This paper presents a procedure for designing a supplementary damping stabilizer for a static synchronous series compensator (SSSC) in multi-machine power systems. The objective is to shift the lightly damped inter-area modes toward the prescribed stability region. A lead-lag stabilizer is used to demonstrate this technique, in which a particular measure of stabilizer gain is considered as an objective function. Constraints of the problem for phase-lead and lag structures are derived. The objective function with the constraints is formed as a quadratic mathematical programming problem. For robust design, the parameters of the stabilizer are calculated under various operating conditions. Two types of SSSC-based stabilizer have been presented and designed. Numerical results including eigenvalue analysis and the nonlinear simulations on the 4- and 50-machine power systems are presented to show the effectiveness of the proposed method.

研究目的：对图像缩放方法进行全面总结，为今后图像缩放研究提供新视角。
\n文章内容：通过对重要区域保持、最小化变形和性能方面的分析，总结各种图像缩放方法的优缺点。首先，分析了图像显著性检测方法。其次，将图像缩放方法分为缩放、裁剪、缝裁剪、变形、多算子和其他方法，总结了近年提出的一些视频缩放方法。最后，总结图像缩放方法，指出未来研究热点包括：基于视频显著性的视频缩放技术的深入研究，具有更多语义信息、复杂结构和不同拓扑关系的图像缩放方法的研究，对特殊场景图像的缩放，如何更加高效地进行图像缩放，等。

Since Service-Oriented Architecture (SOA) reveals the black box nature of services, heterogeneity, service dynamism, and service evolvability, managing services is known to be a challenging problem. Autonomic computing (AC) is a way of designing systems that can manage themselves without direct human intervention. Hence, applying the key disciplines of AC to service management is appealing. A key task of service management is to identify probable causes for symptoms detected and to devise actuation methods that can remedy the causes. In SOA, there are a number of target elements for service remedies, and there can be a number of causes associated with each target element. However, there is not yet a comprehensive taxonomy of causes that is widely accepted. The lack of cause taxonomy results in the limited possibility of remedying the problems in an autonomic way. In this paper, we first present a meta-model, extract all target elements for service fault management, and present a computing model for autonomously managing service faults. Then we define fault taxonomy for each target element and inter-relationships among the elements. Finally, we show prototype implementation using cause taxonomy and conduct experiments with the prototype for validating its applicability and effectiveness.

Proportional integrator (PI) is always adopted in the resonant frequency servo loop in a resonator micro optic gyro (RMOG). The oscillation phenomenon is observed when adjusting the loop gain surpassing a threshold. This phenomenon limits system performance on step response speed and residual error. Based on the experiment system, a simulation model was set up. Further analysis shows that the threshold gain is related to the system loop filter setting and the loop delay. The traditional PI frequency servo loop technique in the RMOG system cannot keep up with the environment’s disturbance quickly enough, which leads to a large residual error. A compensating method is proposed to optimize the tracking performance, solve the oscillation problem, and speed up the system response. Simulation and experiment results show that the compensated system is superior in performance. It has less residual error in the stable state and is 10 times quicker than the uncompensated system on the step response.

