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％.     

Privacy Quantification Model Based on the Bayes Conditional Risk in Location-Based Services

The widespread use of Location-Based Services(LBSs),which allows untrusted service providers to collect large quantities of information regarding users’locations,has raised serious privacy concerns.In response to these issues,a variety of LBS Privacy Protection Mechanisms(LPPMs)have been recently proposed.However,evaluating these LPPMs remains problematic because of the absence of a generic adversarial model for most existing privacy metrics.In particular,the relationships between these metrics have not been examined in depth under a common adversarial model,leading to a possible selection of the inappropriate metric,which runs the risk of wrongly evaluating LPPMs.In this paper,we address these issues by proposing a privacy quantification model,which is based on Bayes conditional privacy,to specify a general adversarial model.This model employs a general definition of conditional privacy regarding the adversary’s estimation error to compare the different LBS privacy metrics.Moreover,we present a theoretical analysis for specifying how to connect our metric with other popular LBS privacy metrics.We show that our privacy quantification model permits interpretation and comparison of various popular LBS privacy metrics under a common perspective.Our results contribute to a better understanding of how privacy properties can be measured,as well as to the better selection of the most appropriate metric for any given LBS application.     

苯并[1，2-b：4，5-b’]二噻吩-thieno[3，4-易]thiadiazole导电性的理论研究

采用密度泛函理论，在B3LYP／6—31G（d）水平下，对苯并[1，2-b：4，5-b’]二噻吩（BDT）-thieno[3，4-b]thiadiaz01e（TD）的低聚物和聚合物进行了理论计算．其中，BDT为电子供体，TD为电子受体，以1：2的方式结合形成化合物，并计算了二面角、分子内的电荷传输、桥键键长和中心键电荷密度．结果显示：随着聚合链增长，共轭程度增加．NICSs值显示：中心环比边环的共轭程度更大．聚合物的能带结构表明：该聚合物的带隙比较低（0．87eV），故其可以作为潜在的导电材料．     

四川羌族成人皮褶厚度的研究

运用人体测量学方法对四川羌族602例(男299例,女303例)成年人进行7项皮褶(面颊、肱二头肌、肱三头肌、肩胛下、髂嵴上、髂前上棘、小腿内侧)厚度的测量,分析该族群皮褶厚度随年龄变化的特征,并与我国部分族群进行比较.结果表明:(1)四川羌族男性和女性的躯干皮褶厚度总体上高于面部和四肢皮褶厚度,后者最低;(2)男性和女性的7项皮褶中,均是髂嵴上皮褶厚度最大,肱二头肌皮褶厚度最小;(3)女性的皮褶厚度和体脂率均高于同年龄组男性的数值,性别间差异均具有统计学意义(P0.05);(4)男性和女性各项皮褶、体脂率之间均存在正相关,相关性具有高度统计学意义(P0.01);(5)同西部地区13个族群基于皮褶厚度的聚类分析结果表明,羌族男性与甘肃汉族最接近,羌族女性与四川汉族、贵州屯堡人最接近.     

不同农药残留标准下家庭农场种植行为选择

文章建立了政府与家庭农场农户之间的博弈模型,探讨在不同农药残留标准下政府如何对生态种植行为进行激励.研究表明,在宽松的农药残留标准下,政府可通过征收农药税等方式提高农药成本来激励农户选择生态种植,生态补贴及超标罚款的效果不明显;在严格的农药残留标准下,当农产品抽查难度较大时,政府可选择降低检查概率,同时大幅度提高农药价格来增加农户使用生态种植的动机;当政府对农药成本控制力较低或农药价格增量的边际效益较小时,政府应提高其检查概率,同时提高对于农药残留超标的罚款及生态种植的补贴来激励农户使用生态种植.     

Lattice-Based Double-Authentication-Preventing Ring Signature for Security and Privacy in Vehicular Ad-Hoc Networks

Amidst the rapid development of the Internet of Things(IoT), Vehicular Ad-Hoc NETwork(VANET), a typical IoT application, are bringing an ever-larger number of intelligent and convenient services to the daily lives of individuals. However, there remain challenges for VANETs in preserving privacy and security. In this paper, we propose the first lattice-based Double-Authentication-Preventing Ring Signature(DAPRS) and adopt it to propose a novel privacy-preserving authentication scheme for VANETs, offering the potential for security against quantum computers. The new construction is proven secure against chosen message attacks. Our scheme is more efficient than other ring signature in terms of the time cost of the message signing phase and verification phase, and also in terms of signature length. Analyses of security and efficiency demonstrate that our proposed scheme is provably secure and efficient in the application.     

基于遗传算法的光电干扰任务分配模型

 为评估光电干扰目标的威胁度，选取了目标的类型、速度、高度、距离、角度和目标的航路捷径等指标，构建了干扰任务分配模型，应用遗传算法对分配任务模型进行了求解，并通过实例验证方法的可行性。     

基于卷积神经网络和稀疏滤波的调制识别方法

针对当前通信系统所采用的主要调制方式,提出了一种基于卷积神经网络和稀疏滤波的调制识别方法。首先,分析了利用信号循环谱二维灰度图进行通信信号调制识别的可行性;然后,通过降采样和裁剪技术对循环谱图预处理;最后,设计了深度卷积神经网络架构,并提出了稀疏滤波预训练的方法。仿真结果表明:相比于经典的基于深度学习的调制识别方法,该方法模型简单,优化量少,且在小样本场景下性能最佳,具有很高应用价值。     

基于CAN-FD总线的车载网络安全通信

以数据加密和入侵检测为基础,建立了一种基于灵活数据速率控制器局域网络的汽车通信网络信息安全方法.提出了包括安全传输、安全启动、时间同步与密钥分配的汽车网络安全通信协议,并通过建立网络仿真模型验证安全协议的有效性.搭建了基于硬件实例的安全通信节点,测试硬件节点的实际通信性能和加密性能.最后针对汽车通信网络潜在的攻击方式,以Dolev-Yao入侵模型攻击和拒绝服务攻击为测试方法,对安全通信模型进行了安全性攻击测试和入侵检测功能验证,确定了网络入侵检测的判定指标.测试结果验证了该方法的安全性和可用性.     

基于神经网络动态优化的再入轨迹设计

为解决当飞行器出现破损以及飞行器受干扰时的轨迹优化问题,新一代的再入式飞行器需要有实时在线轨迹优化的能力。神经网络动态优化算法(neural dynamic optimization,NDO)的主要特点是能使神经网络逼近最优解。神经网络动态优化算法可以避免传统的间接法在求解轨迹优化问题时协态变量初值猜测问题。给出了神经网络动态优化的原理,详细介绍了优化流程。仿真结果表明神经网络动态优化算法可以很好的避免协态变量初值猜测问题,具有较强的鲁棒性,能满足实时性要求。