试论英语学习中词典的使用

词典是汇集词语进行解释、为人们释疑解惑的工具书。初级英语学习者主要依靠教师授课进行学习,而中高级学习者有更多的时间利用英语词典进行自学。词典是英语学习者的必备工具书,但学习者未能充分利用。因此,有必要对以英语学习词典为主的工具书的使用进行探讨,从而得出结论:要使学习者从词典中充分获益,有必要对英语学习者进行词典使用方面的训练。     

探讨研究生学习动机与培养质量的相关性

以往研究研究生的学习动机侧重于量化研究,本文试图从质性研究的角度对当代研究生学习动机进行探讨,归纳出不同的学习类型,分析当代研究生学习动机与培养质量的关系,以及目前由于学习动机造成的培养质量问题,以提高研究生培养质量。     

Batch scheduling with step‐deteriorating processing times to minimize flowtime

Both topics of batch scheduling and of scheduling deteriorating jobs have been very popular among researchers in the last two decades. In this article, we study a model combining these two topics. We consider a classical batch scheduling model with unit‐jobs and batch‐independent setup times, and a model of step‐deterioration of processing times. The objective function is minimum flowtime. The optimal solution of the relaxed version (allowing non‐integer batch sizes) is shown to have a unique structure consisting of two consecutive decreasing arithmetic sequences of batch sizes. We also introduce a simple and efficient rounding procedure that guarantees integer batch sizes. The entire solution procedure requires an effort of O(n) (where nis the number of jobs.) © 2012 Wiley Periodicals, Inc. Naval Research Logistics, 2012     

A branch‐and‐price algorithm for parallel machine scheduling with time windows and job priorities

This paper presents a branch‐and‐price algorithm for scheduling n jobs on m nonhomogeneous parallel machines with multiple time windows. An additional feature of the problem is that each job falls into one of ρ priority classes and may require two operations. The objective is to maximize the weighted number of jobs scheduled, where a job in a higher priority class has “infinitely” more weight or value than a job in a lower priority class. The methodology makes use of a greedy randomized adaptive search procedure (GRASP) to find feasible solutions during implicit enumeration and a two‐cycle elimination heuristic when solving the pricing subproblems. Extensive computational results are presented based on data from an application involving the use of communications relay satellites. Many 100‐job instances that were believed to be beyond the capability of exact methods, were solved within minutes. © 2005 Wiley Periodicals, Inc. Naval Research Logistics, 2006     

钼的化合价对有机钼化合物的极压抗磨性能的影响

用四球机试验评价了所合成的有机钼化合物极压抗磨性能 .讨论了钼的化合价与有机钼化合物的极压抗磨性能的关系 .发现对黄原酸硫氧钼和硫代磷酸硫氧钼两类有机钼化合物均是含六价钼化合物的载荷性能最好 ;六价钼比五价钼化合物的反应活性高 ,可在更低的浓度下表现出最佳的抗磨效果 ;钼的化合价不影响硫代磷酸硫氧钼在基础油中的理化性能 .     

微分算子插值样条解析性质的一种新证法

讨论带线性泛函约束的微分算子插值样条 ,在空间Wm2 中给出了由约束泛函和微分算子构造再生核的普遍方法 ,利用微分算子及其共轭微分算子零空间基底之间的关系得到了微分算子插值样条解析性质新的推导方法。     

Opportunistic retooling of a flexible machine subject to failure

A set of jobs can be processed without interruption by a flexible machine only if the set of tools required by all jobs can be loaded in the tool magazine. However, in practice the total number of tools required by a job set would exceed the tool magazine capacity. In such situations, the job set has to be carefully partitioned at the start of the production run such that each partition can be processed without interruption. During the production run, if there are unscheduled machine downtimes due to machine failure, this provides an additional opportunity to optimally retool the magazine for a smaller job set consisting of just the unprocessed jobs. In this paper, we study job sequencing rules that allow us to minimize the total expected cost of machine down time due to machine failures and magazine retooling, assuming a dynamic re‐sequencing of the unprocessed jobs after each machine failure. Using these rules, we develop a branch‐and‐bound heuristic that allows us to solve problems of reasonable size. © 2001 John Wiley & Sons, Inc. Naval Research Logistics 48: 79–97, 2001     

上下文感知的深度弱监督图像哈希表示学习方法

针对现有深度监督图像哈希表示学习方法依赖于图像的类别信息,难以在现实中被广泛应用问题,利用与图像相关的标签信息作为监督信息,提出上下文感知的深度弱监督图像哈希表示学习方法。该方法一方面通过自适应捕获图像区域特征的相关上下文来增强它们的表示能力,另一方面通过引入判别损失来提高学习到的哈希码表示的判别性。在现有两个公开数据集上的大量实验结果证明了该方法的有效性。     

增量式神经网络聚类算法

神经网络模型具有强大的问题建模能力,但是传统的反向传播算法只能进行批量监督学习,并且训练开销很大。针对传统算法的不足,提出全新的增量式神经网络模型及其聚类算法。该模型基于生物神经学实验证据,引入新的神经元激励函数和突触调节函数,赋予模型以坚实的统计理论基础。在此基础上,提出一种自适应的增量式神经网络聚类算法。算法中引入"胜者得全"式竞争等学习机制,在增量聚类过程中成功避免了"遗忘灾难"问题。在经典数据集上的实验结果表明:该聚类算法与K-means等传统聚类算法效果相当,特别是在增量学习任务的时空开销方面具有较大优势。     

变工况下轴承健康监测的相关向量机与自适应阈值模型方法

工况在旋转机械运行过程中通常是变化的。变化的工况和故障一样,也会引起机械振动特征发生改变,从而引起诊断误差。为此,提出一种用于变工况下轴承健康监测的新方法。该方法使用相关向量机拟合振动特征的统计量随工况参数的变化,得到特征统计量与工况参数之间的连续函数关系;基于不同工况下的特征统计,构建自适应阈值模型。将该方法用于不同转速下的轴承健康监测,结果表明,当转速超过某一个较小的值时,该方法有效。