Panoramic view and national identity: two of Santiago de Chile's public spaces in the second half of the nineteenth century

This article shows how the panorama, as a modern form of visualization and representation, became a model for the Santa Lucia Hill and the Cousiño Park, two emblematic projects of Santiago's transformation, carried out by Benjamín Vicuña Mackenna between 1872 and 1875. On the one hand, supported by the height and location of the hill and its pattern of paths and terraces, the Santa Lucia promenade became an effective mechanism for visual control of the city as a whole, as well as a reference to the new urban order that was to be imposed. On the other hand, by proposing a landscape design that served as an urban window into Santiago's geographical surroundings, the Cousiño Park project interpreted the qualities of the panorama from a strongly local sensitivity that highlighted the values of life in contact with nature. The analysis of these two cases will show how the panorama remarkably influenced Santiago's first transformation in the republican era, while representing fundamental values of the emerging national identity.     

Collective foraging in heterogeneous landscapes

Animals foraging alone are hypothesized to optimize the encounter rates with resources through Lévy walks. However, the issue of how the interactions between multiple foragers influence their search efficiency is still not completely understood. To address this, we consider a model to study the optimal strategy for a group of foragers searching for targets distributed heterogeneously. In our model, foragers move on a square lattice containing immobile but regenerative targets. At any instant, a forager is able to detect only those targets that happen to be in the same site. However, we allow the foragers to have information about the state of other foragers. A forager who has not detected any target walks towards the nearest location, where another forager has detected a target, with a probability exp(−αd), where d is the distance between the foragers and α is a parameter characterizing the propensity of the foragers to aggregate. The model reveals that neither overcrowding (α → 0) nor independent searching (α → ∞) is beneficial for the foragers. For a patchy distribution of targets, the efficiency is maximum for intermediate values of α. In addition, in the limit α → 0, the length of the walks can become scale-free.     

RER： A Replica Efficiency Based Replication Strategy

The technology of replication is often used in the unstructured Peer-to-peer （P2P） systems to allocate more replicas for the hot spots in order for a higher search performance. But the questions that what is the optimal number of copies for each file and what is the practicable approach to the optimal number are seldom answered in the related works. In terms of success rate, this paper firstly investigates the optimal allocation of copies for each file according to query rate with the routing algorithm of random walks. Then a practicable method is proposed to approach the optimal allocation in the unstructured P2P systems. Our results offer a new understanding of replication and our work contributes much to the content distribution in the Internet environment.     

Simulation of polymer systems

The present paper describes an algorithm which can generate, even on a small computer, arbitrarily long polymer chains, making sure that the configurations generated do not suffer from boundary effects. This has been achieved by employing the concept of a window, which is an analogue of virtual memory scheme. The algorithm has been tested for the case of dilute polymer solution.     

结合SSFCM与随机游走的半监督图像分割算法

针对基于颜色特征空间的半监督聚类分割算法适合分割结果包含多个颜色特征相似目标的应用场合,但对高噪声图像却无法获得理想的分割结果,而基于随机游走理论的半监督图像分割算法需要用户对目标逐一进行标记的问题,提出一种半监督图像分割算法.首先根据用户标记采用半监督模糊C均值聚类(SSFCM)算法对图像颜色特征进行建模;然后引入一个确信度函数,并根据SSFCM算法得到的隶属度数据计算确信度函数值,再将像素分为2类,分别作为随机游走图像分割算法的已标记点和未标记点;最后采用随机游走算法完成最终的分割.实验结果表明,该算法对图像中的噪声具有良好的抑制作用,且无需用户对目标逐一进行标记.     

Detecting Overlapping Community Structures in Networks

Community structure has been recognized as an important statistical feature of networked systems over the past decade. A lot of work has been done to discover isolated communities from a network, and the focus was on developing of algorithms with high quality and good performance. However, there is less work done on the discovery of overlapping community structure, even though it could better capture the nature of network in some real-world applications. For example, people are always provided with varying characteristics and interests, and are able to join very different communities in their social network. In this context, we present a novel overlapping community structures detecting algorithm which first finds the seed sets by the spectral partition and then extends them with a special random walks technique. At every expansion step, the modularity function Q is chosen to measure the expansion structures. The function has become one of the popular standards in community detecting and is defined in Newman and Girvan (Phys. Rev. 69:026113, 2004). We also give a theoretic analysis to the whole expansion process and prove that our algorithm gets the best community structures greedily. Extensive experiments are conducted in real-world networks with various sizes. The results show that overlapping is important to find the complete community structures and our method outperforms the C-means in quality.     

一种鲁棒视频抠图算法*

基于鲁棒抠图算法提出了一种鲁棒视频抠图算法。新算法给出了一种基于少量手工标记的Strokes生成Trimap的方法,为视频帧半自动生成较为粗糙的Trimap划分,同时结合标记传递策略大大减少视频抠图过程中的手工标记操作。理论分析和实验结果证明鲁棒视频抠图算法能够获得较优的视频抠图结果。     

One-Dimensional Continuous-Time Quantum Walks

We survey the equations of continuous-time quantum walks on simple one-dimensional lattices, which include the finite and infinite lines and the finite cycle, and compare them with the classical continuous-time Markov chains. The focus of our expository article is on analyzing these processes using the Laplace transform on the stochastic recurrences. The resulting time evolution equations, classical vs. quantum, are strikingly similar in form, although dissimilar in behavior. We also provide comparisons with analyses performed using spectral methods. PACS: 03.67.Lx     

基于随机游走的医学超声图像分割

医学超声图像不可避免地存在斑点噪声、弱边界等问题,很难达到满意的分割效果。随机游走算法对噪声具有鲁棒性,对弱边界有良好的提取能力。将此算法应用于医学超声图像分割,通过融合区域信息与用户指定的种子点信息,借助于电路模拟以及组合Dirichlet问题,可以得到每个非种子点到标记了目标点或者背景点的概率,并对其赋予概率中最大的种子点所对应的标记,从而实现图像的分割。实验结果表明,该方法对医学超声图像的分割是有效的。此算法通过求解稀疏的、对称的、正定的线性方程的系统来获得Dirichlet问题的解,使计算速度大为提高。