A high-level synthesis based dual-module redundancy with multi-residue detection （DMR-MRD） fault-tolerant method for on-board processing satellite communication systems

On board processing （OBP） satellite systems have obtained more and more attentions in recent years because of their high efficiency and performance.However,the OBP transponders are very sensitive to the high energy particles in the space radiation environments.Single event upset （SEU） is one of the major radiation effects,which influences the satellite reliability greatly.Triple modular redundancy （TMR） is a classic and efficient method to mask SEUs.However,TMR uses three identical modules and a comparison logic,the circuit size becomes unacceptable,especially in the resource limited environments such as OBP systems.Considering that,a new SEU-tolerant method based on residue code and high-level synthesis （HLS） is proposed,and the new method is applied to FIR filters,which are typical structures in the OBP systems.The simulation results show that,for an applicable HLS scheduling scheme,area reduction can be reduced by 48.26％ compared to TMR,while fault missing rate is 0.15％.     

SwiftArray: Accelerating Queries on Multidimensional Arrays

Scientific instruments and simulation programs are generating large amounts of multidimensional array data.Queries with value and dimension subsetting conditions are commonly used by scientists to find useful information from big array data,and data storage and indexing methods play an important role in supporting queries on multidimensional array data efficiently.In this paper,we propose SwiftArray,a new storage layout with indexing techniques to accelerate queries with value and dimension subsetting conditions.In SwiftArray,the multidimensional array is divided into blocks and each block stores sorted values.Blocks are placed in the order of a Hilbert space-filling curve to improve data locality for dimension subsetting queries.We propose a 2-D-Bin method to build an index for the blocks’value ranges,which is an efficient way to avoid accessing unnecessary blocks for value subsetting queries.Our evaluations show that SwiftArray surpasses the NetCDF-4 format and FastBit indexing technique for queries on multidimensional arrays.     

用于虚拟化环境的进程隔离方法研究与实现

针对虚拟化环境中用户进程运行安全问题,提出一种适用于虚拟化环境的进程隔离方法.该方法引入安全域作为进程隔离保护的基本单元,安全域是进程以及进程运行过程中依赖的环境构成的整体,通过建立安全域之间的依赖关系和安全域之间信息的交换规则,确保进程初始安全和运行过程中的隔离性.给出了安全域的相关概念和形式化描述,以及安全域之间信息流交换和依赖关系的建立方法和相关证明.以Xen虚拟化系统为基础,给出了该保护方法的具体实现以及实验结果,实验结果分析表明:该方法在虚拟化环境中能够抵御多种攻击手段,额外执行开销不超过10%.     

Detecting MoS2 and MoSe2 with optical contrast simulation

Optical imaging is a promising method to identify and locate 2D materials efficiently and non-invasively. By putting a 2D material on a substrate, the nanolayer will add to an optical path and create a contrast to the case when the nanolayer is absent. This optical contrast imaging can be used to identify the 2D material and its number of layers. To make the optical imaging process in the laboratories an effective tool, Fresnel Law as a model was used to simulate the optical imaging results of 2D materials(graphene, Mo S2 and MoSe_2) on top of different thickness of SiO_2 and Si wafer in the present investigation. The results provide the details of the optimal conditions(optimal light wavelength and optimal SiO_2 thickness) to identify and locate single to few 2D nanolayers, which can be used directly in laboratories. The optical contrasts of 1–5 layers of molybdenum disulfide(MoS_2) and molybdenum diselenide(MoSe_2) were simulated. To the best of our knowledge, it is the first time that the optical contrast results of MoSe_2 have been reported. In particular, this work highlights the sensitivity of the model on the accuracy of the refractive indices used. It is demonstrated that through computational modeling that optical contrast can allow effective determination of number of layers in few layer 2D materials.     

