Computation Rate Maximization in Multi-User Cooperation-Assisted Wireless-Powered Mobile Edge Computing with OFDMA

In the era of Internet of Things(Io T),mobile edge computing(MEC)and wireless power transfer(WPT)provide a prominent solution for computation-intensive applications to enhance computation capability and achieve sustainable energy supply.A wireless-powered mobile edge computing(WPMEC)system consisting of a hybrid access point(HAP)combined with MEC servers and many users is considered in this paper.In particular,a novel multiuser cooperation scheme based on orthogonal frequency division multiple access(OFDMA)is provided to improve the computation performance,where users can split the computation tasks into various parts for local computing,offloading to corresponding helper,and HAP for remote execution respectively with the aid of helper.Specifically,we aim at maximizing the weighted sum computation rate(WSCR)by optimizing time assignment,computation-task allocation,and transmission power at the same time while keeping energy neutrality in mind.We transform the original non-convex optimization problem to a convex optimization problem and then obtain a semi-closed form expression of the optimal solution by considering the convex optimization techniques.Simulation results demonstrate that the proposed multi-user cooperationassisted WPMEC scheme greatly improves the WSCR of all users than the existing schemes.In addition,OFDMA protocol increases the fairness and decreases delay among the users when compared to TDMA protocol.

Online Computation Offloading and Trajectory Scheduling for UAV-Enabled Wireless Powered Mobile Edge Computing

The unmanned aerial vehicle(UAV)-enabled mobile edge computing(MEC) architecture is expected to be a powerful technique to facilitate 5 G and beyond ubiquitous wireless connectivity and diverse vertical applications and services, anytime and anywhere. Wireless power transfer(WPT) is another promising technology to prolong the operation time of low-power wireless devices in the era of Internet of Things(IoT). However, the integration of WPT and UAV-enabled MEC systems is far from being well studied, especially in dynamic environments. In order to tackle this issue, this paper aims to investigate the stochastic computation offloading and trajectory scheduling for the UAV-enabled wireless powered MEC system. A UAV offers both RF wireless power transmission and computation services for IoT devices. Considering the stochastic task arrivals and random channel conditions, a long-term average energyefficiency(EE) minimization problem is formulated.Due to non-convexity and the time domain coupling of the variables in the formulated problem, a lowcomplexity online computation offloading and trajectory scheduling algorithm(OCOTSA) is proposed by exploiting Lyapunov optimization. Simulation results verify that there exists a balance between EE and the service delay, and demonstrate that the system EE performance obtained by the proposed scheme outperforms other benchmark schemes.

Computational Mass Transfer Method for Chemical Process Simulation

在计算集体转移(CMT ) 的开发的最近的工作在化学进程模拟的方法和它的应用程序被考察。在未来研究的一些发展策略和挑战也被讨论。

Prediction of Distillation Column Performance by Computational Mass Transfer Method

一个计算集体转移模型为预言集中侧面和筛托盘蒸馏列的 Murphree 效率被建议。建议模型基于用为由考虑从筛洞注射是三的蒸汽与改进关上微分狂暴的集体转移方程修改了二方程明确的表达维。由使用建议模型的预言的集中分布被为使放出在直径在 1.2 米的一个筛托盘模拟器上进行的试验性的工作检查由吹空气的 feed 水里的溶解的氧。模型预言被试验性的测量证实。建议模型的确认被把模仿的结果与 Kunesh 等报导的工业规模筛托盘蒸馏列的表演作比较进一步测试。为从它的水答案脱衣甲苯。在不同操作条件下面的每个托盘和 Murphree 托盘效率的预言的插头集中与出版数据一致。每个托盘上的模仿的狂暴的集体转移扩散性在在蔡等报导的一样的筛列的试验性的结果的范围以内。另外，由使用建议模型的托盘效率上的筛托盘结构的影响的预言被表明。

Different efficiency toward the biomimetic aerobic oxidation of benzyl alcohol in microchannel and bubble column reactors: Hydrodynamic characteristics and gas–liquid mass transfer

