无双线性对的无证书安全签密方案

已有的无双线性对的无证书签密方案,大都存在着机密性漏洞和签名选择性伪造问题。针对此问题,基于有限乘法交换群上的离散对数难题,提出一种无双线性对的无证书签密方案,并进行了安全分析和证明。指出采用随机预言模型的证明方法可能忽略不解决DL难题时对签密方案的攻击,不能证明破解签密方案的难度与解决DL难题相等价。通过对参数的数学分析,证明了破解本签密方案的必要条件是解决DL难题,不存在不解决DL难题攻击本签密方案的多项式时间算法。与已知所有方案相比,所提方案安全性更高。     

Catalytic reduction of no over perovskite-type catalysts

In the present work, we have investigated the reduction of NO by propane over perovskite-type oxides prepared by malic acid method. The catalysts were modified to enhance the activity by substitution of metal into A or B site of perovskite oxides. In addition, the reaction conditions, such as temperature, O₂ concentration, and space velocity have been varied to understand their effects on the catalytic performance. In the LaCoO₃ type catalyst, the partial substitution of Ba and Sr into A site enhanced the catalytic activity in the reduction of NO. For the La_0.6Ba (Sr)_o.4 Co_1−x Fe_xO₃ (x=0-1.0) catalyst, the partial substitution of Fe into B site enhanced the conversion of NO, but excess amount of Fe decreased the conversion of NO. The surface area and catalytic activity of perovskite catalysts prepared by malic acid method showed higher values than those of solid reaction method. The conversion of NO increased with increasing O₂ concentration and contact time. The introduction of water into reactant feed decreased the catalytic activity but the deactivation was shown to be reversible over La_0.6Ba_0.4Co_1−x ,Fe_xO₃ catalyst.     

氨基磺酸作催化剂合成苹果酯的研究

以乙酰乙酸乙酯和乙二醇为原料，氨基磺酸为催化剂，催化合成了苹果酯。最佳反应条件为：乙酰乙酸乙酯与乙二醇的摩尔比1：1：3，催化剂加入量为0.5g(0.1摩尔的乙酰乙酸乙酯），反应温度70-80℃，反应时间2h，苹果酯的收率为92.7%。     

伪实例与人工标注实例相结合的词义消歧方法

知识获取是制约基于语料库的词义消歧方法性能提高的瓶颈,使用等价伪词的自动语料标注方法是近年来解决该问题的有效方法。等价伪词是用来代替歧义词在语料中查找消歧实例的词。但使用等价伪词获得的部分伪实例质量太差,且无法为没有或很少同义词的歧义词确定等价伪词。基于此,该文提出一种将等价伪词获得的伪实例和人工标注实例相结合的词义消歧方法。该方法通过计算伪实例与歧义词上下文的句子相似度,删除质量低下的伪实例。并借助人工标注语料为某些无等价伪词的歧义词提供消歧实例,计算各义项的分布概率。在Senseval-3汉语消歧任务上的实验中,该文方法取得了平均F-值为0.79的成绩。     

自适应斥力系数的无人机路径规划

使用人工势场法进行无人机路径规划时,往往存在目标不可达、运动轨迹迂回反复和路径长度过长等问题.传统的人工势场法不能根据环境具体信息对斥力系数进行调整,而现有的改进方法不能在自适应调整斥力系数的同时兼顾规划效果和规划时长.针对以上问题,提出了一种基于深度学习的无人机自适应斥力系数路径规划方法.首先通过融合遗传算法与人工势场法找出在特定环境下最合适的斥力系数样本集,其次利用该样本集训练残差神经网络,最后通过残差神经网络计算适应环境的斥力系数,进而使用人工势场法进行路径规划.仿真实验表明,该方法在一定程度上解决了人工势场法规划中目标不可达、运动轨迹迂回反复和路径长度过长等问题,规划效果和规划时长方面均有优异表现,能很好地满足无人机路径规划中对当前环境的自适应要求和快速规划的要求.     