研究目的：针对海水和高压环境，设计了一种稳定、高效的感应式电能传输装置，并在原型系统的基础上，对不同参数下系统的传输能力和效率进行分析，评估系统的电路损耗、线圈损耗和涡流损耗，探讨功率增大时系统效率的变化趋势和提高系统性能的方法。
创新方法：设计适用于AUV接驳系统的耦合线圈，并详细分析各设计参数对系统性能的影响。然后从损耗的角度对系统效率进行评估和预测，通过分析损耗的来源和特点，提出提高系统效率的方法。
研究手段：建立系统简化模型后，采用MATLAB编程进行数值运算，避免了繁琐的化简过程（且实际化简结果也十分复杂，难以找到规律）。用MATLAB编程运算的另一大优点是可以有效的对各设计参数进行分析，得到直观的图形结果。通过分析损耗来评估系统效率，对系统的损耗来源做全面的分析对比，有利于找到提升系统效率的方法。采用瞬态电路仿真对电路中的半导体元件和线圈的损耗进行分析，并且，采用ANSYS瞬态电磁场仿真对系统的涡流损耗进行分析。通过仿真和试验结果的对比验证了仿真手段的有效性。仿真方法也可以为新系统的参数设计提供参考。
重要结论：1. 采用次级串联谐振方式，线圈间的耦合系数对系统输出功率有影响，但对系统的效率影响很小。2. 可以通过降低频率或者采用更合适的线缆减小线圈损耗；电路损耗主要来自开关管和二极管的半导体损耗，通过选择更合适的元器件或者采用软开关降低半导体损耗；当腔体直径远小于线圈直径时，腔体中的涡流损耗很小，且海水中的涡流损耗相较于其他损耗也比较小。3. 通过调整线圈的电感和增大输入电压可以提高系统输出功率。并且通过增大电压的方式在系统功率升高的同时，系统效率也随之提高。

研究目的：通过调查不同反锯齿技术的实现方法和优缺点，为研究人员提供一种快速理解反锯齿技术的方法，并指出该领域未来研究方向。
\n文章内容：将图像反锯齿技术分为后滤波和预滤波两大类，并将后滤波技术细分为硬件反锯齿技术和后处理反锯齿技术（图1）。针对每一类技术，分析了主流反锯齿技术的实现原理和主要优缺点。在讨论每一类技术的最后，将这些技术作了归纳和比较，并阐述其应用。对后滤波技术，首先讨论了基于GPU管线的SSAA、MSAA及其不同的改进技术，接着分析了为适应延迟渲染技术而出现的独立于GPU管线的各种后处理滤波技术（以形态反锯齿技术为代表），最后从不同方面比较了主流后滤波技术间的差异（表1）。对于预滤波技术，主要依据时间发展脉络讨论了不同的解析反锯齿技术。最后，从反锯齿质量、性能、输入限制、带宽需求等方面对这两大类技术作了比较（表2)，指出了未来研究方向。

An IEEE 1588 based application scheme was proposed to achieve accurate time synchronization for a deep seafloor observatory network based on the communication topological structure of the Zhejiang University Experimental and Research Observatory. The principles of the network time protocol (NTP) and precision time protocol (PTP) were analyzed. The framework for time synchronization of the shore station, undersea junction box layer, and submarine science instrument layer was designed. NTP and PTP network signals were decoded by a PTP master clock on a shore station that receives signals from the Global Positioning System and the BeiDou Navigation Satellite System as reference time sources. These signals were remotely transmitted by a subsea optical–electrical composite cable through an Ethernet passive optical network. Accurate time was determined by time synchronization devices in each layer. Synchronization monitoring experiments performed within a laboratory environment indicated that the proposed system is valid and has the potential to realize microsecond accuracy to satisfy the time synchronization requirements of a high-precision seafloor observatory network.

近年来，互联网使得人们可以在分布式计算环境中获取广泛的远程服务。然而，一系列安全问题影响着分布式计算平台数据传输完整性。例如，\"僵尸网络\"（包含恶意代码）就是互联网安全的一种显著威胁。多种犯罪活动依附于僵尸网络，包括分布式拒绝服务（DDoS）攻击、点击欺诈、网络钓鱼、恶意软件分发、垃圾邮件、建立用于非法信息交换的机器，等等。因此，有必要设计并构建一种稳健的机制以提升僵尸网络的探测、分析和移除过程。目前，已有较多工作从不同角度针对僵尸网络的探测技术进行综述，但是，这些工作视角有限，缺乏对最新技术的探讨。本文全面评述僵尸网络最新探测技术，指出该技术的发展趋势；对僵尸网络探测技术作了分类，并通过定性分析凸显了这些技术的潜在影响和关键方面。基于此全面综述，指出涵盖整个僵尸网络探测领域多个方案的改进方向，并指明此领域长期存在的显著挑战。