The selective aerobic oxidation of benzyl alcohol to benzaldehyde has attracted considerable attention because benzaldehyde is a high value-added product. The rate of this typical gas–liquid reaction is significantly affected by mass transfer. In this study, CoTPP-mediated(CoTPP: cobalt(II) mesotetraphenylporphyrin) selective benzyl alcohol oxidation with oxygen was conducted in a membrane microchannel(MMC) reactor and a bubble column(BC) reactor, respectively. We observed that 83% benzyl alcohol was converted within 6.5 min in the MMC reactor, but only less than 10% benzyl alcohol was converted in the BC reactor. Hydrodynamic characteristics and gas–liquid mass transfer performances were compared for the MMC and BC reactors. The MMC reactor was assumed to be a plug flow reactor,and the dimensionless variance was 0.29. Compared to the BC reactor, the gas–liquid mass transfer was intensified significantly in MMC reactor. It could be ascribed to the high gas holdup(2.9 times higher than that of BC reactor), liquid film mass transfer coefficient(8.2 times higher than that of BC reactor), and mass transfer coefficient per unit interfacial area(3.8 times higher than that of BC reactor). Moreover,the Hatta number for the MMC reactor reached up to 0.61, which was about 15 times higher than that of the BC reactor. The computational fluid dynamics calculations for mass fractions in both liquid and gas phases were consistent with the experimental data.

Multiway Dynamic Trust Chain Model on Virtual Machine for Cloud Computing

This paper sums up four security factors after analyzing co-residency threats caused by the special multitenant environment in the cloud.To secure the factors,a multiway dynamic trust chain transfer model was proposed on the basis of a measurement interactive virtual machine and current behavior to protect the integrity of the system.A trust chain construction module is designed in a virtual machine monitor.Through dynamic monitoring,it achieves the purpose of transferring integrity between virtual machine.A cloud system with a trust authentication function is implemented on the basis of the model,and its practicability is shown.

Second-order two-scale computations for conductive radiative heat transfer problem in periodic porous materials

In this paper, a kind of second-order two-scale （SOTS） computation is developed for conductive-radiative heat trans- fer problem in periodic porous materials. First of all, by the asymptotic expansion of the temperature field, the cell problem, homogenization problem, and second-order correctors are obtained successively. Then, the corresponding finite element al- gorithms are proposed. Finally, some numerical results are presented and compared with theoretical results. The numerical results of the proposed algorithm conform with those of the FE algorithm well, demonstrating the accuracy of the present method and its potential applications in thermal engineering of porous materials.

A code-independent technique for computational verification of fluid mechanics and heat transfer problems

The goal of this paper is to present a versatile framework for solution verification of PDE＇s. We first generalize the Richardson Extrapolation technique to an optimized extrapolation solution procedure that constructs the best consistent solution from a set of two or three coarse grid solution in the discrete norm of choice. This technique generalizes the Least Square Extrapolation method introduced by one of the author and W. Shyy. We second establish the conditioning number of the problem in a reduced space that approximates the main feature of the numerical solution thanks to a sensitivity analysis. Overall our method produces an a posteriori error estimation in this reduced space of approximation. The key feature of our method is that our construction does not require an internal knowledge of the software neither the source code that produces the solution to be verified. It can be applied in principle as a postprocessing procedure to off the shelf commercial code. We demonstrate the robustness of our method with two steady problems that are separately an incompressible back step flow test case and a heat transfer problem for a battery. Our error estimate might be ultimately verified with a near by manufactured solution. While our pro- cedure is systematic and requires numerous computation of residuals, one can take advantage of distributed computing to get quickly the error estimate.

Energy-Delay Tradeoff for Online Offloading Based on Deep Reinforcement Learning in Wireless Powered Mobile-Edge Computing Networks

Benefited from wireless power transfer(WPT)and mobile-edge computing(MEC),wireless powered MEC systems have attracted widespread attention.Specifically,we design an online offloading scheme based on deep reinforcement learning that maximizes the computation rate and minimizes the energy consumption of all wireless devices(WDs).Extensive results validate that the proposed scheme can achieve better tradeoff between energy consumption and computation delay.

Cracking and buoyancy effect on hydrocarbon endothermic and heat transfer characteristics in rectangular mini-channel

Although buoyancy and cracking reactions are strongly coupled in the active cooling process, most of the previous studies consider only one of these factors, and their coupling relationship has not been considerably examined. In this work, this coupling relationship was numerically investigated with complete consideration of different cases of heating, and in the view of energy transport and conversion. By comparing with the no-gravity case(NGC), the results indicate that buoyancy has a significant effect on the bottom-heated case(BHC) and side-heated case(SHC), but has little influence on the top-heated case(THC) owing to the different magnitudes of secondary flow. The heat transfer of the BHC and SHC was significantly enhanced by the secondary flow, but their energy conversion was simultaneously impaired.The conversion of the BHC and SHC was approximately half that of the THC and NGC. For all cases, by analyzing the energy transport ways, the cross section can be classified into three regions in the heating direction. Laminar conduction dominates in region Ⅰ, but gradually fails in region Ⅱ, where its role is replaced by other energy transport ways. In region Ⅲ, convection dominates the energy transport for BHC and SHC, whereas turbulence dominates for THC and NGC.

