Improvement of Binocular Reconstruction Algorithm for Measuring 3D Pavement Texture Using a Single Laser Line Scanning Constraint

The dense and accurate measurement of 3D texture is helpful in evaluating the pavement function.To form dense mandatory constraints and improve matching accuracy,the traditional binocular reconstruction technology was improved threefold.First,a single moving laser line was introduced to carry out global scanning constraints on the target,which would well overcome the difficulty of installing and recognizing excessive laser lines.Second,four kinds of improved algorithms,namely,disparity replacement,superposition synthesis,subregion segmentation,and subregion segmentation centroid enhancement,were established based on different constraint mechanism.Last,the improved binocular reconstruction test device was developed to realize the dual functions of 3D texture measurement and precision self-evaluation.Results show that compared with traditional algorithms,the introduction of a single laser line scanning constraint is helpful in improving the measurement’s accuracy.Among various improved algorithms,the improvement effect of the subregion segmentation centroid enhancement method is the best.It has a good effect on both overall measurement and single pointmeasurement,which can be considered to be used in pavement function evaluation.

Research on Kalman Filtering Algorithmfor Deformation Information Series ofSimilar Single-Difference Model

Using similar single-difference methodology(SSDM) to solve the deformation values of the monitoring points, there is unstability of the deformation information series, at sometimes.In order to overcome this shortcoming, Kalman filtering algorithm for this series is established,and its correctness and validity are verified with the test data obtained on the movable platform in plane. The results show that Kalman filtering can improve the correctness, reliability and stability of the deformation information series.

Rolling optimization algorithm based on collision window for single machine scheduling problem

Focusing on the single machine scheduling problem which minimizes the total completion time in the presence of dynamic job arrivals, a rolling optimization scheduling algorithm is proposed based on the analysis of the character and structure of scheduling. An optimal scheduling strategy in collision window is presented. Performance evaluation of this algorithm is given. Simulation indicates that the proposed algorithm is better than other common heuristic algorithms on both the total performance and stability.

Improved Interleaved Single-Ended Primary Inductor-Converter forSingle-Phase Grid-Connected System

The generation of electricity based on renewable energy sources,parti-cularly Photovoltaic(PV)system has been greatly increased and it is simply insti-gated for both domestic and commercial uses.The power generated from the PV system is erratic and hence there is a need for an efficient converter to perform the extraction of maximum power.An improved interleaved Single-ended Primary Inductor-Converter(SEPIC)converter is employed in proposed work to extricate most of power from renewable source.This proposed converter minimizes ripples,reduces electromagnetic interference due tofilter elements and the contin-uous input current improves the power output of PV panel.A Crow Search Algo-rithm(CSA)based Proportional Integral(PI)controller is utilized for controlling the converter switches effectively by optimizing the parameters of PI controller.The optimized PI controller reduces ripples present in Direct Current(DC)vol-tage,maintains constant voltage at proposed converter output and reduces over-shoots with minimum settling and rise time.This voltage is given to single phase grid via 1�Voltage Source Inverter(VSI).The command pulses of 1�VSI are produced by simple PI controller.The response of the proposed converter is thus improved with less input current.After implementing CSA based PI the efficiency of proposed converter obtained is 96%and the Total Harmonic Distor-tion(THD)is found to be 2:4%.The dynamics and closed loop operation is designed and modeled using MATLAB Simulink tool and its behavior is performed.

Fast Fourier single-pixel imaging based on Sierra–Lite dithering algorithm

The single-pixel imaging(SPI) technique is able to capture two-dimensional(2 D) images without conventional array sensors by using a photodiode. As a novel scheme, Fourier single-pixel imaging(FSI) has been proven capable of reconstructing high-quality images. Due to the fact that the Fourier basis patterns(also known as grayscale sinusoidal patterns)cannot be well displayed on the digital micromirror device(DMD), a fast FSI system is proposed to solve this problem by binarizing Fourier pattern through a dithering algorithm. However, the traditional dithering algorithm leads to low quality as the extra noise is inevitably induced in the reconstructed images. In this paper, we report a better dithering algorithm to binarize Fourier pattern, which utilizes the Sierra–Lite kernel function by a serpentine scanning method. Numerical simulation and experiment demonstrate that the proposed algorithm is able to achieve higher quality under different sampling ratios.

