海潮模型在珠江口潮位预测中的精度评估

结合卫星测高技术的海潮模型能方便、精确地模拟大洋潮汐,可用于缺乏观测资料的地区。为评估该方法在珠江河口潮位预测应用中的精度,本文采用NAO.99b、OTPS和WWT等3种海潮模型预测珠江口不同验潮站的潮位过程,与实测数据对比并计算误差均方根。分析结果表明,海潮模型可以较好地预测珠江河口区潮汐基本时间特征,潮位预测精度在一定区域、一定时段不低于传统的预测方法。口门附近尤其口外的预测精度明显高于口内;在洪水期精度下降但口外开阔区域影响较小;在口门处,潮优型河口湾的预测精度高于径流型河口。3种模型中,推荐使用WWT。     

An iterative HAM approach for nonlinear boundary value problems in a semi-infinite domain

In this paper, we propose an iterative approach to increase the computation efficiency of the homotopy analysis method (HAM), a analytic technique for highly nonlinear problems. By means of the Schmidt–Gram process (Arfken et al., 1985)  [15], we approximate the right-hand side terms of high-order linear sub-equations by a finite set of orthonormal bases. Based on this truncation technique, we introduce the M$M$th-order iterative HAM by using each M$M$th-order approximation as a new initial guess. It is found that the iterative HAM is much more efficient than the standard HAM without truncation, as illustrated by three nonlinear differential equations defined in an infinite domain as examples. This work might greatly improve the computational efficiency of the HAM and also the Mathematica package BVPh for nonlinear BVPs.     

Distributed clock skew and offset estimation from relative measurements in mobile networks with Markovian switching topology

We analyze a distributed algorithm for the estimation of scalar parameters belonging to nodes in a mobile network from noisy relative measurements. The motivation comes from the problem of clock skew and offset estimation for the purpose of time synchronization. The time variation of the network was modeled as a Markov chain. The estimates are shown to be mean square convergent under fairly weak assumptions on the Markov chain, as long as the union of the graphs is connected. Expressions for the asymptotic mean and correlation are also provided.     

Robust linear output feedback controller for autonomous landing of a quadrotor on a ship deck

Ship deck landing control of a quadrotor requires certain robustness with respect to ship heave motion. Typical systems only provide relative height, therefore do not have relative heave rate information. In this paper, a linear output feedback control consisting of a full state feedback controller and a Luenberger observer is formulated. Invariant ellipsoid method is used to formulate an estimation of a bound on the response of a linear output feedback-controlled system subjected to external disturbances and measurement noise. The gains that result in a minimum bound are optimized using a gradient descent iterative approach proposed in this paper where the invariant ellipsoid condition is linearized into a tractable LMI condition. This approach is applied to a simulation of a quadrotor landing on a ship deck and results are compared with other gains. The gains selected using the proposed approach exhibits improved robustness to external disturbances and measurement noise.     

Effects of actuator and sensor bandwidths in intelligent cruise control of autonomous vehicles. Part II: performance

We analyse disturbance rejection for a platoon of vehicles with intelligent cruise control, both for the spatially discrete model and the continuum model with open and periodic boundary conditions. By explicitly calculating the eigenmodes for both the discrete and the continuum models, we derive the dynamic response of an individual discrete mode, as well as the response of a single vehicle to disturbances generated through either boundary vehicles or vehicles within the platoon. It is shown that if the biasing is small then the n-mode truncated continuum model and the spatially discrete model predict same qualitative responses to disturbances for the lower order modes. In the case of periodic boundary conditions, the two types of models predict quantitatively the same responses to disturbances for a range of feedback gains.     

A job‐plan based performance evaluation for construction value engineering study

Abstract

Value Engineering can reduce costs and enhance the value of projects. Currently, the acceptance rate of Value Engineering Study (VES) recommendations and total potential savings are considered the principal performance indicators of a VES. In reality the success of a VES depends on numerous interrelated factors not easy for a VES team to control. However, a study team can ensure the success of a VES by fully implementing a VES job plan. Thus, realizing a job plan is a principal contribution toward insuring the success of the VES. This study presents a novel model that is able to evaluate the performance of a VES for a construction project. Two questionnaires, distributed to VE experts, were used to collect data needed for this research. Factor analysis, AHP, and SWAM were applied to build the VES performance evaluation model which consists of six evaluation groups and thirty‐two evaluation items. A real‐life VES for a construction project was then analyzed using the proposed model to demonstrate its usefulness in performance assessment. Defects of the VES were identified and suggestions were provided for the particular VES. The proposed model can be used by VES teams for self‐diagnosis, improvement, and motivation in achieving enhanced performance.     

Detecting near-duplicate documents using sentence-level features and supervised learning

We present a novel method for detecting near-duplicates from a large collection of documents. Three major parts are involved in our method, feature selection, similarity measure, and discriminant derivation. To find near-duplicates to an input document, each sentence of the input document is fetched and preprocessed, the weight of each term is calculated, and the heavily weighted terms are selected to be the feature of the sentence. As a result, the input document is turned into a set of such features. A similarity measure is then applied and the similarity degree between the input document and each document in the given collection is computed. A support vector machine (SVM) is adopted to learn a discriminant function from a training pattern set, which is then employed to determine whether a document is a near-duplicate to the input document based on the similarity degree between them. The sentence-level features we adopt can better reveal the characteristics of a document. Besides, learning the discriminant function by SVM can avoid trial-and-error efforts required in conventional methods. Experimental results show that our method is effective in near-duplicate document detection.     

基础-任务驱动模式在《微生物学基础》实验教学中的改革初探

任务驱动是高职教育正在推广的"教、学、做"一体化的一种教学模式,能激发学生的思维,发挥学生的主动性及与教师之间的深层次沟通。基础实验则有助于学生掌握微生物学基础实验技术与技能,为任务驱动教学的顺利展开奠定基础。在《微生物学基础》实验教学过程中进行基础-任务驱动模式教学,教学效果显著,学生综合技能大有提高。     

Decision making for contractor insurance deductible using the evolutionary support vector machines inference model

Loss risk during the course of a construction project may be described in terms of frequency (i.e., loss frequency) and severity (i.e., loss severity). This study focused on improving the methodology used to evaluate loss risk. The authors first identified the common attributes of building construction project loss through a review of the literature and interviews with experts. Objective factors adequate to describe loss attributes were selected as model inputs. The loss prediction model was created using the evolutionary support vector machine inference model (ESIM) and deployed to evaluate loss frequency and loss severity. This research combined the deductible efficient frontier curve with the indifference curve of risk versus insurance cost, and developed criteria for optimal insurance deductible decision making.