Recommending suitable learning scenarios according to learners’ preferences: An improved swarm based approach

The paper presents a new approach for recommending suitable learning paths for different learners groups. Selection of the learning path is considered as recommendations to choosing and combining the sequences of learning objects (LOs) according to learners’ preferences. Learning path can be selected by applying artificial intelligence techniques, e.g. a swarm intelligence model. If we modify and/or change some LOs in the learning path, we should rearrange the alignment of new and old LOs and reallocate pheromones to achieve effective learning recommendations. To solve this problem, a new method based on the ant colony optimisation algorithm and adaptation of the solution to the changing optimum is proposed. A simulation process with a dynamic change of learning paths when new LOs are inserted was chosen to verify the method proposed. The paper contributes with the following new developments: (1) an approach of dynamic learning paths selection based on swarm intelligence, and (2) a modified ant colony optimisation algorithm for learning paths selection. The elaborated approach effectively assist learners by helping them to reach most suitable LOs according to their preferences, and tutors – by helping them to monitor, refine, and improve e-learning modules and courses according to the learners’ behaviour.     

Web proxy cache replacement scheme based on back-propagation neural network

Web proxy caches are used to reduce the strain of contemporary web traffic on web servers and network bandwidth providers. In this research, a novel approach to web proxy cache replacement which utilizes neural networks for replacement decisions is developed and analyzed. Neural networks are trained to classify cacheable objects from real world data sets using information known to be important in web proxy caching, such as frequency and recency. Correct classification ratios between 0.85 and 0.88 are obtained both for data used for training and data not used for training. Our approach is compared with Least Recently Used (LRU), Least Frequently Used (LFU) and the optimal case which always rates an object with the number of future requests. Performance is evaluated in simulation for various neural network structures and cache conditions. The final neural networks achieve hit rates that are 86.60% of the optimal in the worst case and 100% of the optimal in the best case. Byte-hit rates are 93.36% of the optimal in the worst case and 99.92% of the optimal in the best case. We examine the input-to-output mappings of individual neural networks and analyze the resulting caching strategy with respect to specific cache conditions.     

海上移动信道分析及抗多径接收机设计与仿真

海上舰船之间的通信通常工作在复杂的信道环境下,通信距离可远可近,不仅存在强的敌方恶意干扰,由于受地球弧度和海浪、船只等的遮挡,还存在深衰落和多径效应,因此设计海上通信系统时需要充分考虑这些不利因素的影响.针对海上移动信道的路径衰减特性,提出利用Longley-Rice模型建立海上移动信道模型,并对信道衰减模型进行了数值仿真;分析了多径对扩频系统伪码捕获的影响,提出利用Rake接收技术改善接收机的抗多径性能,并设计了一个Rake接收机结构,最后进行了仿真分析.仿真结果表明所设计的Rake接收机具有良好的抗多径能力,能够满足海上通信的需要.     

最小通路法在通信保密装备可靠性建模中的应用

针对通信保密装备可靠性建模难度大的问题,提出了一种新的适用于复杂系统的可靠性建模方法一最小通路法。通过在系统拓扑结构图上搜索出所有能够使系统正常工作的最小通路,建立系统的可靠性模型。该方法基于广义的网络拓扑结构,因此网络的源节点和目标节点不必局限于严格的定义,可以随意指定,具有很大的灵活性。实例证明,该方法可行有效。     

A study of replacement rules for a parallel fleet replacement problem based on user preference utilization pattern and alternative fuel considerations

Parallel fleet replacement problems deal with determining an optimal replacement schedule that results in a minimal total cost of owning and operating a fleet within a finite planning horizon. In this paper, the fleet consists of service vehicles, varying in age and cumulative mileage, commonly owned by government agencies or private business organizations. The paper focuses on three main aspects of the problem, including the effects of some widely used replacement rules, consideration of alternative fuel vehicles for replacement, and a new “user preference” utilization pattern. The vehicle replacement rules under study include purchase-new-vehicles-only, no-splitting-in-selling, one-purchase-choice, older-vehicles-selling, and all-or-none rules. The initial fleet consists of gasoline vehicles, while alternative-fuel vehicles using either compressed natural gas (CNG) or liquefied petroleum gas (LPG) are included as challengers in every replacement decision period. The user preference utilization pattern denotes a pattern in which yearly usage of vehicles declines as the vehicles grow older or have higher cumulative mileage. Integer programming formulation of the defined problem that incorporates these new factors is provided. Small numerical examples under various scenarios and a large problem instance with model parameters estimated from actual data are solved to optimality to gain some insights about the replacement rules and other considered factors.     

基于N-最短路径方法的中文词语粗分模型

预处理过程的词语粗切分, 是整个中文词语分析的基础环节, 对最终的召回率、准确率、运行效率起着重要的作用。词语粗分必须能为后续的过程提供少量的、高召回率的、中间结果。本文提出了一种基于N-最短路径方法的粗分模型, 旨在兼顾高召回率和高效率。在此基础上, 引入了词频的统计数据, 对原有模型进行改进, 建立了更实用的统计模型。针对人民日报一个月的语料库(共计185,192个句子), 作者进行了粗分实验。按句子进行统计, 2-最短路径非统计粗分模型的召回率为99.73%；在10-最短路径统计粗分模型中, 平均6.12个粗分结果得到的召回率高达99.94%, 比最大匹配方法高出15%, 比以前最好的切词方法至少高出6.4%。而粗分结果数的平均值较全切分减少了64倍。实验结果表明：N-最短路径方法是一种预处理过程中实用、有效的的词语粗分手段。     

板料多道次渐进成形下沉现象的模拟分析

基于ANSYS/LS-DYNA分析平台构建多道次渐进成形的有限元模型。对圆台件的3道次成形过程进行模拟,从节点运动角度分析下沉现象产生的原因:节点产生径向运动的同时伴随有Z轴负向运动。通过不同成形参数圆台两道次成形过程的模拟,分析道次间夹角、工具头直径及Z轴进给量对下沉现象的影响。提出下沉现象解决方案:根据后续道次成形下沉量的大小调整前一道次成形深度,对多道次渐进成形路径的设计有重要意义。     

Adaptive quality of service‐based routing approaches: development of neuro‐dynamic state‐dependent reinforcement learning algorithms

In this paper, we propose two adaptive routing algorithms based on reinforcement learning. In the first algorithm, we have used a neural network to approximate the reinforcement signal, allowing the learner to take into account various parameters such as local queue size, for distance estimation. Moreover, each router uses an online learning module to optimize the path in terms of average packet delivery time, by taking into account the waiting queue states of neighbouring routers. In the second algorithm, the exploration of paths is limited to N‐best non‐loop paths in terms of hops number (number of routers in a path), leading to a substantial reduction of convergence time. The performances of the proposed algorithms are evaluated experimentally with OPNET simulator for different levels of traffic's load and compared with standard shortest‐path and Q‐routing algorithms. Our approach proves superior to classical algorithms and is able to route efficiently even when the network load varies in an irregular manner. We also tested our approach on a large network topology to proof its scalability and adaptability. Copyright © 2006 John Wiley & Sons, Ltd.     

海上搜救雷达应答器天线架设高度的研究

研究了多径和海面大气折射这两种环境因素对雷达搜索应答器最远距离的影响,使用PE方程计算了不同蒸发波导高度条件下导航雷达和应答器发射信号的传播衰减,通过对计算结果分析和解释,结合东海试验的实测数据,得出应答器天线高度的最佳选择。