克氏针茅典型草原区建植人工草地的探索

发展优质高产的人工草地是有效解决草畜矛盾的途径之一。以羊草、披碱草、冰草、紫花苜蓿为实验材料,在呼伦贝尔市新巴尔虎右旗克氏针茅草原区开展人工草地实验。结果表明:建植当年,四种牧草都有较好的出苗率。建植第二年,羊草、披碱草和冰草的株丛数之间无显著差异,显著高于紫花苜蓿的株丛数;羊草和冰草的返青率高于30%,显著大于披碱草的返青率,紫花苜蓿的返青率最低,低于2%,显著小于披碱草的返青率;羊草、披碱草和冰草三种禾草之间的叶氮和叶绿素含量差异均不显著,紫花苜蓿叶片氮和叶绿素含量高于三种禾草;羊草、披碱草和冰草的植株高度为30~40 cm,差异不显著,紫花苜蓿的植株高度最低,为21.6 cm,显著低于其他三种禾草的植株高度;紫花苜蓿地上生物量显著低于三种禾草。受该区域冬季寒冷和生长季干旱的气候限制,需要综合评价确立该区域建植人工草地的可行性。     

军用航空装备技术发展趋势

 军用航空装备技术的发展方向直接影响一个国家的军用航空装备，进而决定一个国家的空中力量。通过分析研究世界航空军事强国着力发展的航空装备以及新兴技术在航空装备上的应用，提出未来军用航空装备技术将向着体系化、信息化、敏捷化、远程化和智能化的方向发展，并对中国军用航空装备未来发展提出了建议。     

云计算视角下可验证计算的分析研究

云计算能否在未来的各个领域中被广泛运用,决定因素在于其可信度。可验证计算在检测云计算结果的可信度方面具有其独特优势。利用可验证计算协议可验证云服务器端所返回的数据是否正确,它成为实现云计算可信度的重要保障。文中在阐述可验证计算基本内容和相关设计原则的基础上,分析了可验证计算协议的一般流程、设计原则及计算模型,并结合基于交互系统的可验证计算协议分析,探讨在云计算视角下可验证计算的研究展望。     

ID-Based Public Auditing Protocol for Cloud Storage Data Integrity Checking with Strengthened Authentication and Security

Cloud storage service reduces the burden of data users by storing users’ data files in the cloud. But, the files might be modified in the cloud. So, data users hope to check data files integrity periodically. In a public auditing protocol, there is a trusted auditor who has certain ability to help users to check the integrity of data files. With the advantages of no public key management and verification, researchers focus on public auditing protocol in ID-based cryptography recently. However, some existing protocols are vulnerable to forgery attack. In this paper, based on ID-based signature technology, by strengthening information authentication and the computing power of the auditor, we propose an ID-based public auditing protocol for cloud data integrity checking. We also prove that the proposed protocol is secure in the random oracle model under the assumption that the Diffie-Hellman problem is hard. Furthermore, we compare the proposed protocol with other two ID-based auditing protocols in security features, communication efficiency and computation cost. The comparisons show that the proposed protocol satisfies more security features with lower computation cost.     

Quantitative Analysis of Multi-Recovery-Based Intrusion Tolerance Model

Quantitative analysis has always been a difficult problem in security analysis of intrusion tolerance systems. An intrusion tolerance model based on multiple recovery mechanisms is introduced in this paper and how to quantify the security attributes of the model is proposed. A state transition model with recovery states more accurately describes the dynamic behavior of the system. Considering that recovery mechanisms have a great impact on the security performance of the system, we set up the cost models corresponding to different recovery mechanisms. We propose a feasible security measure based on mean cost to security failure in order to evaluate the system cost during the recovery phase. The experimental results confirmed the feasibility of the proposed methods.     

The Ore-Sato Theorem and Shift Exponents in the q-Difference Case

The authors translate the main results in the paper entitled "Multiplicative Decomposition of Multivariate q-Hypergeometric Terms" from Chinese into English. The paper is written by Shaoshi Chen, Ruyong Feng, Guofeng Fu and Jing Kang, and published in Journal of Mathematics and Systems Science, 32(8), 1019–1032, 2012. Some minor simpli?cation and modi?cation are made during the translation. Based on the results in the above paper, a special form is derived for q-shift exponents appearing in the q-shift quotients of a q-hypergeometric term.     

