加强研究生基层任职能力培养的思考

针对军校培养的硕士研究生到基层任职比例逐年增大,为进一步提高研究生培养质量,通过对学院已毕业的硕士研究生在基层部队任职情况的调研,分析了硕士研究生在基层部队任职中暴露出的问题和原因,提出了加强思想政治教育、增强培养的针对性以及与部队开展联合培养等建议.     

Compound stabilization/solidification of MSWI fly ash with trimercapto-s-triazine and cement

A new treatment technology of municipal solid waste incineration (MSWI) fly ash is presented in this paper. Feasibility of solidification/stabilization treatment of MSWI by successively adding trimercapto-s-triazine and cement, and the effect of addition, fly ash size and curing time were studied by batch tests. The results showed that MSWI posed a huge environmental risk, the partial distribution showed normal distribution approximately. Treatment of fly ash with trimercapto-s-triazine and cement showed a good effect, the leaching toxicity of treated fly ash solidified blocks with 2% trimercapto-s-triazine and 20% cement could meet the standard for pollution control on the landfill site of MSW in China after curing for 7 days, and the flexural strength of solidified blocks could reach 2.4 MPa. Ground fly ash had a positive effect on both leaching toxicity and strength.     

Tracking mobile users in wireless networks via semi-supervised colocalization

Recent years have witnessed the growing popularity of sensor and sensor-network technologies, supporting important practical applications. One of the fundamental issues is how to accurately locate a user with few labeled data in a wireless sensor network, where a major difficulty arises from the need to label large quantities of user location data, which in turn requires knowledge about the locations of signal transmitters or access points. To solve this problem, we have developed a novel machine learning-based approach that combines collaborative filtering with graph-based semi-supervised learning to learn both mobile users' locations and the locations of access points. Our framework exploits both labeled and unlabeled data from mobile devices and access points. In our two-phase solution, we first build a manifold-based model from a batch of labeled and unlabeled data in an offline training phase and then use a weighted k-nearest-neighbor method to localize a mobile client in an online localization phase. We extend the two-phase colocalization to an online and incremental model that can deal with labeled and unlabeled data that come sequentially and adapt to environmental changes. Finally, we embed an action model to the framework such that additional kinds of sensor signals can be utilized to further boost the performance of mobile tracking. Compared to other state-of-the-art systems, our framework has been shown to be more accurate while requiring less calibration effort in our experiments performed on three different testbeds.     

鄂尔多斯盆地东南部长7油层组沉积相研究

为了明确鄂尔多斯盆地东南部长7油层组沉积体系类型和沉积相展布特征,总结其沉积演化规律,以沉积学的基本原理和方法为指导,综合运用地球化学、盆地分析等理论和方法,通过野外露头、钻井、测井等资料的综合分析,认为鄂尔多斯盆地东南部长7油层组主要发育三角洲和湖泊沉积体系,可进一步划分为3类亚相,其中以三角洲前缘和深湖2种亚相为主．     

减震油弹性模量及疲劳特性试验台设计与实现

油液的体积弹性模量以及疲劳特性参数是油液非常重要的物理参数,在液压系统中,直接影响系统的稳定性和动态品质.研究设计了弹性模量及疲劳特性参数测试试验台,基于弹性模量的定义对弹性模量进行测量计算,同时以专用车辆油气悬挂装置为对象,对悬挂内液压油疲劳特性参数进行测试,如:温度、粘度等.完成控制系统以及数据采集系统的设计,与上位机实时通讯,实现测试过程的自动化.     

Global stabilization of a chain of integrators with input saturation and disturbances: A new approach

In this article, we solve the problem of global stabilization for a chain of integrators in the presence of input saturation and disturbances. A novel and elegant approach to solve this problem, in the absence of disturbances, was proposed by Teel (1992) using saturation functions and coordinate transformation. With Teel’s work as a foundation, many results have been proposed to improve the performance of controllers for a chain of integrators. Naturally, all such approaches also inherited the limitations of Teel’s approach. Most importantly, in the presence of uncertainties and disturbances, the transformation introduced in Teel (1992) would considerably shrink the region where the controller is unsaturated and, severely limit the level of uncertainties and disturbances which can be tolerated. In order to overcome these difficulties, a conceptually different approach which does not rely on the coordinate transformation is presented in this work. Specifically, modified saturation functions are directly applied to the tracking error of actual states as opposed to transformed fictitious states to develop a globally stable controller. The proposed controller is less conservative in terms of the level of uncertainties and disturbances which can be handled. In addition, arbitrarily good disturbance rejection in the unsaturated region can be achieved theoretically. Comparative simulation studies performed on a third order integrator chain verified the effectiveness of the proposed scheme.     

Porous haydite used as waste water filter medium for lake sludge

Porous haydite used as waste filter medium was prepared by dreging lake sludge to help solve the treatment problem of sludge and realize its reclamation. Several calcination regimes were considered and their effects on the pore structure and the properties such as the strength, the density, the filtering ability and the phosphate absorption ability of the haydite were investigated. For the mixture of 60% lake sludge and 40% fly ash in this experiment, the calcination regime with a pre-calcination period at about 600 °C, a temperature keeping period at 1 200 °C and a moderate cooling rate are recommended to prepare haydite with reasonable pore structure and good performances for its usage as the waste water filter media.     

基于遗传算法的关联议题并发谈判

基于遗传算法的并发谈判在电子商务应用中具有独特的优势,但已有的研究尚未考虑议题之间的相关性、动态权重的变化规则依赖于对手信息的获取,极大地限制了其使用价值.对此,提出议题分组的方法以解决议题的相关性问题,而议题权重的变化则采取从历史资源中发掘知识的方法进行动态调整.构建了基于遗传算法的关联性议题并发谈判模型,给出了模型的形式化描述、谈判算法设计和动态权重更新方案.通过对模型的实验和比较分析,证实了该方案能够更方便地满足用户谈判的多样性需求,解决谈判中议题关联性的问题,而且能够快速、有效地得出最优谈判结果.     

Preface

Recently, there has been a dramatic increase in research on data mining on social networks and social media. Theubiquitous nature of Web-enabled devices, including desktops,     

Probabilistic characterisation of model error using Gaussian mixture model—With application to Charpy impact energy prediction for alloy steel

A novel approach to characterise the model prediction errors using a Gaussian mixture model is proposed. The motivation for this work lies behind many data models that are developed through prediction error minimisation with the assumption of a normal noise distribution. When the noise is non-normal, which may often be the case in complicated data modelling scenarios, the model prediction errors may contain rich information, which can be further exploited for model refinement and improvement. The key contents presented in this paper include: choosing the relevant variables to form the error data, optimising the number of Gaussian components required for the error data modelling, and fitting the Gaussian mixture parameters using an expectation-maximisation algorithm. Application of the proposed method for further model improvement, within the framework of hybrid deterministic/stochastic modelling, is also discussed. Preliminary results on the real industrial Charpy impact energy data for heat-treated steels show its effectiveness for model error characterisation, and the potential for model performance improvement in terms of prediction accuracy as well as providing accurate prediction confidence intervals.