P2P应用层数据流量优化

为减少对主干网络带宽的消耗,提出了一套数据流量优化方法。首先通过把Peer间的邻居关系明确划分为物理邻居关系和逻辑邻居关系,并用探路者算法来发现Peer的物理邻居,实现拓扑匹配;然后在数据调度算法中,引入通报/退避机制,把大部分数据传输控制在城域网络内部。通过建立模拟仿真环境进行实验分析,证实了该方法可以减少90%以上的网络数据流量。     

Pricing decisions in a multi-criteria setting for product recovery facilities

Unpredictability in the arrival time and quantity of discarded products at product recovery facilities (PRFs) and varying demand for recovered components contribute to the volatility in their inventory levels. Achieving profit under such capricious inventory levels and stringent environmental legislations remains a challenge to many PRFs. This paper presents a multi-criteria decision model to determine a pricing policy that can simultaneously address two issues: stabilize inventory fluctuations and boost profits. The model considers that PRFs passively accepts discarded products as well as acquires them proactively if necessary. Under a multi-criteria setting, the current work determines prices of reusable and recyclable components to maximize revenue and minimize product recovery costs. A genetic algorithm is employed to solve the multi-criteria decision making problem. Sensitivity analysis is performed to investigate the effect of sorting yield, disassembly yield, and reusable component yield on the profits, prices, inventory levels, and disposal quantities.     

梯度相关的无线传感器网络成簇路由协议

分析了梯度和成簇无线传感器网络路由协议,确定了协议中存在的缺陷,设计了一种基于梯度的高效节能成簇路由协议(GBCRP)。采用基于跳数的梯度建立、能量相关的成簇算法、关键节点转发和功率自适应的簇头路由等技术,解决了无线传感器网络的节点能耗和路由失败而导致的数据传输可靠性问题。仿真实验表明,该协议有效地延长了网络的生命周期。针对不同密度的传感器节点,网络生命周期具有很好的稳定性,同时该协议也具有较好的可靠性保障。     

论产业集群中政府作用的界定

政府在产业集群中有着重要的地位和作用,对政府作用的精确界定,有利于充分发挥产业集群的优势。政府在产业集群中的作用体现在:提供公共政策与公共产品;制定目标与监管市场;扮演中介和提供公共服务;搭建平台与搞好配套环境建设。     

Influence of Argentine and coastal brown ant (Hymenoptera: Formicidae) invasions on ant communities in Perth gardens,Western Australia

A survey examined the influence of Argentine (Linepithema humile (Mayr)) and coastal brown ant (Pheidole megacephala (Fabricius)) populations on other ants in the Perth metropolitan area, Western Australia. Twelve gardens (yards) were sampled; four infested by Argentine ants, three infested by coastal brown ants, and five controls where these two tramp ants were absent or collected only as isolated strays. Collection methods used were pitfall trapping and hand collection. A total of 27 species was recorded. Eight of these species, including the above two tramp ants, are non-native to the region. Pheidole megacephala was the most abundant species, comprising 95.4% of ants in P. megacephala–infested gardens. Linepithema humile comprised 92.1% of ants in L. humile–infested gardens. Other common ants were the native Iridomyrmex chasei and the introduced species Tetramorium simillimum and Tetramorium bicarinatum. The cryptic introduced species Cardiocondyla nuda and Tetramorium simillimum appear able to persist in small numbers in L. humile–infested gardens, but virtually no other ant species occurred where the coastal brown ant was well established. Mean richness, diversity, and evenness were significantly different between P. megacephala–infested and control gardens, and significantly different between L. humile–infested and control gardens. Diversity and evenness, but not richness, were significantly different between P. megacephala–infested and L. humile–infested gardens. Ordination analysis revealed that the three types of gardens had very different ant community profiles.     

实时调度算法研究

对实时调度进行了讨论：研究了单处理器下的经典调度算法：单调速率调度、最早死线调度和最短空闲时间优先调度;分析了多处理器系统中的典型调度算法：对分布式系统中的两种调度算法：广义单调速率调度和分布式风车调度做了简要论述;指出实时调度研究策略方向。     

学生非正式群体对其心理健康的影响及对策

学生非正式群体对学生心理健康的影响具有双重性。学校教育者、家长和全社会都应该在正确认识学生非正式群体的基础上 ,根据其形成的原因、类型进行有针对性的教育和引导 ,发挥其积极作用 ,限制或消除其消极作用 ,以促进学生的心理健康发展     

决策支持系统的自适应建模研究及应用实例分析

在进行决策的过程中 ,建立正确的系统模型是解决问题的关键 .由于多方面的原因 ,有时要针对研究对象选用适用的模型来进行分析是很困难的 .本文根据遗传算法在程序设计中的应用 ,探讨了基于遗传算法的自适应建模方法 ,并对实际应用中自适应建模的算法存在的问题提出了改进方法 .最后应用自适应建模方法对全国的集装箱与外贸数据进行了建模分析 ,应用实例表明自适应建模方法对于解决难以选择合适的模型进行建模分析时是很有效的     

Approximation Algorithms for the Multiple Knapsack Problem with Assignment Restrictions

Motivated by a real world application, we study the multiple knapsack problem with assignment restrictions (MKAR). We are given a set of items, each with a positive real weight, and a set of knapsacks, each with a positive real capacity. In addition, for each item a set of knapsacks that can hold that item is specified. In a feasible assignment of items to knapsacks, each item is assigned to at most one knapsack, assignment restrictions are satisfied, and knapsack capacities are not exceeded. We consider the objectives of maximizing assigned weight and minimizing utilized capacity.We focus on obtaining approximate solutions in polynomial computational time. We show that simple greedy approaches yield 1/3-approximation algorithms for the objective of maximizing assigned weight. We give two different 1/2-approximation algorithms: the first one solves single knapsack problems successively and the second one is based on rounding the LP relaxation solution. For the bicriteria problem of minimizing utilized capacity subject to a minimum requirement on assigned weight, we give an (1/3,2)-approximation algorithm.     

Quantifying the similarity of 2D images using edge pixels: an application to the forensic comparison of footwear impressions

We propose a novel method to quantify the similarity between an impression (Q) from an unknown source and a test impression (K) from a known source. Using the property of geometrical congruence in the impressions, the degree of correspondence is quantified using ideas from graph theory and maximum clique (MC). The algorithm uses the x and y coordinates of the edges in the images as the data. We focus on local areas in Q and the corresponding regions in K and extract features for comparison. Using pairs of images with known origin, we train a random forest to classify pairs into mates and non-mates. We collected impressions from 60 pairs of shoes of the same brand and model, worn over six months. Using a different set of very similar shoes, we evaluated the performance of the algorithm in terms of the accuracy with which it correctly classified images into source classes. Using classification error rates and ROC curves, we compare the proposed method to other algorithms in the literature and show that for these data, our method shows good classification performance relative to other methods. The algorithm can be implemented with the R package shoeprintr.