地学数据标注和引用现状与存在的问题初探

科学数据引用是近年来逐渐兴起与成熟的一个领域,世界各国都对其进行了一系列相关工作。地学作为一门涉及范围极广的科学,在众多科研工作中积累了大量的科学数据。概述了我国科学数据共享体系的现状与存在的问题,以寒区旱区科学数据中心提供的数据施引文献库为例,分析了该中心数据集自2006~2013年(注:2013年数据不全)的被引情况。研究结果发现:科学数据集自公开到被广泛引用需要约2年的时间积累,2年之后被引情况大幅度增长。该数据集遥感数据最多,其次是土地和气象数据。但从被引情况来看,以遥感和气象被引次数居首,说明用户对此类数据的需求较大。     

联合模板先验概率和稀疏表示的目标跟踪

目的 虽然基于稀疏表示的目标跟踪方法表现出了良好的跟踪效果,但仍然无法彻底解决噪声、旋转、遮挡、运动模糊、光照和姿态变化等复杂背景下的目标跟踪问题。针对遮挡、旋转、姿态变化和运动模糊问题,提出一种在粒子滤波框架内,基于稀疏表示和先验概率相结合的目标跟踪方法。方法 通过先验概率衡量目标模板的重要性,并将其引入到正则化模型中,作为模板更新的主要依据,从而获得一种新的候选目标稀疏表示模型。结果 在多个测试视频序列上,与多种流行算法相比,该算法可以达到更好的跟踪性能。在5个经典测试视频下的平均中心误差为6.77像素,平均跟踪成功率为97%,均优于其他算法。结论 实验结果表明,在各种含有遮挡、旋转、姿态变化和运动模糊的视频中,该算法可以稳定可靠地跟踪目标,适用于视频监控复杂场景下的目标跟踪。     

K均值聚类和支持向量数据描述的图像超分辨率算法

目的 为了提高图像超分辨率算法对数据奇异点的鲁棒性,提出一种采用K均值聚类和支持向量数据描述的图像超分辨率重建算法(Kmeans-SVDD)。方法 训练过程:首先用K均值聚类算法将训练图像的近似子带划分为若干类,然后用支持向量数据描述去除每类数据的奇异点,最后在小波域内用主成分分析训练近似子带和细节子带字典。测试过程:根据同一场景高低分辨率图像近似子带相似这一现象,首先将待重建低分辨率测试图像的近似子带作为相应高分辨率测试图像的近似子带,然后由训练得到的字典恢复出高分辨率测试图像的细节子带,最后通过逆小波变换得到高分辨率测试图像。结果 相比于当前双三次插值、Zeyde、ANR与Kmeans-PCA算法,Kmeans-SVDD算法重建的高分辨率测试图像的平均峰值信噪比依次提高了1.82 dB、0.37 dB、0.30 dB、0.15 dB。结论 通过大量实验发现,在字典训练之前加入SVDD过程可以去除离群点,提高字典质量。在小波域中将各频带分开重建,可避免低频图像中包含的不可靠高频信息对超分辨率结果的影响,从而恢复出可靠的高频信息。     

Coordination arrival control for multi‐agent systems

The coordination arrival problems of first‐order multi‐agent systems with the arriving structure and the time structure requirements are considered for the cases with no obstacle and obstacle. To describe the distributed coordination arrival problems, we first introduce needed definitions, such as coordination arrival, threat point, and arrival structure. By selecting the estimated value of the arriving time of the agent as variable, we then develop a central estimating algorithm, which is used to construct the arriving protocols. Based on the estimating algorithm, we build and analyze coordination arriving protocols for the proposed coordination arrival problems. Several simulation examples are presented to validate the proposed algorithms. Copyright © 2015 John Wiley & Sons, Ltd.     