A new integration algorithm for finite deformation of thermo-elasto-viscoplastic single crystals

An algorithm for integrating the constitutive equations in thermal framework is presented, in which the plastic deformation gradient is chosen as the integration variable. Compared with the classic algorithm, a key feature of this new approach is that it can describe the finite deformation of crystals under thermal conditions. The obtained plastic deformation gradient contains not only plastic defor- mation but also thermal effects. The governing equation for the plastic deformation gradient is obtained based on ther- mal multiplicative decomposition of the total deformation gradient. An implicit method is used to integrate this evo- lution equation to ensure stability. Single crystal 1 100 aluminum is investigated to demonstrate practical applications of the model. The effects of anisotropic properties, time step, strain rate and temperature are calculated using this integration model.

Algorithms for single machine scheduling with availability constraints

It is a NP-hard problem to schedule a list of nonresumable jobs to the available intervals of an availability-constrained single machine to minimize the scheduling length. This paper transformed this scheduling problem into a variant of the variable-sized bin packing problem, put forward eight bin packing algorithms adapted from the classic one-dimensional bin packing problem and investigated their performances from both of the worst-case and the average-case scenarios. Analytical results show that the worst-case performance ratios of the algorithms are not less than 2. Experimental results for average cases show that the Best Fit and the Best Fit Decreasing algorithm outperform any others for independent and precedence-constrained jobs respectively.

A Genetic Algorithm for Single Machine Scheduling with Fuzzy Processing Time and Multiple Objectives

In this paper, by considering the fuzzy nature of the data in real-life problems, single machine scheduling problems with fuzzy processing time and multiple objectives are formulated and an efficient genetic algorithm which is suitable for solving these problems is proposed. As illustrative numerical examples, twenty jobs processing on a machine is considered. The feasibility and effectiveness of the proposed method have been demonstrated in the simulation.

Algorithms for Multicriteria Scheduling Problems to Minimize Maximum Late Work, Tardy, and Early

This study examines the multicriteria scheduling problem on a single machine to minimize three criteria: the maximum cost function, denoted by maximum late work (Vmax), maximum tardy job, denoted by (Tmax), and maximum earliness (Emax). We propose several algorithms based on types of objectives function to be optimized when dealing with simultaneous minimization problems with and without weight and hierarchical minimization problems. The proposed Algorithm (3) is to find the set of efficient solutions for 1//F (Vmax, Tmax, Emax) and 1//(Vmax + Tmax + Emax). The Local Search Heuristic Methods (Descent Method (DM), Simulated Annealing (SA), Genetic Algorithm (GA), and the Tree Type Heuristics Method (TTHM) are applied to solve all suggested problems. Finally, the experimental results of Algorithm (3) are compared with the results of the Branch and Bound (BAB) method for optimal and Pareto optimal solutions for smaller instance sizes and compared to the Local Search Heuristic Methods for large instance sizes. These results ensure the efficiency of Algorithm (3) in a reasonable time.

An Algorithm for Solving Generalized Single Row Facility Layout Problem

Layout design problem is to determine a suitable arrangement for the departments so that the total costs associated with the flow among departments become least. Single Row Facility Layout Problem, SRFLP, is one of the layout problems that have many practical applications. This problem and its specific scenarios are often used to model many of the raised issues in the field of facility location. SRFLP is an arrangement of n departments with a specified length in a straight line so that the sum of the weighted distances between the pairs of departments is minimized. This problem is NP-hard. In this paper, first, a lower bound for a special case of SRFLP is presented. Then, a general case of SRFLP is presented in which some new and real assumptions are added to generate more practical model. Then a lower bound, as well as an algorithm, is proposed for solving the model. Experimental results on some instances in literature show the efficiency of our algorithm.

