Protecting local access telecommunications networks: Toward a minimum-cost solution

The problem of designing fibre-optic networks for local-access telecommunications generates (at least) three non-trivial subproblems. In the first of these subproblems one must determine how many fibre-optic cables (fibres) are required at either end of a street. In the next subproblem a minimum-cost network must be designed to support the fibres. The network must also provide distinct paths from either end of the street to the central exchange(s). Finally, the fibre-optic cables must be placed in protective covers. These covers are available in a number of different sizes, allowing some flexibility when covering each section of the network. In this paper we describe a dynamic programming (DP) formulation for finding a minimum-cost (protective) covering for the network (the third of the subproblems). This problem is a generalised set covering problem with side constraints and is further complicated by the introduction of fixed and variable welding costs. The DP formulation selects covers along each arc (in the network), but cannot exactly model the fixed costs and so does not guarantee optimality. We also describe an integer programming (IP) formulation for assessing the quality of the DP solutions. The cost of the networks constructed by the IP model is less than those designed using the DP model, but the saving is not significant for the problems examined (less than 0.1%). This indicates that the DP model will generally give very good solutions. Furthermore, as the problem dimensions grow, DP gives significantly better solution times than IP.     

Life is pleasant--and memory helps to keep it that way!

People's recollections of the past are often positively biased. This bias has 2 causes. The 1st cause lies in people's perceptions of events. The authors review the results of several studies and present several new comparative analyses of these studies, all of which indicate that people perceive events in their lives to more often be pleasant than unpleasant. A 2nd cause is the fading affect bias: The affect associated with unpleasant events fades faster than the affect associated with pleasant events. The authors review the results of several studies documenting this bias and present evidence indicating that dysphoria (mild depression) disrupts such bias. Taken together, this evidence suggests that autobiographical memory represents an important exception to the theoretical claim that bad is stronger than good. (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

Large deflection dynamics and control for planar continuum robots

This paper focuses on a class of robot manipulators termed "continuum" robots - robots that exhibit behavior similar to tentacles, trunks, and snakes. In previous work, we studied details of the mechanical design, kinematics, path-planning and small-deflection dynamics for continuum robots such as the Clemson "tentacle manipulator". In this paper, we discuss the dynamics of a planar continuum backbone section, incorporating a large-deflection dynamic model. Based on these dynamics, we formulate a vibration-damping setpoint controller, and include experimental results to illustrate the efficacy of the proposed controller.     

Promatech公司推出多用剑杆织机

意大利织机制造商Ｐｒｏｍａｔｅｃｈ公司以Ｓｏｍｅｔ品牌推出了一种新型剑杆织机。这种以“Ａｌｐｈａ”命名的织机于２００１年９月底首次在一个演示间里亮相，随后又成为新加坡ＩＴＭＡ　Ａｓｉａ展会上的一个亮点。Ｓｏｍｅｔ公司剑杆织机产品经理Ｐｉｅｒｍａｒｃｏ　Ａｒｎｏｌｄｉ先生说，这种新型织机操作简便，可靠性高和多用性强，能以非常高的织造速度织许多种织物。一、Ａｌｐｈａ剑杆织机的性能１．操作简便Ａｌｐｈａ的设计使操作工很容易接近机器和修复断头。例如：打纬点与胸梁之间的距离大幅度缩短，使操作工更容易用手来…     

K-winner networks.

A special class of mutually inhibitory networks is analyzed, and parameters for reliable K-winner performance are presented. The network dynamics are modeled using interactive activation, and results are compared with the sigmoid model. For equal external inputs, network parameters that select the units with the larger initial activations (the network converges to the nearest stable state) are derived. Conversely, for equal initial activations, networks that select the units with larger external inputs (the network converges to the lowest energy stable state) are derived. When initial activations are mixed with external inputs, anomalous behavior results. These discrepancies are analyzed with several examples. Restrictions on initial states are derived which ensure accurate K-winner performance when unequal external inputs are used.     

Towards deterministic downscaling of SMOS soil moisture using MODIS derived soil evaporative efficiency

A deterministic approach for downscaling ～ 40 km resolution Soil Moisture and Ocean Salinity (SMOS) observations is developed from 1 km resolution MODerate resolution Imaging Spectroradiometer (MODIS) data. To account for the lower soil moisture sensitivity of MODIS surface temperature compared to that of L-band brightness temperature, the disaggregation scale is fixed to 10 times the spatial resolution of MODIS thermal data (10 km). Four different analytic downscaling relationships are derived from MODIS and physically-based model predictions of soil evaporative efficiency. The four downscaling algorithms differ with regards to i) the assumed relationship (linear or nonlinear) between soil evaporative efficiency and near-surface soil moisture, and ii) the scale at which soil parameters are available (40 km or 10 km). The 1 km resolution airborne L-band brightness temperature from the National Airborne Field Experiment 2006 (NAFE'06) are used to generate a time series of eleven clear sky 40 km by 60 km near-surface soil moisture observations to represent SMOS pixels across the three-week experiment. The overall root mean square difference between downscaled and observed soil moisture varies between 1.4% v/v and 1.8% v/v depending on the downscaling algorithm used, with soil moisture values ranging from 0 to 15% v/v. The accuracy and robustness of the downscaling algorithms are discussed in terms of their assumptions and applicability to SMOS.     

Introduction of a nonlinearity measure for principal component models

Although principal component analysis (PCA) is an important tool in standard multivariate data analysis, little interest has been devoted to assessing whether the underlying relationship within a given variable set can be described by a linear PCA model or whether nonlinear PCA must be utilized. This paper addresses this deficiency by introducing a nonlinearity measure for principal component models. The measure is based on the following two principles: (i) the range of recorded process operation is divided into smaller regions; and (ii) accuracy bounds are determined for the sum of the discarded eigenvalues. If this sum is within the accuracy bounds for each region, the process is assumed to be linear and vice versa. This procedure is automated through the use of cross-validation. Finally, the paper shows the utility of the new nonlinearity measure using two simulation studies and with data from an industrial melter process.