目的：针对复杂多模态工业过程故障监测存在的问题，充分利用过程数据的局部和非局部几何信息，同时实现数据聚类和低维子空间选择，提高非线性、非高斯多模态过程监测性能。
创新点：提出融合局部鉴别正则化软k-均值与贝叶斯推理的多模态过程监测算法。该方法充分利用过程数据的局部和非局部几何信息，较好地发挥了无监督学习和有监督学习的优点，提高了模态数据的分离性和解释性，监测性能良好。
方法：该方法分为二个阶段：第一阶段，首先，考虑过程数据的局部和非局部几何信息，提出一种局部保持的正则化软k-均值聚类算法（LPRSKM）。然后，建立有监督学习与无监督学习的统一框架，提出融合LPRSKM与广义线性鉴别分析算法(GELDA)的局部鉴别正则化软k-均值算法(LDRSKM)(图1)。第二阶段，使用核支持向量数据描述(KSVDD)对各局部子空间建立监测统计量及控制限。然后，基于贝叶斯推理方法建立多模态过程全局监测统计量。最后，在TE仿真平台对所提方法进行仿真分析。
结论：针对非线性、非高斯的多模态过程监测，提出一种新的数据划分和最优低维子空间选择的迭代算法来提高不同模态数据的分离效果。在此基础上使用KSVDD和贝叶斯推理方法，较好地解决了多个非高斯和非线性的过程模态的监测准确性和可靠性问题。

The faults in switched reluctance motors (SRMs) were detected and diagnosed in real time with the Kohonen neural network. When a fault happens, both financial losses and undesired situations may occur. For these reasons, it is important to detect the incipient faults of SRMs and to diagnose which faults have occurred. In this study, a test rig was realized to determine the healthy and faulty conditions of SRMs. A data set for the Kohonen neural network was created with implemented measurements. A graphical user interface (GUI) was created in Matlab to test the performance of the Kohonen artificial neural network in real time. The data of the SRM was transferred to this software with a data acquisition card. The condition of the motor was monitored by marking the data measured in real time on the weight position graph of the Kohonen neural network. This test rig is capable of real-time monitoring of the condition of SRMs, which are used with intermittent or continuous operation, and is capable of detecting and diagnosing the faults that may occur in the motor. The Kohonen neural network used for detection and diagnosis of faults of the SRM in real time with Matlab GUI was embedded in an STM32 processor. A prototype with the STM32 processor was developed to detect and diagnose the faults of SRMs independent of computers.

研究目的：随着异构网络的快速发展和部署，移动用户期望得到无处不在的网络接入服务。对于带宽需求较高的应用，如互联网协议电视（IPTV），多媒体内容分发等服务通常采用具有较高带宽利用率的组播数据传输方法。然而，在异构网络环境中，并非所有网络都支持多播技术。因此，当用户从多播网络移至单播网络时，服务可能中断。此种情形下，保证实时多媒体应用顺畅传输，具有重要意义。
\n创新要点：有别于以往的分析和模拟研究，本文建立了一个实时流媒体测试平台，提出了一个标准流式传输方法。本文的设计考虑了实际限制，特别是，音频和视频缓冲器的行为均可能影响用户体验。
\n方法提亮：对于客户端的操作，本文设计了触发器代理和流媒体代理。触发器代理负责发起一个连接切换。因此，该切换方案属于移动端控制切换。根据可选择的连接类型（单播或多播），触发器代理将传送当前多媒体流的统一资源定位器（URL）或发出组播加入请求信息。流媒体代理从该服务器接收流媒体内容。如果是多媒体新流，它将传入的数据区分为音频和视频数据，分别转发到A/V解码器。对于服务器的操作，本文设计了请求处理器和多媒体流切换代理。请求处理器侦听传入的客户端请求，主要负责提取客户的IP地址，并与多媒体流的URL一起转发至多媒体流切换代理。多媒体流切换代理使用多媒体流的URL查找当前被传递至发出请求的用户的资源，同时获取该多媒体流的当前播放时间。随后，多媒体流切换代理将通知数据流接口，并以交替的方法将多媒体流传送给客户端。
\n重要结论：实验结果表明，在网络的重叠区域内，多播网络—单播网络和单播网络—多播网络的切换时间分别为56毫秒和4毫秒。依据ITU-T建议书，利用本文方法得到的视频画质被归为\"好\"。平均意见得分（mean opinion score, MOS）证实了视频播放流畅度。