MATHEMATICAL MODEL AND COMPUTER SIMULATION OF MOISTURE TRANSFER PROCESS DURING SINTERING

ＭＡＴＨＥＭＡＴＩＣＡＬＭＯＤＥＬＡＮＤＣＯＭＰＵＴＥＲＳＩＭＵＬＡＴＩＯＮＯＦ ＭＯＩＳＴＵＲＥＴＲＡＮＳＦＥＲＰＲＯＣＥＳＳＤＵＲＩＮＧＳＩＮＴＥＲＩＮＧＺｏｕ；ＺｈｉｙｉＨｕａｎｇ；ＴｉａｎｚｈｅｎｇＹａｎｇ；ＸｉａｏｓｈｅｎｇＣｈｅｎ；Ｊｉ（...

A NEW COMPUTATION METHOD FOR THE UNSTEADY HEAT TRANSFER COEFFICIENT IN A DEEP MINE

In mine geothermal prediction, the unsteady heat transfer coefficient is an important parameter for heat transfer computation between country rock and mine airflow. In this paper, the rock temperature distributions in the geothermal fields have been derived in mathematics, the unsteady heat transfer coefficients that can expound the relation between its nature and influencing factors have been derived also based on this analytic formula. It is shown both by numerical simulations and through in situ measurernents that the new computation method for determining the unsteady heat transfer cofeeicient is accurate, rapid and simple.

基于计算机视觉的采摘机械臂控制系统设计

为了提高机械臂采摘的效率及增强安全自主性,提出了一种基于改进卷积神经网络和迁移学习的计算机图像识别模型。首先,建立了由可采摘与不可采摘图像组成的样本数据集,将每幅图像的像素设置为256×256;然后,构建基于改进卷积神经网络和迁移学习的计算机图像识别模型,并将自动编码机网络结构与卷积神经网络运算方法相结合,利用自动编码机网络结构具有编码和解码的环节,通过卷积神经网络运算方式构建出一种改进的卷积神经网络;通过卷积层挖掘图片信息中具有采摘信息的特征,同时消除随机环境对图片的干扰,解码部分能够对特征图像进行上采样并判断是否应该进行采摘与采摘姿势;最后,将构建网络模型与迁移学习相结合进行实验,分析迁移学习方法、数据集样本大小、网络参数对实验结果的影响。结果表明:采摘机械臂识别模型整体识别率更高,能够构建出效率更高、鲁棒性更强的采摘控制系统。

基于CCA融合FFT的SSVEP脑机接口分类算法

为解决多目标刺激范式的稳态视觉诱发电位脑电信号识别准确率低和信息传输率低的问题,提出了一种快速傅里叶变换同典型相关分析相结合的方法,通过快速傅里叶变换将信号训练成对应频率的训练模板,并作为参考信号与实时采集的信号进行典型相关分析来计算频率的识别准确率。6名受试者参与并完成了180组实验,在时间窗口长度为1.5 s的条件下,基于快速傅里叶变换-典型相关分析的稳态视觉诱发电位信号识别算法的平均识别准确率为93.98%,比典型相关分析算法提升了14.75%,信息传输率为62.30 bit·min^(-1),比典型相关分析算法提升了55.63%。实验结果表明,快速傅里叶变换-典型相关分析算法性能更优。

铜凿剪纸风格化方法研究

铜凿剪纸是一种在铜箔上凿点并使用矿物质颜料上色的传统艺术形式,其成品光彩夺目。铜凿剪纸工艺复杂、制作时间长,对手工艺人的技术水平有很高的要求。为此,提出了一种铜凿剪纸风格化的方法,并设计、实现了一种计算机辅助铜凿剪纸设计工具,通过生成图像线稿、凿点图以及铜凿剪纸效果图,帮助手工艺人快速完成铜凿剪纸的创作和制作。将输入图像进行区域分割以提取图像的线条,生成图像线稿;定义了一种颜色损失函数,结合贪心算法和梯度下降法求解函数最小值得到最佳颜色映射方案;基于VGG-19网络对图像线条进行风格迁移,生成凿点图;将线条风格迁移图像与颜色迁移图像进行融合,生成铜凿剪纸效果图;基于PyQt5框架开发铜凿剪纸设计工具,设计了交互平台。实验结果表明,该方法能够实现图像的铜凿剪纸风格化,且效果接近真实的铜凿剪纸,支持手工艺人快速生成工艺流程中需要的图像线稿、凿点图以及效果图等相关材料,提高铜凿剪纸的制作效率,具有较高的应用价值。