An Improved Ant Colony Algorithm for a Single-machine Scheduling Problem with Setup Times

Motivated by industrial applications we study a single-machine scheduling problem in which all the jobs are mutu- ally independent and available at time zero.The machine processes the jobs sequentially and it is not idle if there is any job to be pro- cessed.The operation of each job cannot be interrupted.The machine cannot process more than one job at a time.A setup time is needed if the machine switches from one type of job to another.The objective is to find an optimal schedule with the minimal total jobs’completion time.While the sum of jobs’processing time is always a constant,the objective is to minimize the sum of setup times.Ant colony optimization(ACO)is a meta-heuristic that has recently been applied to scheduling problem.In this paper we propose an improved ACO-Branching Ant Colony with Dynamic Perturbation(DPBAC)algorithm for the single-machine schedul- ing problem.DPBAC improves traditional ACO in following aspects:introducing Branching Method to choose starting points;im- proving state transition rules;introducing Mutation Method to shorten tours;improving pheromone updating rules and introduc- ing Conditional Dynamic Perturbation Strategy.Computational results show that DPBAC algorithm is superior to the traditional ACO algorithm.

Application of Fuzzy Logic Algorithm to Single-Molecule Force Spectroscopy of the Streptavidin-Biotin System

The rupture force of the streptavidin-biotin complex was investigated using atomic force microscopy (AFM). The most frequently observed rupture force (MFOF), which is essential for the evaluation of the potential landscape, was evaluated by processing 22,500 force curves using two methods. One method is a conventional method, which is usually built in commercial AFM systems, i.e., difference between the baseline value and the minimum force value in the force curve. The other is a detection of rupture events based on a fuzzy logic algorithm to detect the rupture event from analyzing the shape of the force curves. Our statistical analysis revealed that the conventional method exhibited a significant artifact, which is the increase in the population of small forces comparable to thermal noise of cantilevers, resulting in a smaller MFOF. Based on this finding, we discuss the choice of a method and its effecton the illustrated potential landscapes of ligand-receptor complexes.

基于改进的single-pass网络舆情话题发现研究

舆情监控系统解决的关键问题是如何有效且精确地对文本进行聚类,以便从大量Web网页中发现网络舆情热点话题。single-pass算法是话题发现中最常用的文本聚类算法,但其在文本聚类的精度和时效方面存在不足,因而论文在对大量新闻报道语料进行深入分析的基础上,从三个方面对single-pass进行了改进。通过实验求证,发现改进后的single-pass算法在漏检率、误检率和耗费函数等方面有了明显改善。

New Method for Solving GPS Deformation Monitoring Information at Single Epoch

Based on the analyses for the characteristics of high precise GPS defor-mation monitor,according to the spatial relationship among the satellite, base point and monitoring point a new model and its corresponding algorithm were presented to solve the monitoring point deformation directly at single epoch. In this method the carrier phases is used as the basic observations, and the initial condition is precise baseline vectors obtained in the first period observations between the base point and monitoring point. This model is called the similar single difference model (SSDM). The main error sources effecting the accuracy of deformations were analyzed briefly, the single epoch algorithm of the receiver clock offset was advanced. The numerical results of test data show that the SSDM and the single epoch algorithm of receiver clock offset advanced are reliable and correct.

Wind-induced internal pressure fluctuations of structure with single windward opening

A frequency domain method for estimating wind-induced fluctuating internal pressure of structure with single windward opening is presented in this paper and wind tunnel tests were carried out to verify the theory. The nonlinear differential equation of internal pressure dynamics and iteration algorithm were applied to calculate fluctuating internal pressure and time domain analysis was used to verify the accuracy of the proposed method. A simplified estimation method is also provided and its scope of application is clarified. The mechanism of internal pressure fluctuation is obtained by using the proposed method in the frequency domain and a new equivalent opening ratio is defined to evaluate internal pressure fluctuation. A series of low-rise building models with various openings and internal volumes were designed for wind tunnel tests with results agreeing well with analytical results. It is shown that the proposed frequency domain method based on Gaussian distribution of internal pressure fluctuations can be applied to predict the RMS internal pressure coefficient with adequate accuracy for any opening dimensions, while the simplified method can only be used for structure with single dominant opening. Helmholtz resonance is likely to occur when the equivalent opening ratio is adequately high, and controlling individual opening dimension is an effective strategy for avoiding Helmholtz resonance in engineering.