研究目的：在三维数字化工程和数字几何处理领域，在获取高度复杂模型的大规模采样数据过程中，由于利用三维扫描设备获取的均匀采样点数据不依赖于模型内在特征，大量采样点数据通常具有许多冗余信息，使得三维模型的远程传输、隐式曲面的快速重建、数字娱乐和虚拟现实实时显示等应用中，需要庞大内存和大量时间处理大规模采样数据。基于视觉显著特性的特征敏感形状简化技术,可在保持复杂模型显著特征的前提下减少模型数据量，从而满足特定应用的需求。
\n创新要点：提出一种视觉显著性引导的特征敏感形状简化方法。将三维复杂模型的内容敏感显著性度量引入模型顶点对的迭代收缩简化。顶点对的收缩误差由显著性加权的二次误差度量来衡量。与传统模型简化方法不同，该误差度量定义在结合模型顶点位置信息和法向量信息的6维空间上。
\n重要结论：实验结果表明，得到的重采样结果能够很好地反映模型的视觉显著特征，在模型的高显著区域采样点较稠密，在低显著区域采样点较稀疏。

目的：重采样方法是粒子滤波设计的重要环节，也是避免或克服“权值退化”和“多样性匮乏”这一对粒子滤波难点问题的关键。当前研究领域已有几十余种重采样方法，然而尚缺乏一个基础性的重采样设计原则以及对这些方法的综合性能对比。针对于此，本文提出重采样“同分布”设计原则，并在此基础上，提出一种能够最大程度满足同分布原则的最优重采样方法。本文希望所提出的重采样同分布原则以及新方法有利于进一步的新方法设计或已有方法的工程选用。
创新点：理论上严格定义了同分布原则作为重采样方法设计的普遍性原则，给出三种同分布测度方法；提出了一种最小采样方差（MSV: minimum sampling variance）最优重采样方法，在满足渐近无偏性的前提下获得最小采样方差。
方法：给出三种“重采样同分布”测度方法：Kullback-Leibler偏差,Kolmogorov-Smirnov统计和采样方差（sampling variance）。所提出的最小采样方差重采样放宽了无偏性条件，仅满足渐近无偏，但获得了最小采样方差（参见定理2-4论证以及仿真性能对比）。
结论：重采样前后粒子的概率分布应该统计上一致（即“同分布”）是重采样方法设计的一个重要原则。明确这一基本原则有利于规范化重采样新方法的设计与工程选用。所提出的MSV重采样新方法渐近无偏，并具有最小采样方差的优异理论特性，即最优地满足同分布原则。算法性能分析表明：大多数无偏或者渐近无偏重采样方法在滤波精度上差异较小，但是在采样方差、计算效率方面差异较大。另一方面，基于一些特殊规则或者问题模型设计的重采样方法可能具有特别优势。

目的：随着四元数在信号处理各个领域越来越广泛的应用，基于四元数的信号处理理论也获得了快速发展。然而，制约其进一步应用的一个瓶颈就是对一般四元数函数的梯度的定义及特性还缺乏清晰并有说服力的描述。本文就试图对这一问题进行探索。
创新点：在信号处理中，虽然很多优化函数的值都是实数，但在进行优化时，尤其是在非线性信号处理中，经常会遇到对取值为四元数的四元数函数求梯度。不同于以往只适用于实数值四元数函数梯度的定义，本文第一次就一般四元数函数的梯度给出了一个自洽的定义，并对其特性进行了详细的研究和描述。基于以上研究，本文对四元数值的最小均方(LMS)自适应算法，以及一个有代表性的非线性自适应算法进行了推导，并以矢量传感器阵列波束形成为例进行了计算机模拟。