平煤四矿矿井通风阻力测定与系统分析

矿井通风系统阻力测定是煤矿安全生产和通风安全管理的重要内容,阻力的大小直接影响矿井通风的效果。为了了解平煤四矿矿井通风阻力的大小及其分布,优化矿井通风系统,选定主要测定路线,基于基点气压计法进行矿井阻力测定,并根据测定结果对矿井通风系统进行了分析。     

水动力作用对污染物在河流水沙两相中分配的影响研究进展

通过总结近年来有关水动力作用对河流中泥沙吸附/释放重金属、磷等污染物影响研究成果,分析了水流紊动强度和流速对污染物在河流水沙两相中分配的影响规律。当水流紊动强度较低时,泥沙主要以床沙形式存在,泥沙对污染物的吸附/释放速率和强度较低;随着紊动强度增大,水沙界面切应力随之增大并促使泥沙悬浮,污染物与悬浮泥沙颗粒接触面积增大,使得泥沙对污染物的吸附/释放速率和强度显著增加。流速对污染物在水沙两相间分配的影响较为复杂。泥沙静止时,流速的增大会减小边界层厚度,增大水体溶解氧含量、氧化还原电位等参数,并使污染物在水体里的扩散由分子扩散转变为以紊动扩散为主,增强污染物在水-沙界面的交换通量,对污染物在水沙两相间的分配产生影响;随着流速进一步增大,床沙逐渐起动、悬浮,此时除上述因素外,泥沙运动状态、悬浮颗粒间碰撞强度、悬浮物的絮凝等均会对泥沙吸附/释放污染物产生影响,由于影响因素较多,作用机制复杂,目前关于泥沙运动对污染物在水沙两相间分配的影响所得结论仍存在分歧。相应的机理研究及数学模型的建立均做了较大简化。综观当前的研究成果,水沙运动及其化学生物过程等对污染物在河流水沙两相中的分配作用机理和耗氧有机物、有毒有机物等污染物与泥沙的作用机理是这一领域的未来研究重点。     

Efficient Feature Extraction Using Apache Spark for Network Behavior Anomaly Detection

Extracting and analyzing network traffic feature is fundamental in the design and implementation of network behavior anomaly detection methods. The traditional network traffic feature method focuses on the statistical features of traffic volume. However, this approach is not sufficient to reflect the communication pattern features. A different approach is required to detect anomalous behaviors that do not exhibit traffic volume changes,such as low-intensity anomalous behaviors caused by Denial of Service/Distributed Denial of Service(Do S/DDo S)attacks, Internet worms and scanning, and Bot Nets. We propose an efficient traffic feature extraction architecture based on our proposed approach, which combines the benefit of traffic volume features and network communication pattern features. This method can detect low-intensity anomalous network behaviors and conventional traffic volume anomalies. We implemented our approach on Spark Streaming and validated our feature set using labelled real-world dataset collected from the Sichuan University campus network. Our results demonstrate that the traffic feature extraction approach is efficient in detecting both traffic variations and communication structure changes.Based on our evaluation of the MIT-DRAPA dataset, the same detection approach utilizes traffic volume features with detection precision of 82.3% and communication pattern features with detection precision of 89.9%. Our proposed feature set improves precision by 94%.     

基于信任的服务实体跨域认证方案

根据目前基于身份的跨域认证过程中域代理(domain agent,DA)数量有限的特点,针对该跨域认证过程中计算复杂的问题,采用信任和基于身份密码体制相结合的方式,提出了基于信任的用户跨域访问信息服务实体(information services entity,ISE)资源的算法。该算法首先完成用户在DA的身份认证,然后采用提出的信任度判断方法进行信任度的判断达到双向认证的目的,最终实现用户跨域访问ISE。仿真结果表明,信任度的判断方法有效地实现抵抗“恶意”DA的攻击,同时该基于信任的ISE跨域认证方案与基于身份的跨域认证方案相比,计算量减少,通信开销降低。     

New Moment Estimators of the Effective Spread Based on Daily High and Low Prices

This paper proposes five new simple moment estimators of the effective spread based on the covariance estimator of Roll(1984) and the High-Low estimator recently developed by Corwin and Schultz(2012). And then the authors theoretically investigate the statistical properties of six simple High-Low spread estimators including Corwin and Schultz's estimator. The biases and mean squared errors(MSE) of these six estimators have been derived and compared with each other asymptotically,which, together with the subsequent simulation study, reveal explicitly the superior performance of newly developed High-Low estimators over Corwin and Schultz's estimator in both ideal and nonideal conditions. Moreover, this paper also develops GMM estimators constructed by three or more moment conditions and compares with the six simple High-Low estimators. Finally, several example applications on the U.S. and Chinese financial markets are conducted to demonstrate the superior performance of the new High-Low estimators. The results provide alternative choices for identifying the liquidity proxies that well capture different structure of markets.