Functional-type Single-input-rule-modules Connected Neural Fuzzy System for Wind Speed Prediction

Wind is one kind of clean and free renewable energy sources. Wind speed plays a pivotal role in the wind power output. However, due to the random and unstable nature of the wind, accurate prediction of wind speed is a particularly challenging task. This paper presents a novel neural fuzzy method for the hourly wind speed prediction. Firstly, a neural structure is proposed for the functional-type single-input-rule-modules(FSIRMs) connected fuzzy inference system(FIS) to combine the merits of both the FSIRMs connected FIS and the neural network. Then, in order to achieve both the smallest training errors and the smallest parameters, a least square method based parameter learning algorithm is presented for the proposed FSIRMs connected neural fuzzy system(FSIRMNFS). Further,the proposed FSIRMNFS and its parameter learning algorithm are applied to the hourly wind speed prediction. Experiments and comparisons are also made to show the effectiveness and advantages of the proposed approach. Experimental results verified that our study has presented an effective approach for the hourly wind speed prediction. The proposed approach can also be used for the prediction of wind direction, wind power and some other prediction applications in the research field of renewable energy.

Single Epoch GPS Deformation Signals Extraction and Gross Error Detection Technique Based on Wavelet Transform

Wavelet theory is efficient as an adequate tool for analyzing single epoch GPS deformation signal. Wavelet analysis technique on gross error detection and recovery is advanced. Criteria of wavelet function choosing and Mallat decomposition levels decision are discussed. An effective deformation signal extracting method is proposed, that is wavelet noise reduction technique considering gross error recovery, which combines wavelet multi-resolution gross error detection results. Time position recognizing of gross errors and their repairing performance are realized. In the experiment, compactly supported orthogonal wavelet with short support block is more efficient than the longer one when discerning gross errors, which can obtain more finely analyses. And the shape of discerned gross error of short support wavelet is simpler than that of the longer one. Meanwhile, the time scale is easier to identify.

基于改进Single-Pass算法的网络新闻话题发现

通过改进的Single-Pass增量文本聚类算法,以话题为粒度对新闻信息进行组织,实现网络新闻话题的发现.该方法考虑了新闻的动态性和时间特性,在特征词项权重计算中从词项在标题和正文中的位置信息及词项的增量文档频率两方面进行优化,同时在相似度的计算中添加了时间因素及聚类中动态更新话题的质心向量.应用基于主题的网络爬虫构建的新闻等语料作为测试数据集,实验结果表明,改进算法较传统算法在耗费代价和错检率上分别降低0.34%和1.57%,验证了改进算法的有效性和准确性.

基于改进Single-Pass算法的话题发现技术研究

为了在海量的移动互联网数据中自动识别出新闻话题,分析经典Single-Pass聚类算法及其不足,提出针对性改进方法完成新闻话题发现。改进算法继承Single-Pass聚类算法的原理,通过对关键信息加权和引入时间因子提高算法的聚类精度;通过设置话题中心与待聚类文本比较来降低算法的计算开销。实验表明,改进后的算法相比于经典算法在准确率、召回率和F值三个指标上有所提高。

基于改进Single-pass 算法的新闻话题演化跟踪算法

随着信息技术的发展,每天都有大量的新闻文本在互联网上发布、转发,在这样的海量信息环境下,如何快速定位自己感兴趣的话题、追踪其发展趋势已成了近年来的研究热点。面向互联网上新闻文本,提出聚类阈值的估计方法对已有的Single-pass算法进行优化,进而基于时间片设计一个新闻文本演化算法。在新华网等四个网站上采集新闻数据并进行实验,实验表明所提算法可有效跟踪新闻话题的演化过程。