理工科学生英语口语现状分析及对策

着力从客观方面总结并分析理工科学生张不开口说英语的主要原因,提出语言本身如词汇、语音及语调、语法与语用等方面的应对策略,旨在有目的地提高大学英语教学。     

A Low Power Error Detection in the Syndrome Calculator Block for Reed-Solomon Codes: RS(204,188)

Reed-Solomon (RS) codes have been widely adopted in many modern communication systems. This paper describes a new method for error detection in the syndrome calculator block of RS decoders. The main feature of this method is to prove that it is possible to compute only a few syndrome coeffi-cients — less than half — to detect whether the codeword is correct. The theoretical estimate of the prob-ability that the new algorithm failed is shown to depend on the number of syndrome coefficients computed. The algo...     

基于手指运动方向的动态碰撞检测算法及实现

通过对虚拟手抓握物体时手指运动过程的分析,提出基于手指运动方向的动态碰撞检测算法,在详细描述该算法的基础上,给出算法流程图、算法实现框图和应用实例。针对单个手指与球体的接触过程,将此动态碰撞检测算法和传统的静态碰撞检测算法进行性能测试比较,结果证实该动态碰撞检测算法在总体性能上优于传统静态碰撞检测算法,主要体现在提高了抓握操作仿真过程中碰撞检测阶段的运行速度、解决了抓握操作中以多面体模型之间的碰撞检测仿真实体模型之间的碰撞检测问题。该动态碰撞检测算法并可以推广应用于其他动态碰撞检测仿真。     

四卡问题的新视角——社会契约理论

Cosmides所提出的社会契约理论表明,人的推理能力具有领域特殊性的和内容依赖性。这不仅挑战了传统的推理假设,更以一种超越常规的方式促进了心理学特别是认知和发展心理学的发展。     

龙桥铁矿复杂采空区的探测及处理方案

安徽省庐江县龙桥铁矿-320 m水平采空区,发生局部塌落导致现有采空区形态不详,为保证下部矿体正常安全开采,在地表不允许塌落的情况下,采用留设隔离矿柱的方案来隔离上部采空区.在钻孔探测确定采空区形态的基础上,应用FLAC3D程序建立三维数字模型,分析了留设不同厚度隔离层对整个采空区应力分布的影响及自身稳定程度.结果表明:留设25 m厚的水平隔离矿柱可以有效地分担地压分布情况,能够保证下部矿体安全开采.     

基于边缘组合算法的似物性采样研究

利用图像中的边缘信息对似物性窗口进行定性分析,设计了一种采用边缘组合算法的采样,降低了采样数量的同时保证了窗口精度,并用一种基于边缘的似物性估计为这些窗口排序,在较短的时间内为物体检测算法提供高精度的建议窗口.在VOC2007测试集中该算法在性能上达到了真正的平衡,限定每张图片输出1 000个窗口时,不仅达到了0.2s的计算速度,而且在0.7的重叠率条件下命中率高达79%,与其他似物性采样相比,该算法具有更强的通用性和适用性.     

电火花线切割加工中放电间隙状态的实时检测

通过对电火花放电状态的分析,提出了基于数字电路的电火花线切割(WEDM)放电间隙的实时检测方法。采用对单位时间内放电状态的统计,得到电火花线切割过程中各种状态的概率,为电火花线切割的智能控制提供控制依据。试验表明,该方法能有效检测WEDM加工中放电间隙的状态,为进一步研究WEDM智能加工控制系统提供了可靠的控制依据。     

纬编针织物疵点的图像分割方法

分别采用Otsu法和CNN两种方法对疵点图像进行了分割.在比较两种图像分割技术的基础上,提出了一种对于图像增强的预处理方法.用带有破洞、横路和漏针的纬编罗纹针织物作为材料进行实验.结果表明,所提出的图像增强方法对疵点的分割有很好的促进作用.     

Cooperative Sensor Anomaly Detection Using Global Information

Sensor networks are deployed in many application areas nowadays ranging from environment monitoring, industrial monitoring, and agriculture monitoring to military battlefield sensing. The accuracy of sensor readings is without a doubt one of the most important measures to evaluate the quality of a sensor and its network. Therefore, this work is motivated to propose approaches that can detect and repair erroneous (i.e., dirty) data caused by inevitable system problems involving various hardware and software components of sensor networks. As information about a single event of interest in a sensor network is usually reflected in multiple measurement points, the inconsistency among multiple sensor measurements serves as an indicator for data quality problem. The focus of this paper is thus to study methods that can effectively detect and identify erroneous data among inconsistent observations based on the inherent structure of various sensor measurement series from a group of sensors. Particularly, we present three models to characterize the inherent data structures among sensor measurement traces and then apply these models individually to guide the error detection of a sensor network. First, we propose a multivariate Gaussian model which explores the correlated data changes of a group of sensors. Second, we present a Principal Component Analysis (PCA) model which captures the sparse geometric relationship among sensors in a network. The PCA model is motivated by the fact that not all sensor networks have clustered sensor deployment and clear data correlation structure. Further, if the sensor data show non-linear characteristic, a traditional PCA model can not capture the data attributes properly. Therefore, we propose a third model which utilizes kernel functions to map the original data into a high dimensional feature space and then apply PCA model on the mapped linearized data. All these three models serve the purpose of capturing the underlying phenomenon of a sensor network from its global view, and then guide the error detection to discover any anomaly observations. We conducted simulations for each of the proposed models, and evaluated the performance by deriving the Receiver Operating Characteristic (ROC) curves.     

不同信息源条件下的目标初始位置分布预测

为使目标的初始位置分布假设更为合理，根据海上搜索编队所携带探测器材的特点，分析了搜索编队执行搜索任务时可能获得的多种信息源，并将之划分为精确信息源、模糊信息源和推测信息源3类，分别阐述了搜索编队在获得3种不同信息源情况下目标初始位置分布的预测方法．通过实例仿真，给出了海上搜索编队在获得不同信息源情况下的后续搜索行动建议，该方法可作为对海上搜索编队的搜索战法研究的参考．