推土机智能化控制技术的现状与发展趋势

随着电子信息技术的进步,推土机正在向自动化、智能化方向发展。从行走系统智能控制、工作装置智能控制、故障诊断等方面介绍了推土机智能化控制技术的现状,从数字化机械施工、工作装置智能引导与自动控制、互联网大数据共享、机群智能化控制管理等方面分析了推土机智能化控制技术的发展趋势。     

南非矿产工业的现状、挑战和前景

南非是世界性矿业大国，对世界矿产品市场有重要影响。本文首先分析了南非矿业的发展现状，然后讨论了所面临的问题和挑战，包括恶化的生态环境、不断升高的矿山生产成本和老化的矿山、不乐观的矿山劳动安全、不断减少的矿业投资等。在此基础上，笔者简要讨论了南非矿产工业的发展前景问题，认为尽管有挑战，但与其它国家相比，南非矿业仍存在一系列比较优势和较大发展潜力。笔者进一步认为，只要化挑战为动力、落实好各项行动计划和创新政策，南非矿业仍会有一个辉煌的未来。     

玉簪属植物种质资源及其园林应用现状

对中国原产的玉簪属植物种质资源,进行收集调查,并阐述应用于园林的玉簪种、变种和品种的观赏特点,及其园林应用现状.通过比较研究,认为目前我国对国产原生种及其变种的应用开发力度不够,应大力开发玉簪属植物作为园林地被和盆栽观赏材料的潜力,并通过引种,充实国内玉簪属的品种资源,对我国玉簪属种质资源的园林应用,起到促进作用.     

从园林虫害发展动向和防治现状谈今后的防治策略--以葫芦岛园林虫害的综合防治为例

园林和森林存在很大差异,它有很大的人为因素,因此生态比较脆弱.防治害虫所使用的化学农药多且不合理,治理上没有长远打算,致使危害不断发生,这是目前普遍存在的现状.今后应在尊重生态规律的前提下,抓好园林几种主要害虫生命表的研究,建立预测预报模型,防治前确定虫害的经济阈值,找出适宜的决策依据,建立害虫综合动态模型和生态综合管理体系,最终达到自然控制的目的.     

Promotion Routes for Women Engineering Managers

ABSTRACT

Total quality management (TQM) has been increasingly accepted as a management philosophy. Criteria such as those contained in the Malcolm Baldrige National Quality Award (MBNQA) often guide TQM implementation. However, reports indicate that fully assessing TQM efforts is difficult and hiring experts to help with this task is expensive. Using survey instruments is an attractive alternative to full-scale assessment. Despite the availability of many papers covering organizational performance assessment, few instruments specifically address TQM evaluation. Furthermore, none of the TQM assessment instruments has been subjected to rigorous validation; thus, only modest confidence can be placed in results obtained from their use. This article proposes a quick and cost-effective instrument that is a simple questionnaire designed to assist organizations in conducting self-evaluations of their TQM programs. The proposed instrument is based on the seven categories of the MBNQA criteria and was developed in cooperation with the Excellence in Missouri Foundation, which administers the Missouri Quality Award (MQA). This article highlights how questionnaire results can be used to guide further TQM implementation efforts.     

A case study in evaluating the status of consolidation of a soft soil deposit by incomplete piezocone dissipation tests using laboratory and field data

By using the piezocone penetration test (PCPT or CPTu), one can develop not only a better understanding of the soil stratification, but also an understanding of soil behavior parameters related to soil compressibility, as well as soil strength. This paper describes a case study that utilizes incomplete piezocone dissipation test to estimate status of consolidation of a soil deposit. Incomplete pore pressure dissipation record of PCPT is extrapolated on an inverse time scale (1/t method) to estimate the “in situ” pore pressure and “residual excess” pore pressure. No case study has been reported in open literature where this methodology has been utilized to estimate the status of consolidation of the soil deposit. In this paper, the 1/t method was verified using dissipation data from rigorous calibration chamber tests and field test data.     

Driving on the motorway: the effect of alternating speed on driver's activation level and mental effort

When most of the driving tasks are performed automatically, a driver's level of alertness may decline, as has been pointed out in the study of the phenomenon called ‘highway hypnosis’. One possible countermeasure is to periodically vary the speed (Wertheim 1978), but the authors have not found any studies that directly assess the effectiveness of this countermeasure. The objective of our study has been to provide empirical evidence regarding the effects of this strategy on the level of driver activation on a motorway route in real traffic. In the present study activation level as indexed by a relative measure based on slow EEG activity tended to be significantly higher when speed was modified periodically than when it remained constant. In addition, this index tended to be progressively higher when the speed was constant during the first part of the route, while the same thing did not occur when the speed was modified periodically. Finally, no significant differences between the constant and varying speed conditions were obtained with respect to any of the cardiovascular indices related to the effort put into driving and the stress experienced in the situation.     

老工业园区的改造升级、转型发展策略初探--以赣州沙河工业园为例

沙河工业园经过十余年的发展，取得了较好的成绩。但随着城市总体规划的修编，沙河工业园在区域发展中的地位、角色，发生了重大的变化，园区发展面临转型、升级的新形势。本文以沙河工业园为例，提出了针对老工业园的改造升级、转型发展的策略。     

Stock trend prediction based on a new status box method and AdaBoost probabilistic support vector machine

Stock trend prediction is regarded as one of the most challenging tasks of financial time series prediction. Conventional statistical modeling techniques are not adequate for stock trend forecasting because of the non-stationarity and non-linearity of the stock market. With this regard, many machine learning approaches are used to improve the prediction results. These approaches mainly focus on two aspects: regression problem of the stock price and prediction problem of the turning points of stock price. In this paper, we concentrate on the evaluation of the current trend of stock price and the prediction of the change orientation of the stock price in future. Then, a new approach named status box method is proposed. Different from the prediction issue of the turning points, the status box method packages some stock points into three categories of boxes which indicate different stock status. And then, some machine learning techniques are used to classify these boxes so as to measure whether the states of each box coincides with the stock price trend and forecast the stock price trend based on the states of the box. These results would support us to make buying or selling strategies. Comparing with the turning points prediction that only considered the features of one day, each status box contains a certain amount of points which represent the stock price trend in a certain period of time. So, the status box reflects more information of stock market. To solve the classification problem of the status box, a special features construction approach is presented. Moreover, a new ensemble method integrated with the AdaBoost algorithm, probabilistic support vector machine (PSVM), and genetic algorithm (GA) is constructed to perform the status boxes classification. To verify the applicability and superiority of the proposed methods, 20 shares chosen from Shenzhen Stock Exchange (SZSE) and 16 shares from National Association of Securities Dealers Automated Quotations (NASDAQ) are applied to perform stock trend prediction. The results show that the status box method not only have the better classification accuracy but also effectively solve the unbalance problem of the stock turning points classification. In addition, the new ensemble classifier achieves preferable profitability in simulation of stock investment and remarkably improves the classification performance compared with the approach that only uses the PSVM or back-propagation artificial neural network (BPN).