Bi-directional LSTM based channel estimation in 5G massive MIMO OFDM systems over TDL-C model with Rayleigh fading distribution

In this work, a deep learning (DL)-based massive multiple-input multiple-output (mMIMO) orthogonal frequency division multiplexing (OFDM) system is investigated over the tapped delay line type C (TDL-C) model with a Rayleigh fading distribution at frequencies ranging from 0.5 to 100 GHz. The proposed bi-directional long short-term memory (Bi-LSTM) channel state information (CSI) estimator uses online learning during training and offline learning during the practical implementation phase. The design of the estimator takes into account situations in which prior knowledge of channel statistics is limited and targets excellent performance, even with limited pilot symbols (PS). Three separate loss functions (mean square logarithmic error [MSLE], Huber, and Kullback–Leibler Distance [KLD]) are assessed in three classification layers. The symbol error rate (SER) and outage probability performance of the proposed estimator are evaluated using a number of optimization techniques, such as stochastic gradient descent (SGD), momentum, and the adaptive gradient (AdaGrad) algorithm. The Bi-LSTM-based CSI estimator is trained considering a specific number of PS. It can be readily seen that by incorporating a cyclic prefix (CP), the system becomes more resilient to channel impairments, resulting in a lower SER. Simulations show that the SGD optimization approach and Huber loss function-trained Bi-LSTM-based CSI estimator have the lowest SER and very high estimation accuracy. By using deep neural networks (DNNs), the Bi-LSTM method for CSI estimation achieves a superior channel capacity (in bps/Hz) at 10 dB than long short-term memory (LSTM) and other conventional CSI estimators, such as minimum mean square error (MMSE) and least squares (LS). The simulation results validate the analytical results in the study.     

基于对抗深度学习的无人机航拍违建场地识别

对违建场地的检测方法主要是通过人工对无人机航拍视频进行检查,存在检测精度低、识别性能差、工作效率低的问题。提出一种结合空间变换网络与Fast RCNN的生成对抗网络ASTN-Fast RCNN,通过深度学习与无人机航拍视频相结合自动识别检测处在建设初期的违建场地。将空间变换网络作为生成器,生成Fast RCNN目标检测器难以识别的旋转形变样本,并通过目标检测器与生成器的对抗式训练,提高检测器的鲁棒性。实验结果表明,该方法能够有效提高对无人机航拍违建场地的识别性能。     

一种基于YOLOv4-TIA的林业害虫实时检测方法

针对现有基于深度学习的林业昆虫图像检测方法存在检测精度低和检测速度慢的问题,提出一种结合改进PANet结构与三分支注意力机制的目标检测方法YOLOv4-TIA。通过对样本数量较少的昆虫类别进行数据增强,实现样本均衡分布。利用三分支注意力机制改进YOLOv4中的CSPDarkNet53骨干网络,同时通过旋转操作和残差变换建立维度间的依存关系,以提高有效的特征通道权重,在PANet结构上增加将跳跃连接与跨尺度连接相结合的特征融合方式,从而获取更丰富的语义信息和位置信息。在此基础上,采用Focal loss函数优化分类损失,解决正负样本不均衡的问题。实验结果表明,该方法的精确率和召回率分别达到85.9%和91.2%,相比SSD、Faster R-CNN、YOLOv4方法,其在保证检测速度的同时,能够有效提高检测精度,且实现对林业害虫的实时精确监测。     

A formally specified ontology management API as a registry for ubiquitous computing systems

Recently, several standards have emerged for ontology markup languages that can be used to formalize all kinds of knowledge. However, there are no widely accepted standards yet that define APIs to manage ontological data. Processing ontological information still suffers from the heterogeneity imposed by the plethora of available ontology management systems. Moreover, ubiquitous computing environments usually comprise software components written in a variety of different programming languages, which makes it particularly difficult to establish a common ontology management API with programming language agnostic semantics. We implemented an ontological Knowledge Base Server, which can expose the functionality of arbitrary off-the-shelf ontology management systems via a formally specified and well defined API. A case study was carried out in order to demonstrate the feasibility of our approach to use a formally specified ontology management API to implement a registry for ubiquitous computing systems.     

支持OAI-PMH的元数据互操作体系结构设计与实现

随着全球数字图书馆的迅猛发展,互操作成为亟待解决的重要问题。OAI-PMH协议的制定为在元数据级别上设计实现一个统一、高效的互操作框架创造了条件。文章基于北京大学数字图书馆项目,详尽阐述了一个典型的支持OAI-PMH互操作体系结构的完整的设计与实现;不仅包括在理论上逻辑清晰的设计方案,在实现上也采用了比较成熟又兼具理论和应用前景的技术,如Java、DOM、XML、Oracle9i等。该文的工作为将来联合式数字图书馆这一发展方向做出了很好的尝试。