An SNN-Based Semantic Role Labeling Model with Its Network Parameters Optimized Using an Improved PSO Algorithm

Semantic role labeling (SRL) is a fundamental task in natural language processing to find a sentence-level semantic representation. The semantic role labeling procedure can be viewed as a process of competition between many order parameters, in which the strongest order parameter will win by competition and the desired pattern will be recognized. To realize the above-mentioned integrative SRL, we use synergetic neural network (SNN). Since the network parameters of SNN directly influence the synergetic recognition performance, it is important to optimize the parameters. In this paper, we propose an improved particle swarm optimization (PSO) algorithm based on log-linear model and use it to effectively determine the network parameters. Our contributions are two-folds: firstly, a log-linear model is introduced to PSO algorithm which can effectively make use of the advantages of a variety of different knowledge sources, and enhance the decision making ability of the model. Secondly, we propose an improved SNN model based on the improved PSO and show its effectiveness in the SRL task. The experimental results show that the proposed model has a higher performance for semantic role labeling with more powerful global exploration ability and faster convergence speed, and indicate that the proposed model has a promising future for other natural language processing tasks.     

QoS constraints-based energy-efficient model in cloud computing networks for multimedia clinical issues

For many applications of multimedia medical devices in clinical and medical issues, cloud computing becomes a very useful way. However, high energy consumption of cloud computing networks for these applications brings forth a large challenge. This paper studies the energy-efficient problem with QoS constraints in large-scale cloud computing networks. We use the sleeping and rate scaling mechanism to propose a link energy consumption model to characterize the network energy consumption. If there is no traffic on a link, we will let it be sleeping. Otherwise, it is activated and we divide its energy consumption into base energy consumption and traffic energy consumption. The former describes the constant energy consumption that exists when the link runs, while the later, which is a quadratic function with respect to the traffic, indicates the relations between link energy consumption and the traffic on the link. Then considering the relation among network energy consumption, number of active links, and QoS constraints, we build the multi-constrained energy efficient model to overcome the high energy consumption in large-scale cloud computing networks. Finally, we exploit the NSF and GEANT network topology to validate our model. Simulation results show that our approach can significantly improve energy efficiency of cloud computing networks.     

Measurement device-independent quantum key distribution with heralded pair coherent state

The original measurement device-independent quantum key distribution is reviewed, and a modified protocol using heralded pair coherent state (HPCS) is proposed to overcome the quantum bit error rate associated with the dark count rate of the detectors in long-distance quantum key distribution. Our simulation indicates that the secure transmission distance can be improved evidently with HPCS owing to the lower probability of vacuum events when compared with weak coherent source scenario, while the secure key rate can be increased with HPCS due to the higher probability of single-photon events when compared with heralded single-photon source scenario. Furthermore, we apply the finite key analysis to the decoy state MDI-QKD with HPCS and obtain a practical key rate.     

Scheme for implementing multitarget qubit controlled-NOT gate of photons and controlled-phase gate of electron spins via quantum dot-microcavity coupled system

We propose a deterministic scheme to implement the multiqubit controlled-NOT gate of photons and multiqubit controlled-phase gate of electron spins with one control qubit and multiple target qubits using quantum dots in double-sided optical cavities. The scheme is based on spin selective photon reflection from the cavity and can be achieved in a nondestructive way. We assess the feasibility of the scheme and show that the gates can be implemented with high average fidelities by choosing the realistic system parameters appropriately. The scheme is useful in quantum information processing such as entanglement preparation, quantum error correction, and quantum algorithms.     

Novel classical post-processing for quantum key distribution-based quantum private query

Existing classical post-processing (CPP) schemes for quantum key distribution (QKD)-based quantum private queries (QPQs) including the \(kN\rightarrow N\), \(N\rightarrow N\), and \(rM\rightarrow N\) ones have been found imperfect in terms of communication efficiency and security. In this paper, we propose a novel CPP scheme for QKD-based QPQs. The proposed CPP scheme reduces the communication complexity and improves the security of QKD-based QPQ protocols largely. Furthermore, the proposed CPP scheme can provide a multi-bit query efficiently.