Resonance Assignments of Lowly Populated and Unstable Enzyme Intermediate Complex under Real-Time Conditions

Unstable and low-abundance protein complexes represent a large family of transient protein complexes that are difficult to characterize, even by means of high-resolution NMR spectroscopy. A method to assign the NMR signals of these unstable complexes through a combination of selective isotope labeling of amino acids in a protein and site-specific labeling the protein with a paramagnetic tag is presented herein. By using this method, the resonances of unstable thioester intermediate complex (lifetime <5 h and highest concentration ≈20 μm ) generated by Staphylococcus aureus sortase A and its peptide substrate under a real-time reaction have been assigned.     

A Real Time Self-Tuning Motion Controller for Mobile Robot Systems

This paper proposes an intelligent controller for motion control of robotic systems to obtain high precision tracking without the need for a real-time trial and error method. In addition, a new self-tuning algorithm has been developed based on both the ant colony algorithm and a fuzzy system for real-time tuning of controller parameters. Simulations and experiments using a real robot have been addressed to demonstrate the success of the proposed controller and validate the theoretical analysis. Obtained results confirm that the proposed controller ensures robust performance in the presence of disturbances and parametric uncertainties without the need for adjustment of control law parameters by a trial and error method.      

基于近似计算技术的FPRM电路面积优化

近似计算技术通过降低电路输出精度实现电路功耗、面积、速度等方面的优化.本文针对RM（Reed-Muller）逻辑中"异或"运算特点，提出了基于近似计算技术的适合FPRM逻辑的电路面积优化算法，包括基于不相交运算的RM逻辑错误率计算方法，及在错误率约束下，有利于面积优化的近似FPRM函数搜索方法等.优化算法用MCNC（Microelectronics Center of North Carolina）电路进行测试.实验结果表明，提出的算法可以处理输入变量个数为199个的大电路，在平均错误率为5.7%下，平均电路面积减少62.0%，并在实现面积优化的同时有利于实现电路的动态功耗的优化且对电路时延影响不大.     

增强现实场景下移动边缘计算资源分配优化方法

针对高速数据传输及计算所带来时延和终端设备能耗问题，提出了一种在上行链路采用等功率分配的传输方案。首先，依据增强现实（AR）业务的协作属性建立了针对AR特性的系统模型；其次，详细分析了系统帧结构，建立以最小化系统消耗总能量为优化目标的约束条件；最后，在保障延迟和功耗满足约束的条件下，建立了基于凸优化的移动边缘计算（MEC）资源优化求解数学模型，从而获得最优的通信和计算资源分配方案。与独立传输相比，该方案在最大延迟时间分别为0.1 s和0.15 s时的总能耗降幅均为14.6%。仿真结果表明，在相同条件下，与基于用户独立传输的优化方案相比，考虑用户间协作传输的等功率MEC优化方案能显著减少系统消耗的总能量。     

On Cost Aware Cloudlet Placement for Mobile Edge Computing

As accessing computing resources from the remote cloud inherently incurs high end-to-end (E2E) delay for mobile users, cloudlets, which are deployed at the edge of a network, can potentially mitigate this problem. Although some research works focus on allocating workloads among cloudlets, the cloudlet placement aiming to minimize the deployment cost (i.e., consisting of both the cloudlet cost and average E2E delay cost) has not been addressed effectively so far. The locations and number of cloudlets have a crucial impact on both the cloudlet cost in the network and average E2E delay of users. Therefore, in this paper, we propose the Cost Aware cloudlet PlAcement in moBiLe Edge computing (CAPABLE) strategy, where both the cloudlet cost and average E2E delay are considered in the cloudlet placement. To solve this problem, a Lagrangian heuristic algorithm is developed to achieve the suboptimal solution. After cloudlets are placed in the network, we also design a workload allocation scheme to minimize the E2E delay between users and their cloudlets by considering the user mobility. The performance of CAPABLE has been validated by extensive simulations.      

镀液温度实时控制系统的设计与实现

针对镀液温度变化的非线性和滞后性,设计了采用专家规则的镀液温度实时控制系统。该系统在实时监测的基础上,构建了综合评判镀液温度偏差和镀液温度偏差变化率的专家规则,实现了镀液温度的自适应快速调节。仿真分析结果表明,该系统克服了非线性和滞后性的不良影响,能够实现镀液温度的实时控制。     

高性能计算分析技术在大型钠冷快堆屏蔽设计中的应用

钠冷快堆堆容器是一体化的池式结构，由众多堆内构件组成且结构复杂，堆芯到生物屏蔽外中子输运过程中各向异性明显且深穿透问题严重，大尺度范围下三维S_N方法计算是制约快堆屏蔽设计的瓶颈。通过将三维SN程序与高性能计算技术相结合，采用并行计算方法可解决快堆堆本体内各向异性的三维深穿透屏蔽问题。本文以中国示范快堆（CFR600）堆本体为研究对象，采用JSNT-CFR程序详细计算了堆本体内的中子注量率、光子注量率、剂量率，并将计算结果与已有的二维程序设计结果进行比较。结果表明，将传统屏蔽计算方法与高性能计算相结合，能满足CFR600堆本体屏蔽计算精度要求，获得更为全面的三维展示效果，在计算模型复杂、粒子穿透深度等复杂问题的屏蔽计算上具有较明显的优势，为大型钠冷快堆屏蔽设计提供有力支撑。     

Extraction of Distinguished Hyperbolic Trajectories for 2D Time-Dependent Vector Field Topology

This paper does two main contributions to 2D time-dependent vector field topology. First, we present a technique for robust, accurate, and efficient extraction of distinguished hyperbolic trajectories (DHT), the generative structures of 2D time-dependent vector field topology. It is based on refinement of initial candidate curves. In contrast to previous approaches, it is robust because the refinement converges for reasonably close initial candidates, it is accurate due to its adaptive scheme, and it is efficient due to its high convergence speed. Second, we provide a detailed evaluation and discussion of previous approaches for the extraction of DHTs and time-dependent vector field topology in general. We demonstrate the utility of our approach using analytical flows, as well as data from computational fluid dynamics.     

An architecture for digital hate content reduction with mobile edge computing

Mobile devices with social media applications are the prevalent user equipment to generate and consume digital hate content. The objective of this paper is to propose a mobile edge computing architecture for regulating and reducing hate content at the user's level. In this regard, the profiling of hate content is obtained from the results of multiple studies by quantitative and qualitative analyses. Profiling resulted in different categories of hate content caused by gender, religion, race, and disability. Based on this information, an architectural framework is developed to regulate and reduce hate content at the user's level in the mobile computing environment. The proposed architecture will be a novel idea to reduce hate content generation and its impact.     

Distributed privacy protection strategy for MEC enhanced wireless body area networks

With the rapid development and widespread application of Wireless Body Area Networks (WBANs), the traditional centralized system architecture cannot handle the massive data generated by the edge devices. Meanwhile, in order to ensure the security of physiological privacy data and the identity privacy of patients, this paper presents a privacy protection strategy for Mobile Edge Computing(MEC) enhanced WBANs, which leverages the blockchain-based decentralized MEC paradigm to support efficient transmission of privacy information with low latency, high reliability within a high-demand data security scenario. On this basis, the Merkle tree optimization model is designed to authenticate nodes and to verify the source of physiological data. Furthermore, a hybrid signature algorithm is devised to guarantee the node anonymity with unforgeability, data integrity and reduced delay. The security performance analysis and simulation results show that our proposed strategy not only reduces the delay, but also secures the privacy and transmission of sensitive WBANs data.