基于矩阵初等变换的量子可逆逻辑电路双向综合算法

基于矩阵初等变换,提出了量子可逆逻辑电路双向综合算法。该算法依据两数字间的汉明距离,通过交换矩阵行号或矩阵元素对量子可逆逻辑电路的矩阵进行初等行变换。在变换的过程中,利用邻接矩阵的电路转化规则,生成任意给定置换的量子可逆逻辑电路。与其它同类算法相比,由于不需要穷尽搜索,该算法的时空复杂度有大幅降低;又由于采用任意n量子扩展通用Toffoli门,该算法可综合任一置换(奇或偶置换)的量子可逆逻辑电路,并且电路中门的数量有所减少。     

A Normalization Method of Moment Invariants for 3D Objects on Different Manifolds

3D objects can be stored in computer of different describing ways, such as point set, polyline, polygonal surface and Euclidean distance map. Moment invariants of different orders may have the different magnitude. A method for normalizing moments of 3D objects is proposed, which can set the values of moments of different orders roughly in the same range and be applied to different 3D data formats universally. Then accurate computation of moments for several objects is presented and experiments show that this kind of normalization is very useful for moment invariants in 3D objects analysis and recognition.     

Sorption of ethene and ethane on the V2O5(001)/TiO2(001) anatase interface

Simulation techniques have been employed to investigate the differences in the low energy adsorption configurations of ethene and ethane on the TiO₂ supported and unsupported V₂O₅(001) surface. We find that the ethene molecule approaches much closer to thesupported V₂O₅(001) surface which is reflected in the 40 kj mol^–1 higher adsorption energy. The low energy adsorption configuration located for ethane on the supported V₂O₅ shows that the molecule does not approach as close to the supported V₂O₅ surface as does ethene, resulting in the adsorption energy of ethane being 52 kJ mol^–1 lower than that of ethene on the supported V₂O₅ surface.     

多孔泡沫金属及其磁导率的研究

研究了多孔泡沫金属的磁导率,建立了电沉积金属磁导率的计算模型。利用石蜡熔融的方法,得到了电沉积所得的多孔泡沫金属的孔隙率;利用振动样品磁强计对结构参数相同、磁导率不同的三种多孔泡沫金属进行了测试,得到了多孔泡沫金属及电沉积金属的相对磁导率,根据等效磁阻的原理,对电沉积金属相对磁导率进行了仿真计算,计算结果与实验相近;结果表明,建立的模型可以用来计算电沉积金属的相对磁导率;多孔泡沫金属的磁导率随着电沉积金属磁导率的增加而增加,随着孔隙率的增加而减小,为研究多孔泡沫金属的磁性能提供了理论和实验依据。     

Evolutionary digital twin: A new approach for intelligent industrial product development

To fulfill increasingly difficult and demanding tasks in the ever-changing complex world, intelligent industrial products are to be developed with higher flexibility and adaptability. Digital twin (DT) brings about a possible means, due to its ability to provide candidate behavior adjustments based on received “feedbacks” from its physical part. However, such candidate adjustments are deterministic, and thus lack of flexibility and adaptability. To address such problem, in this paper an extended concept – evolutionary digital twin (EDT) and an EDT-based new mode for intelligent industrial product development has been proposed. With our proposed EDT, a more precise approximated model of the physical world could be established through supervised learning, based on which the collaborative exploration for optimal policies via parallel simulation in multiple cyberspaces could be performed through reinforcement learning. Hence, more flexibility and adaptability could be brought to industrial products through machine learning (such as supervised learning and reinforcement learning) based self-evolution. As a primary verification of the effectiveness of our proposed approach, a case study has been carried out. The experimental results have well confirmed the effectiveness of our EDT based development mode.     

基于RISC-V处理器的卷积加速SoC系统设计

为提高卷积神经网络（CNN）的计算效率和能效,以8 bit定点数据作为输入,设计一个支持激活、批标准化以及池化等CNN网络中常见计算类型的卷积加速器,优化循环计算顺序并将其与数据复用技术相结合,以提高卷积计算的效率。基于软硬件协同设计思想,构建包含RISC-V处理器和卷积加速器的SoC系统,RISC-V处理器基于开源的指令集标准,可以根据具体的设计需求扩展指令功能。将该SoC系统部署在Xilinx ZCU102开发板上,RISC-V处理器和卷积加速器分别工作在100 MHz和300 MHz频率下,测试结果表明,该加速器的算力达到153.6 GOP/s,运行VGG16网络进行图片推理计算时加速效果较好。     

改进麻雀搜索算法求解作业车间调度问题

针对最小化完工时间的作业车间调度问题(JSP),提出改进麻雀搜索算法(ISSA).首先设计有效的编码转换方式,形成JSP离散决策空间与麻雀搜索算法(SSA)连续搜索空间的对应关系.然后,针对SSA在求解后期易陷入局部最优,利用量子计算、正余弦搜索和警戒者数量递减策略对SSA进行改进,同时引入多邻域搜索和高斯扰动策略以弥补SSA在求解离散问题时深度发掘能力不足的弊端.最后,进行FT、LA系列10个测试问题、6种算法和2个应用实例的对比实验.结果表明,ISSA在求解JSP时,能获得更好的最小值、平均值和寻优成功率,验证了ISSA求解JSP的有效性.     

基于NOMA的5G超密网计算迁移与资源分配策略

针对5G超密网中移动设备计算能力不足、频谱资源有限的问题,提出了一种基于非正交多址接入（NOMA）的计算迁移与带宽分配策略。首先,对系统模型进行了分析,并在此基础上以最小化设备计算代价为目标对所研究的问题进行形式化定义;然后,将该问题分解成设备的计算迁移、系统的带宽分配和设备的分组匹配三个子问题,并利用模拟退火、内点法和贪心算法对这三个子问题进行求解;最后,通过联合优化算法对上述子问题进行交替性迭代求解,最终获得最优计算迁移和资源分配策略。仿真结果表明,所提出的联合优化策略不但优于传统的正交多址接入（OMA）方式,而且能获得比平均分配带宽的NOMA技术更低的设备计算代价。     

Differentially private data fusion and deep learning Framework for Cyber–Physical–Social Systems: State-of-the-art and perspectives

The modern technological advancement influences the growth of the cyber–physical system and cyber–social system to a more advanced computing system cyber–physical–social system (CPSS). Therefore, CPSS leads the data science revolution by promoting tri-space information resource from a single space. The establishment of CPSSs increases the related privacy concerns. To provide privacy on CPSSs data, various privacy-preserving schemes have been introduced in the recent past. However, technological advancement in CPSSs requires the modifications of previous techniques to suit its dynamics. Meanwhile, differential privacy has emerged as an effective method to safeguard CPSSs data privacy. To completely comprehend the state-of-the-art developments and learn the field’s research directions, this article provides a comprehensive review of differentially private data fusion and deep learning in CPSSs. Additionally, we present a novel differentially private data fusion and deep learning Framework for Cyber–Physical–Social Systems , and various future research directions for CPSSs.     

基于约化乘法表的绝热量子整数分解算法

绝热量子计算模型是一种极具潜力的量子计算模型。报告一种基于约化乘法表的绝热量子整数分解方案及其在6量子~16量子比特内的数值仿真实验结果。这种方案采用约化的乘法表将整数分解问题转化为优化问题,从而将分解问题所需要的量子比特降低到n(n为待分解整数的二进制位宽)。实验结果表明新的绝热量子整数分解算法只需要多项式时间来求解此优化问题。