Congestion in wireless sensor networks (WSNs) not only causes severe information loss but also leads to excessive energy consumption. To address this problem, a novel scheme for congestion avoidance, detection and alleviation (CADA) in WSNs is proposed in this paper. By exploiting data characteristics, a small number of representative nodes are chosen from those in the event area as data sources, so that the source traffic can be suppressed proactively to avoid potential congestion. Once congestion occurs inevitably due to traffic mergence, it will be detected in a timely way by the hotspot node based on a combination of buffer occupancy and channel utilization. Congestion is then alleviated reactively by either dynamic traffic multiplexing or source rate regulation in accordance with the specific hotspot scenarios. Extensive simulation results under typical congestion scenarios are presented to illuminate the distinguished performance of the proposed scheme.

It is universally acknowledged by network security experts that proactive peer-to-peer (P2P) worms may soon engender serious threats to the Internet infrastructures. These latent threats stimulate activities of modeling and analysis of the proactive P2P worm propagation. Based on the classical two-factor model, in this paper, we propose a novel proactive worm propagation model in unstructured P2P networks (called the four-factor model) by considering four factors: (1) network topology, (2) countermeasures taken by Internet service providers (ISPs) and users, (3) configuration diversity of nodes in the P2P network, and (4) attack and defense strategies. Simulations and experiments show that proactive P2P worms can be slowed down by two ways: improvement of the configuration diversity of the P2P network and using powerful rules to reinforce the most connected nodes from being compromised. The four-factor model provides a better description and prediction of the proactive P2P worm propagation.

创新方法：传统的模糊c均值方法（FCM）有两个缺点：对初始值要求严格，无法处理非线性分割数据。通过使用基于核的模糊c均值聚类法（KFCM-F）作为本地搜索方法，采用渐进方法获得近乎最优的结果，这种方法的渐进性和KFCM-F的非线性，可以避免FCM的两个缺点。
研究手段：使用KFCM-F处理数据，在不显著影响实验结果的情况下，设计了一个加速计划以降低计算复杂度。采用非线性人工数据组和现实数据组作为语音信号，进行辅音/元音分割，以检测这种新算法的性能。
重要结论：KFCM-F方法巧妙地避免了传统FCM方法的两个缺点。我们设计的算法（FGKFCM-F）继承了KFCM-F和全局模糊c均值方法（GFCM）的优点，得以实现基于非线性分割数据组的近乎最优解。此外，我们设计的加速计划大大降低了整个计算的复杂度。实验结果证实，FGKFCM-F比其他方法更适合处理人工和现实数据。

概要：全世界对电能的需求显著增长，但电能生产和传输能力却未相应提升。这导致电能消费者受多种问题困扰（如：电压和频率不稳定及电能质量问题）。为解决上述问题，需提升电力传输网的可用功率传输能力。世界各地的研究者采用柔性交流传输系统（FACTS）装置来提升这一能力。本文全面总结了FACTS控制器如何用于提升电力系统网的可用传输能力（ATC）和功率传输能力（PTC）；针对不同因素，讨论不同FACTS设备的分类；结合相关统计结果，讨论FACTS设备的普及性和应用情况。此外，本文还包含六种主要FACTS装置的操作原理及其在提升ATC和PTC方面的应用。最后针对不同的控制算法，评估FACTS装置在提升ATC和PTC方面的性能。

We develop a numerical solution algorithm of the nonlinear potential flow equations with the nonlinear free surface boundary condition. A finite difference method with a predictor-corrector method is applied to solve the nonlinear potential flow equations in a two-dimensional (2D) tank. The irregular tank is mapped onto a fixed square domain with rectangular cells through a proper mapping function. A staggered mesh system is adopted in a 2D tank to capture the wave elevation of the transient fluid. The finite difference method with a predictor-corrector scheme is applied to discretize the nonlinear dynamic boundary condition and nonlinear kinematic boundary condition. We present the numerical results of wave elevations from small to large amplitude waves with free oscillation motion, and the numerical solutions of wave elevation with horizontal excited motion. The beating period and the nonlinear phenomenon are very clear. The numerical solutions agree well with the analytical solutions and previously published results.