歧管式射流微通道液冷散热性能

随着信息技术进步,芯片向大面积、高功率方向发展,对热管理提出了严峻挑战。微通道液冷能够解决高功率芯片散热难题,但传统平直微通道热沉流阻大、温度均匀性差。提出了一种耦合歧管式进出液结构、分布式射流和微针翅的新型歧管式微通道散热器,在平均热通量高于330 W/cm^(2)、总功率达到2500 W时,芯片平均温度低于70℃,实现了高效散热。通过数值模拟发现:降低散热器射流腔高度可显著强化传热,但整体压降也随之陡升,存在一个最佳射流腔高度;散热器底板的微针翅尺寸及其与射流腔的相对尺寸是新型歧管式微通道散热器的重要结构参数,微针翅的存在并不是绝对有益于传热强化。定义了微针翅与射流腔之间相对高度的无量纲参数——翅占比,存在临界翅占比使得阻碍效应和强化效应相抵消,当翅占比高于这一临界值时才能达到强化换热效果。本研究为新型歧管式微通道散热器的设计提供了指导。

运动想象脑机接口的判别迁移特征学习与分类

为了解决不同时间采集的运动想象脑电数据之间存在的分布差异,避免跨时段使用前长时间的重校准步骤,提出了一种基于判别迁移特征学习(discriminative transfer feature learning,DTFL)的运动想象分类方法。DTFL通过联合匹配源域和目标域之间的边缘分布和类条件分布来减少域间的差异,同时最大化类间距离和最小化类内距离来保留类判别信息,从而提升对运动想象的分类性能。基于DTFL的运动想象分类方法无需目标域脑电样本的类别信息,可以有效避免长时间的校准。在脑机接口竞赛数据集上的实验结果表明,DTFL显著优于其他迁移学习方法,有效缓解跨域分布的不一致性,提高了运动想象的分类正确率。

基于CATIA的钢结构CAD与CAE一体化实现方法

为了应对钢结构在实现计算机辅助设计(CAD)与计算机辅助工程(CAE)一体化时的特殊性所带来的挑战,分析和归纳CAD与CAE一体化中数据转换,与几何理想化等关键问题,在此基础上,提出一种基于CATIA V6软件实现钢结构CAD与CAE一体化的方法,并通过一个绑扎桥钢结构的设计案例验证了该方法的有效性。通过所提方法分别实现了CAE几何理想化的自动切换与整合载荷数据至CAD模型的技术目标,从而避免了基于传统方法所带来的数据分离问题,减少了人工介入的低效工作。

温室传热水道与土壤换热强度影响的数值分析

以呼和浩特市某日光温室铺设的传热水道为研究对象,为提供传热水道在土壤中铺设间距、深度的准确依据,利用CFD数值模拟技术对传热水道在不同供水温度(30、40、50℃)、不同埋管深度(30、40、50cm)、不同管道间距(20、40、50cm)的情况时对温室土壤的换热强度进行研究与分析。结果表明:埋管深度越深对土壤地面温度影响越小,管道间距越宽则土壤的温度分布越分散,使土壤不容易达到温度扩散的饱和值,管温越高对管道以下的土壤影响越大,造成资源浪费;当埋管深度为30cm、管间距为20cm时,土壤的换热效果最佳。研究结果可为温室传热水道对土壤加热提供理论参考。

面向边缘光算力网络的上行链路资源协同调度算法

为满足冷、热业务实时、高效的算力调度需求,提出一种基于自适应噪声完全集合经验模态分解(CEEMDAN)与时间卷积网络(TCN)的算力负载预测模型(简称C-TCN模型),并设计了基于C-TCN与Q学习的资源协同调度算法(CTQ算法),利用C-TCN模型提前感知下一时刻负载变化,通过Q学习协同调度波长与存储资源,寻找最佳波长划分与边缘存储分配方案。实验结果表明:CTQ算法的调度性能不仅优于现有调度算法,能满足冷、热业务调度性能要求,而且还能提高波长利用率。