802.16e系统周期测距的软件设计和实现

测距作为WiMAX上行链路调整时间偏置、功率信息和载波频率的一种方法,在系统接入和通信过程中起着重要作用。深入研究了基于ARM处理器的802.16e系统正交频分多址(orthogonal frequency division multiple ac-cess,OFDMA)物理层的周期测距的软件设计与实现,给出了802.16e系统OFDMA物理层的周期测距算法和流程、周期测距码的发射和检测原理以及周期测距模块的C语言设计。在搭建的测试平台上进行链路测试,结果表明此方案是可行的。     

连铸坯质量判定模糊专家系统

鉴于连铸过程中存在众多不确定性,考虑某中厚板厂的实际生产状况与中厚板热送热装的控制要求,以表面纵裂为例,按照模糊专家系统的开发思路,建立起连铸坯纵裂知识库,开发推理机制.采用纵裂指数预测和神经网络预测相结合的方法对连铸坯质量进行离线判断、推理和决策,并给出相应的缺陷产生原因解释.采用VC++6.0软件建立人机界面,数据库采用Oracle,调试结果表明该系统可以达到较高的判定准确率(92.8%),为在线应用奠定了基础.     

Latent Co-interests' Relationship Prediction

With the development of the social media and Internet, discovering latent information from massive information is becoming particularly relevant to improving user experience. Research efforts based on preferences and relationships between users have attracted more and more attention. Predictive problems, such as inferring friend relationship and co-author relationship between users have been explored. However, many such methods are based on analyzing either node features or the network structures separately, few have tried to tackle both of them at the same time. In this paper, in order to discover latent co-interests’ relationship, we not only consider users’ attributes but network information as well. In addition, we propose an Interest-based Factor Graph Model (I-FGM) to incorporate these factors. Experiments on two data sets (bookmarking and music network) demonstrate that this predictive method can achieve better results than the other three methods (ANN, NB, and SVM).     

适用于校园网直播的p2p系统策略分析

目前校园网具有带宽高、IP分配有规律、网络结构相对稳定单一、用户集中、内部资源分享率高等特点，同时高校对网络资源的控制较为严格，因此开发适合此环境的p2p软件具有和目前互联网流行的p2p软件不同的方向和方法。节点策略是p2p软件的核心，该文将分析和探讨适合高校校园网直播环境的简单有效的p2p系统策略。     

充分利用网络资源 补充实体馆藏不足

介绍了网上信息资源的特点,从馆藏资源不足、信息需求量大、知识更新快以及阅读习惯和阅读方式的改变等方面谈了开发网上信息资源的必要性和可能性,阐述了开发网上资源应遵循的原则,提出了图书馆开发提供网上信息资源的具体方法.     

基于6LoWPAN６的PRL路由协议研究

鲁迅对日本文化和日本国民性的关注更多的是从中国国民性批判的角度来进行的,他的日本认识包含两个层面:一是作为国民性改造过程中的一个参照物的日本,他过多地强调日本民族的优点而少谈日本民族的缺点,就在于他是以日本民族的优点作为救治本民族缺点的"药",日本民族的优点的选择是出于本民族现实需要的目的;二是作为独立民族文化的日本,他摆脱了中日冲突背景下的激进和狭隘的民族主义,以冷静的态度进行中日文化的交流,以期促成民族间的理解和友好。     

基于神经网络技术自动筛选Monastrol抑制剂的算法研究

带自动荧光显微镜的HCS（high content screening）系统是一种新兴的显微摄影、筛选和处理系统.HCS系统在摄影过程中会产生大量数据,人工筛选和识别费时费力.本文为了进行Monastrol抑制剂的筛选,基于前馈式神经网络技术研究了一种对HCS系统摄影的大量细胞同时进行特征提取和细胞显型识别的自动算法.在得到各个通道分离的图像后,对不同通道图像进行并行预处理,并采用神经网络和逻辑运算相结合的算法进行处理.我们将该方法运用于Monastrol抑制剂的筛选中,并将结果与人工识别结果进行分析比较.相比较前人提出的multi-phenotypic mitotic analysis（MMA）算法自动识别的正确率得以提高,可更好评估抗癌药剂效用.     

基于神经网络数据融合的目标跟踪简化算法

分析了基于神经网络数据融合的目标跟踪算法 ,指出了传统的融合算法计算量大 ,神经网络目标向量不易选取等缺点 ,并提出了一种简化的算法。应用理论分析和蒙特卡洛仿真方法 ,对标准卡尔曼滤波算法和简化的滤波算法进行了比较 ,并给出了均方根误差的统计值。该简化算法原理简单 ,数据处理量小 ,速度快 ,误差小 ,特别适用于多传感器的处理 ,将融合结果反馈给单传感器 ,可提高各单传感器的跟踪精度     

AJAX技术在网络考试系统中的应用

在充分分析网络考试系统的现状、发展前景的基础上,剖析了目前网络考试系统存在客户端相应速度慢、数据处理不灵活等问题,重点论述了在校园网环境下采用AJAX技术提高系统性能的优势及具体的解决策略,取得了良好的效果.     

Network Motif Detection： Algorithms, Parallel and Cloud Computing,and Related Tools

Network motif is defined as a frequent and unique subgraph pattern in a network, and the search involves counting all the possible instances or listing all patterns, testing isomorphism known as NP-hard and large amounts of repeated processes for statistical evaluation. Although many efficient algorithms have been introduced, exhaustive search methods are still infeasible and feasible approximation methods are yet implausible.Additionally, the fast and continual growth of biological networks makes the problem more challenging. As a consequence, parallel algorithms have been developed and distributed computing has been tested in the cloud computing environment as well. In this paper, we survey current algorithms for network motif detection and existing software tools. Then, we show that some methods have been utilized for parallel network motif search algorithms with static or dynamic load balancing techniques. With the advent of cloud computing services, network motif search has been implemented with MapReduce in Hadoop Distributed File System(HDFS), and with Storm, but without statistical testing. In this paper, we survey network motif search algorithms in general, including existing parallel methods as well as cloud computing based search, and show the promising potentials for the cloud computing based motif search methods.