目的：随着电子商务的发展，商品交易形式发生了翻天覆地的变化。在这种新型虚拟交易平台上，消费者快速而又广泛地浏览、购买、评价各种价廉物美的商品，而商品也同样地进行着产品创新、营销拓展、物流改善。所以，消费者和商品之间早已不是简单的一对一直接买卖关系，而是消费者和消费者之间的社交网络，消费者和商品之间的交易网络构成电子商务中最重要的物质载体。于是，对于商品销量预测这一传统经济问题，在电子商务的大环境下有了新型的研究意义。为了能有效和深入地研究在电子商务环境下的商品销量发展模式，本文的目的在于提供一种应用于电子商务的商品销量预测算法，该算法注重于从消费者社会影响力分析入手，更好地适应真实电子商务环境中的销量预测需求。
创新点：首先，本文算法不仅考虑到消费者自身的特征，同时还考虑到存在于消费者之间的社会影响力，考虑到在真实的电子商务中，消费者之间传递商品的价格信息或评价信息十分便捷，因而本文算法很好地切合了实际的应用环境。其次，本文算法定义了交易环境中的两种社会影响力，即“同一商品中消费者互相作用产生的影响力”和“不同商品之间消费者互相作用产生的影响力”，分别考虑到单一商品的交易环境和多个商品互相作用的交易环境中消费者行为，其中以上两种社会影响力都是由真实消费者社交网络分析提炼得来的，使得本算法更加切合真实交易网络的内在结构。
方法：本文算法将商品销量分为主体部分和噪声部分，很好地模拟了真实交易环境中，商品销量的构成是受多成分影响的。并且在预测模型中，对主体部分和噪声部分分别设置了不同的约束条件，具体为要求商品销量的主体部分在时间上应该保持平滑性，并要求商品销量的噪声部分是稀疏的，以上两个约束很好地反映了真实交易环境中商品销量的变化形式。
结论：本文研究电子商务环境下商品销量的发展模式，并提出描述消费者之间关系的两种社会影响力网络。将此社会影响力网络整合入商品销量构成模型中，最后提出对这些商品销量的预测算法。特别是通过在真实的数据环境中（阿里巴巴女装数据）进行算法测试，并结合与传统销量预测算法的比较，展示在复杂数据环境下本算法的有效性。

目的：在IPv6过渡方案中，研究同时具有良好可扩展性、灵活性和IPv4地址共享效率的IPv4地址共享机制，以促进IPv6的过渡进程。
创新点：在已有IPv6过渡机制基础上，提出一种混合的数据通路动态切换机制，可以兼顾已有的无状态机制和有状态机制的优点，从而实现良好的可扩展性、灵活性、安全性和高效的IPv4地址共享。该机制尤其适用于IPv4地址匮乏但用户数量很多的网络，可以在保证用户体验的同时充分促进该网络向IPv6的过渡。在此机制基础上，提出根据实际情况进行灵活的地址规划的方法。
方法：首先，针对当前的IPv4地址共享机制的不足，提出并设计混合的数据通路动态切换机制，其中动态切换的过程由用户侧网关完成。然后，设计该机制的组成模块，并分别讨论其实现算法和细节。接下来，将整个系统实现并部署在连接至IPv6骨干网CERNET2的清华大学校园网中，通过实际流量数据分析该机制对有状态通路和无状态通路上流量和端口消耗的影响，验证该机制的可行性和有效性。最后，在此机制基础上，提出根据实际情况进行灵活的地址规划的方法。
结论：本文所提方法可以有效地使用有限的IPv4地址而不降低终端性能。实验结果（图6-8）验证了所提方法的有效性。该方法尤其适用于具有大量用户且希望使用有限IPv4地址的网络。