租赁设备的状态维修决策建模与优化

随着物联网技术飞速发展,租赁设备大多安装有传感系统,可以及时地对设备关键部件和整体运行状态进行检测,进而可基于设备的健康状态为其安排更为合理的维修方案,在降低租赁商维修费用的同时,尽量少地干预客户的正常施工,并且保证租赁设备在客户施工场所的可靠运行.本文研究了基于状态检测的租赁设备的最优维修问题,研究中引入了顺序状态检测,定义了基于状态的控制限维修策略,并建立了以维修开销最小为目标的解析模型,以决策系统最优的检测间隔和预防维修阈值.除检测、维修等基本费用外,模型中还进一步考虑了租赁系统的故障罚金和故障后维修超时罚金.在模型的求解中,推导了维修干预下设备任意时刻的检测概率和状态概率分布,作为模型构建和求解的依据.数值实验结果验证并表明了面向租赁设备的基于状态的维修策略的有效性.     

基于深度图像预旋转的手势估计改进方法

基于深度图像的手势估计比人体姿势估计更加困难,部分原因在于算法不能很好地识别同一个手势经旋转后的不同外观样式.提出了一种基于卷积神经网络(Convolutional Neural Network, CNN)推测预旋转角度的手势姿态估计改进方法:先利用自动算法标注的最佳旋转角度来训练CNN;在手势识别之前,用训练好的CNN模型回归计算出应预旋转的角度,然后再对手部深度图像进行旋转;最后采用随机决策森林(Random Decision Forest, RDF)方法对手部像素进行分类,聚类产生出手部关节位置.实验证明该方法可以减少预测的手部关节位置与准确位置之间的误差,手势姿态估计的正确率平均上升了约4.69%.     

基于空地协同采样的植被覆盖度随机森林估算方法

基于无人机高光谱影像, 建立地形复杂地区植被覆盖度的非参数随机森林回归估算模型。为获得构建随机森林模型所需的足够数量的训练样本, 利用低空无人机搭载的光学相机, 在从地面难以到达的山地、水域和植被茂密区, 通过垂直拍摄获得厘米分辨率的航拍影像, 作为对地面样方采样的补充。首先计算地面数码相机照片和无人机可见光影像的红绿蓝植被指数(red-green-blue vegetation index, RGBVI), 然后使用大津分割法提取样方的植被覆盖信息, 得到构建模型所需的训练样本。在此基础上, 基于2018年8月16—18日在内蒙古自治区察右中旗油娄沟矿区获取的GaiaSky-mini2无人机高光谱影像数据, 利用递归特征消除算法优选参与随机森林回归的特征变量集, 利用空地协同获取的训练样本构建植被覆盖度的随机森林回归估算模型。该模型在测试集上的确定系数R2为0.923, 均方根误差为0.087, 优于常用的像元二分模型, 可用于矿区植被动态信息的精细化监测。     

中国西北干旱区过度灌溉绿洲的水分收支特征研究

基于水分收支平衡原理, 观测2012年生长季张掖绿洲的水分收支分量动态特征, 探究灌溉对绿洲水分收支的影响。结果表明: 1) 无降水及灌溉时, 绿洲内40~100 cm深度的土壤含水量高 0~20 cm的土壤, 强降水事件对0~20 cm的土壤含水量影响较大, 而灌溉事件对 0~100 cm的土壤含水量有明显影响; 2) 无降水及灌溉时, 绿洲的日均蒸散发(ET)为2.83 mm/d, 降水事件后3日蒸散发量为降水之前的 1.16倍, 灌溉事件之后2日蒸散速率为灌溉之前的1.88倍, 说明灌溉对绿洲的蒸散发影响更为显著; 3) 绿洲生长季水分收支收入项(降水和灌溉, P+I)中, 灌溉占89.7%, 水分支出项主要为深层渗漏(DP), DP/(P+I)为81%; 4) 2012年生长季绿洲灌溉需水量为213 mm, 实际灌溉量比灌溉需水量多出474 mm, 远远超出所需, 水资源浪费严重。