试论加强文件管理的必要性

论述文件与档案的关系,分析提高文件管理的具体措施,强调加强文件管理的重要性.     

神经网络在船舶操纵中的应用研究

该文对人工神经网络用于船舶操纵动态特性的在线学习进行了研究,并提出了基于神经网络预报的操舵控制算法。仿真试验的结果表明了该控制算法的有效性。     

水火弯板建模系统研究

以逐步回归分析和改进的Ｂ－Ｐ神经网络两种方法为算法,基于Ｍｉｃｒｏｓｏｆｔ Ｖｉｓｕａｌ Ｂａｓｉｃ３．０软件平台,应用实船板样本数据,开发了水火弯板局部收缩量的建模系统。     

浅谈机场道面混凝土断裂产生的原因及预防措施

上海浦东国际机场场道板块的施工过程中出现了断裂现象。本文分析了断裂产生的原因及采取的相应措施,在实施中收到了显著效果。     

Feature extraction and modeling of welding quality monitoring in pulsed gas touch argon welding based on arc voltage signal

Arc sensing plays a significant role in the control and monitoring of welding quality for aluminum alloy pulsed gas touch argon welding （GTAW）. A method for online quality monitoring based on adaptive boosting algorithm is proposed through the analysis of acquired arc voltage signal. Two feature extraction algorithms were developed in time domain and frequency domain respectively to extract six statistic characteristic parameters before removing the pulse interference using the wavelet packet transform （WPT）, based on which the Adaboost classification model is successfully established to evaluate and classify the welding quality into two classes and the classified accuracy of the model is as high as 98.81%. The Adaboost algorithm has been verified to be feasible in the online evaluation of welding quality.     

浅谈基于无线的车-地通信系统

基于无线的CBTC列控系统代表了城市轨道交通信号系统的发展方向。介绍基于无线CBTC列控系统的基本原理,及广佛线实现车-地通信的方式和构成无线系统的车载设备及轨旁设备,分析基于无线的车-地通信方式的优点及不足。     

城市交通能耗区的识别及等级划分方法研究

随着社会经济的发展，机动车保有量急剧增长，城市化过程中交通拥堵问题日趋严重，交通能源消耗加剧。为了降低由此带来的损失，需要及时探明路网中交通效率低、能耗高的区域，并采取有效的交通管理措施。通过研究交通状态与能耗的关系，进行相应的交通参数分析，建立能耗区识别及等级划分模型，计算得到3个等级能耗区的界定阈值分别为0．411和0．678。     

板-桁模型计算钢筋混凝土构件抗扭强度综述

首先简单介绍了现有的钢筋混凝土构件抗扭强度计算的简化力学模型,并指出了板-桁模型提出的必要性,最后对板-桁模型进行了详细介绍,有关经验可供相关专业人员参考。     

甲醇汽油非常规排放测试研究

为了探讨汽车使用甲醇汽油后排气中非常规排放物的成分及含量,利用一台质谱分析仪对两辆汽车燃用甲醇汽油及普通汽油的排放物进行了分析,并对排放物中甲醇的含量进行了初步的研究。实验结果表明,汽油与甲醇汽油排放中物质种类基本一致,甲醇汽油排放物中还含有正丙醇、乙酸乙酯、苯酚、丁酸四种物质;甲醇汽油排放物中的甲醇含量很少,基本不会对环境造成影响。     

Poisson noise removal based on nonlocal total variation with Euler’s elastica pre-processing

An enhancement-based Poisson denoising method for photon-limited images is presented. The noisy image is firstly pre-processed for enhancing incomplete object information, and then it is denoised while preserving the restored structural details. A variational regularization model based on Euler’s elastica (EE) is proposed for image enhancement pre-processing. A nonlocal total variation (NLTV) regularization model is then employed in the second stage of image denoising. The above two optimization problems are solved by the alternating direction method of multipliers (ADMM). For Poissonian images with low image peak values, experiments demonstrate the validity and efficiency of the proposed method for both restoring geometric structure and removing noise.