Single-channel separation (SCS) is a challenging scenario where the objective is to segregate speaker signals from their mixture with high accuracy. In this research a novel framework called subband perceptually weighted transformation (SPWT) is developed to offer a perceptually relevant feature to replace the commonly used magnitude of the short-time Fourier transform (STFT). The main objectives of the proposed SPWT are to lower the spectral distortion (SD) and to improve the ideal separation quality. The performance of the SPWT is compared to those obtained using mixmax and Wiener filter methods. A comprehensive statistical analysis is conducted to compare the SPWT quantization performance as well as the ideal separation quality with other features of log-spectrum and magnitude spectrum. Our evaluations show that the SPWT provides lower SD values and a more compact distribution of SD, leading to more acceptable subjective separation quality as evaluated using the mean opinion score.

研究目的：数据中心网络由大量服务器主机与数据交换设备经高速网络互连，是数据中心的重要组成部分。数据中心能够通过建立集中化的数据资源向终端用户按需提供信息与服务。近年来，基于云计算的服务大量增加，由此产生的数据中心内（间）大规模数据流量，使得数据中心网络规模不断扩大，而传统的数据中心网络结构随着云服务的用户增加，在带宽汇聚、扩展性、性价比等方面的表现不尽如人意。因此，迫切需要一个具备良好可扩展性、高性价比、高稳定性以及低能耗的新型数据中心网络结构。
\n文章内容：回顾了近年来数据中心网络结构的研究发现和相关技术，指出现有云计算数据中心网络结构的特点。将现有多种数据中心网络结构按照树形(Clos/tree-based)，负载均衡（valiant load balancing），递归（hierarchically recursive），光/无线（optical/wireless），以及随机连接（randomly connected）五个方面进行分类，详细介绍各个类别下的代表结构，并对这些网络结构进行横向比较，选取的指标包括带宽、容错、可扩展性、开销以及网络搭建大致费用。最后，从可扩展性、成本、稳定性、能效等方面，对未来面向云计算的数据中心网络结构的研究热点进行展望。

The widespread availability of portable computing power and inexpensive digital cameras are opening up new possibilities for retailers in some markets. One example is in optical shops, where a number of systems exist that facilitate eyeglasses selection. These systems are now more necessary as the market is saturated with an increasingly complex array of lenses, frames, coatings, tints, photochromic and polarizing treatments, etc. Research challenges encompass Computer Vision, Multimedia and Human-Computer Interaction. Cost factors are also of importance for widespread product acceptance. This paper describes a low-cost system that allows the user to visualize different glasses models in live video. The user can also move the glasses to adjust its position on the face. The system, which runs at 9.5 frames/s on general-purpose hardware, has a homeostatic module that keeps image parameters controlled. This is achieved by using a camera with motorized zoom, iris, white balance, etc. This feature can be specially useful in environments with changing illumination and shadows, like in an optical shop. The system also includes a face and eye detection module and a glasses management module.

We present an algorithm for image compression based on an image inpainting method. First the image regions that can be accurately recovered are located. Then, to reduce the data, information of such regions is removed. The remaining data besides essential details for recovering the removed regions are encoded to produce output data. At the decoder, an inpainting method is applied to retrieve removed regions using information extracted at the encoder. The image inpainting technique utilizes partial differential equations (PDEs) for recovering information. It is designed to achieve high performance in terms of image compression criteria. This algorithm was examined for various images. A high compression ratio of 1:40 was achieved at an acceptable quality. Experimental results showed attainable visible quality improvement at a high compression ratio compared with JPEG.

