An integrated approach to analysing the cost efficiency of postal networks

An integrated approach to measure the cost efficiency of the postal network of Universal Service Provider is proposed. An integrated approach enables the measurement of cost efficiency for delivery and non-delivery postal network units. The proposed approach is verified and tested on the postal network of the selected provider and the results were derived by using Data Envelopment Analysis (DEA). The results show that the main sources of inefficiency are inadequate allocation of resources relative to the network units. In addition, the study indicates that economies of scale have a positive impact on the efficiency of postal network units.     

A Student's t-based density peaks clustering with superpixel segmentation (tDPCSS) method for image color clustering

Image color clustering is a basic technique in image processing and computer vision, which is often applied in image segmentation, color transfer, contrast enhancement, object detection, skin color capture, and so forth. Various clustering algorithms have been employed for image color clustering in recent years. However, most of the algorithms require a large amount of memory or a predetermined number of clusters. In addition, some of the existing algorithms are sensitive to the parameter configurations. In order to tackle the above problems, we propose an image color clustering method named Student's t-based density peaks clustering with superpixel segmentation (tDPCSS), which can automatically obtain clustering results, without requiring a large amount of memory, and is not dependent on the parameters of the algorithm or the number of clusters. In tDPCSS, superpixels are obtained based on automatic and constrained simple non-iterative clustering, to automatically decrease the image data volume. A Student's t kernel function and a cluster center selection method are adopted to eliminate the dependence of the density peak clustering on parameters and the number of clusters, respectively. The experiments undertaken in this study confirmed that the proposed approach outperforms k-means, fuzzy c-means, mean-shift clustering, and density peak clustering with superpixel segmentation in the accuracy of the cluster centers and the validity of the clustering results.     

Magnetic Resonance Signal Amplification by Reversible Exchange of Selective PyFALGEA Oligopeptide Ligands Towards Epidermal Growth Factor Receptors

The biorelevant PyFALGEA oligopeptide ligand, which is selective towards the epidermal growth factor receptor (EGFR), has been successfully employed as a substrate in magnetic resonance signal amplification by reversible exchange (SABRE) experiments. It is demonstrated that PyFALGEA and the iridium catalyst IMes form a PyFALGEA:IMes molecular complex. The interaction between PyFALGEA:IMes and H₂ results in a ternary SABRE complex. Selective 1D EXSY experiments reveal that this complex is labile, which is an essential condition for successful hyperpolarization by SABRE. Polarization transfer from parahydrogen to PyFALGEA is observed leading to significant enhancement of the ¹H NMR signals of PyFALGEA. Different iridium catalysts and peptides are inspected to discuss the influence of their molecular structures on the efficiency of hyperpolarization. It is observed that PyFALGEA oligopeptide hyperpolarization is more efficient when an iridium catalyst with a sterically less demanding NHC ligand system such as IMesBn is employed. Experiments with shorter analogues of PyFALGEA, that is, PyLGEA and PyEA, show that the bulky phenylalanine from the PyFALGEA oligopeptide causes steric hindrance in the SABRE complex, which hampers hyperpolarization with IMes. Finally, a single-scan ¹H NMR SABRE experiment of PyFALGEA with IMesBn revealed a unique pattern of NMR lines in the hydride region, which can be treated as a fingerprint of this important oligopeptide.     

Sensor network design based on system-wide reliability criteria. Part I: Objectives

Reliability based criteria are quite popular for optimal sensor network design. We present a modified definition of system reliability for sensor network design for two applications: reliable estimation of variables in a steady state linear flow process, and reliable fault detection and diagnosis for any process. Unlike the weakest-link based definition of system reliability in the literature, the proposed definition considers the entire system and is consistent with the reliability concept used in classical reliability literature. For each application, dual approaches for defining system reliability are proposed, and their analogy with the reliability problem in the classical reliability literature is established. Using examples and stochastic simulations, the advantage of using the proposed system reliability in contrast to the existing definition is illustrated. Part II of this series of articles presents methods for efficient generation of the system reliability function and its use in optimization-based approaches for designing optimal sensor networks.     

Fault handling in large water networks with online dictionary learning

Fault detection and isolation in water distribution networks is an active topic due to the nonlinearities of flow propagation and recent increases in data availability due to sensor deployment. Here, we propose an efficient two-step data driven alternative: first, we perform sensor placement taking the network topology into account; second, we use incoming sensor data to build a network model through online dictionary learning. Online learning is fast and allows tackling large networks as it processes small batches of signals at a time. This brings the benefit of continuous integration of new data into the existing network model, either in the beginning for training or in production when new data samples are gathered. The proposed algorithms show good performance in our simulations on both small and large-scale networks.     

一种北斗联合低轨星座的导航增强方法研究

单纯依靠北斗导航系统提供定位导航授时服务,存在卫星信号落地功率低、易受遮蔽和阻断的不足。针对此问题,研究了一种北斗联合低轨星座实现导航增强的系统架构;提出了一种新的适应严重遮蔽或干扰条件下,基于到达时间(TOA)和到达频率(FOA)联合观测的定位解算算法;对高中低轨混合星座条件下的覆盖特性和精度衰减因子进行了仿真分析。分析结果表明,用户可见星数平均增加了64.2%,位置精度衰减因子(PDOP)平均改善了28.7%。研究结果可为下一代北斗的论证设计与研制建设提供参考借鉴。     

黑龙江省节水增粮行动(2012—2015年)实施方案

文章通过对黑龙江省高效节水现状,存在问题的分析,结合黑龙江省高效节水发展的支撑能力,阐述黑龙江省节水增粮目标、任务及总体布局,为黑龙江省2012—2015年节水增粮实施提供依据。     

Diffuse color patterning using blended electrochromic polymers for proof‐of‐concept adaptive camouflage plaques

A study using three different pairs of electrochromic polymers (ECPs) synthesized onto plaques by means of a modified vapor phase polymerization (VPP) technique is presented. Restriction of the respective polymerization times, allowed both faster and slower polymerizing monomers to be controlled, and produced blended plaques with visually diffuse interfaces. The ECPs within the blended plaques retain their individual electrochromic behavior and when encapsulated into an electrochromic device, show outstanding optical switching performance with little degradation evident over 10,000 cycles, coupled with a switching time of the order of 1 second. Blends also allow multiple diffuse color changes within an electrochromic device, due to the difference in oxidation potentials of the individual ECPs, making them candidates for adaptive camouflage use. © 2015 Wiley Periodicals, Inc. J. Appl. Polym. Sci. 2015 , 132, 42158.