ISAC)系统可以将通信感知功能有机融合,以取得更高的频谱效率和硬件利用率,但传统的大规模集中式天线阵列在平面波假设下无法提供距离维增益,且其混合波束赋形设计为非凸优化问题,仍是具有挑战性的难题。为此,提出了一种基于子阵列的混合波束赋形设计方案,在较低的硬件复杂度下通过扩展球面波区域范围提供距离维增益,以在满足感知性能约束和发射功率预算的前提下最大化通信速率。首先提出了一种基于分式规划和最优化最小化方法的算法,将非凸优化问题转化为凸问题后迭代求解得到一个联合波束赋形矩阵;进而提出一种基于流形优化和最小二乘法的算法,迭代求解后将其分解为数字/模拟波束赋形矩阵。仿真结果表明,基于子阵列的算法相较于集中式阵列能够获得更多的距离维信息和感知自由度,通信性能提升40%,且流形优化后混合波束赋形方案能够很好地逼近联合优化的数字波束赋形方案的性能。
文摘针对城市居民区回收箱布局规划和路径优化问题,首先构建居民区回收箱数量与人口、回收频率、回收阈值的线性函数,并构建双层优化模型,回收总利润最大化作为上层目标,运输成本最小化作为下层目标。其次,为求解具有NP-hard特征的新模型,设计加入团体学习算子和自适应选择策略的人类学习优化算法,并与禁忌搜索算法嵌套构建混合人类学习算法(hybrid human learning optimization algorithm,HHLO)。再次,采用不同规模算例,并将新算法与基本人类学习算法、遗传算法、自适应粒子群算法、红嘴蓝鹊算法进行对比分析,验证了模型的可行性和算法的有效性。最后,通过上海杨浦区某实例进行灵敏度分析,探讨回收箱容量、分时定价策略和分区定价策略对回收中心总利润与居民满意度的影响。
文摘对已有梯级水电站进行融合改造,增建抽水蓄能机组形成梯级混合式抽水蓄能电站,是加快抽水蓄能发展的有效途径之一。梯级混合式抽水蓄能电站相较于常规梯级电站,新增具备抽水运行工况,相较于传统抽水蓄能电站,又具有更加复杂梯级水力联系,灵活的运行模式需要更为精细化的调度建模方法。为探索其典型调峰运行模式,提出了梯级混合式抽水蓄能电站短期调峰优化模型。该模型以电网剩余负荷峰谷差最小为目标,以机组为最小调度单元,针对不同类型机组的抽-发运行工况采用差异化建模。在模型求解方面,通过线性转换方法将原有非线性模型转化为混合整数线性规划(mixed integer linear programming,MILP)模型,然后在JAVA环境中运用CPLEX数学工具进行求解。以西南某梯级水电站为实例的分析结果表明,梯级混合式抽水蓄能电站相较于常规梯级电站电网剩余负荷峰谷差减少4.6%。
基金Funded by National Natural Science Foundation of China under the Grant No.90715036Open Project of Jiangsu Key Laboratory of Structural Engineering (Grant No.ZD1004)Project of the Priority Academic Program Development of Jiangsu Higher Education Institutions (PAPD)
文摘To implement structural hybrid simulation independent of the control system of any testing equipment in civil engineering, an external command control approach is put forward. Several setup technologies and the corresponding API approaches are investigated to simultaneously combine numerical simulation with physical testing. Hybrid program technology is put forward and described in detail, using Visual C++ program to effectively and accurately control testing equipment and MATLAB program to implement numerical simulation with easy extension. The control program of testing equipment and numerical simulation program are integrated by calling MATLAB engine in Visual C++. A hybrid simulation about a full-scale six-story masonry structure is carried out. The testing results manifest that the external command control approach has the versatility because of simple hardware connection and control program independent on control software of testing equipment; powerful program function of Visual C++ and flexible program of MATLAB are integrated by hybrid program technology; hybrid simulation system provides a realistic and cost-effective testing platform that enables earthquake engineer researchers to accurately and efficiently capture the seismic performance of large or complex structures without having to carry out physical testing of the entire structure.