Automatic pectoral muscle removal on medio-lateral oblique (MLO) view of mammogram is an essential step for many mammographic processing algorithms. However, it is still a very difficult task since the sizes, the shapes and the intensity contrasts of pectoral muscles change greatly from one MLO view to another. In this paper, we propose a novel method based on a discrete time Markov chain (DTMC) and an active contour model to automatically detect the pectoral muscle boundary. DTMC is used to model two important characteristics of the pectoral muscle edge, i.e., continuity and uncertainty. After obtaining a rough boundary, an active contour model is applied to refine the detection results. The experimental results on images from the Digital Database for Screening Mammography (DDSM) showed that our method can overcome many limitations of existing algorithms. The false positive (FP) and false negative (FN) pixel percentages are less than 5% in 77.5% mammograms. The detection precision of 91% meets the clinical requirement.

Any node in a wireless sensor network is a resource constrained device in terms of memory, bandwidth, and energy, which leads to a large number of packet drops, low throughput, and significant waste of energy due to retransmission. This paper presents a new approach for predicting congestion using a probabilistic method and controlling congestion using new rate control methods. The probabilistic approach used for prediction of the occurrence of congestion in a node is developed using data traffic and buffer occupancy. The rate control method uses a back-off selection scheme and also rate allocation schemes, namely rate regulation (RRG) and split protocol (SP), to improve throughput and reduce packet drop. A back-off interval selection scheme is introduced in combination with rate reduction (RR) and RRG. The back-off interval selection scheme considers channel state and collision-free transmission to prevent congestion. Simulations were conducted and the results were compared with those of decentralized predictive congestion control (DPCC) and adaptive duty-cycle based congestion control (ADCC). The results showed that the proposed method reduces congestion and improves performance.

An appropriate mathematical model can help researchers to simulate, evaluate, and control a proton exchange membrane fuel cell (PEMFC) stack system. Because a PEMFC is a nonlinear and strongly coupled system, many assumptions and approximations are considered during modeling. Therefore, some differences are found between model results and the real performance of PEMFCs. To increase the precision of the models so that they can describe better the actual performance, optimization of PEMFC model parameters is essential. In this paper, an artificial bee swarm optimization algorithm, called ABSO, is proposed for optimizing the parameters of a steady-state PEMFC stack model suitable for electrical engineering applications. For studying the usefulness of the proposed algorithm, ABSO-based results are compared with the results from a genetic algorithm (GA) and particle swarm optimization (PSO). The results show that the ABSO algorithm outperforms the other algorithms.

We use a domain ontology to construct a Semantic Web environment to unify and link the legacy databases, which typically have heterogeneous logic structures and physical properties. Users need only to interact with the Semantic Web environment, and perform searching, querying, and navigating around an extensible set of databases without the awareness of the database boundaries. Additional deductive capabilities can then be implemented to increase the usability and re-usability of data.
In the DartGrid project, we focus on three major TCM requirements, including academic virtual organization, personalized healthcare, and drug discovery and safety. Here we present a brief overview of the major applications that we have developed to satisfy the above requirements.

This paper presents a hybrid brain-computer interface (BCI) control strategy, the goal of which is to expand control functions of a conventional motor imagery or a P300 potential based BCI in a virtual environment. The hybrid control strategy utilizes P300 potential to control virtual devices and motor imagery related sensorimotor rhythms to navigate in the virtual world. The two electroencephalography (EEG) patterns serve as source signals for different control functions in their corresponding system states, and state switch is achieved in a sequential manner. In the current system, imagination of left/right hand movement was translated into turning left/right in the virtual apartment continuously, while P300 potentials were mapped to discrete virtual device control commands using a five-oddball paradigm. The combination of motor imagery and P300 patterns in one BCI system for virtual environment control was tested and the results were compared with those of a single motor imagery or P300-based BCI. Subjects obtained similar performances in the hybrid and single control tasks, which indicates the hybrid control strategy works well in the virtual environment.