Bed morphology, flow structure, and sediment transport at the outlet of Lake Huron and in the upper St. Clair River

An integrated multibeam echo sounder and acoustic Doppler current profiler field survey was conducted in July 2008 to investigate the morphodynamics of the St. Clair River at the outlet of Lake Huron. The principal morphological features of the upper St. Clair River included flow-transverse bedforms that appear weakly mobile, erosive bedforms in cohesive muds, thin non-cohesive veneers of weakly mobile sediment that cover an underlying cohesive (till or glacio-lacustrine) surface, and vegetation that covers the bed. The flow was characterized by acceleration as the banks constrict from Lake Huron into the St. Clair River, an approximately 1500-m long region of flow separation downstream from the Blue Water Bridge, and secondary flow connected to: i) channel curvature; ii) forcing of the flow by local bed topography, and iii) flow wakes in the lee side of ship wrecks. Nearshore, sand-sized, sediment from Lake Huron was capable of being transported into, and principally along, the banks of the upper St. Clair River by the measured flow. A comparison of bathymetric surveys conducted in 2007 and 2008 identifies that the gravel bed does undergo slow downstream movement, but that this movement does not appear to be generated by the mean flow, and could possibly be caused by ship-propeller-induced turbulence. The study results suggest that the measured mean flow and dredging within the channel have not produced major scour of the upper St. Clair River and that the recent fall in the level of Lake Huron is unlikely to have been caused by these mechanisms.     

Collaborative jamming and collaborative defense in cognitive radio networks

In cognitive radio networks, cognitive nodes operate on a common pool of spectrum where they opportunistically access and use parts of the spectrum not being used by others. Though cooperation among nodes is desirable for efficient network operations and performance, there might be some malicious nodes whose objective could be to hinder communications and disrupt network operations. The absence of a central authority or any policy enforcement mechanism makes these kinds of open-access network more vulnerable and susceptible to attacks.In this paper, we analyze a common form of denial-of-service attack, i.e., collaborative jamming. We consider a network in which a group of jammers tries to jam the channels being used by legitimate users who in turn try to evade the jammed channels. First, we compute the distribution of the jamming signal that a node experiences by considering a random deployment of jammers. Then, we propose different jamming and defending schemes that are employed by the jammers and legitimate users, respectively. In particular, we model and analyze the channel availability when the legitimate users randomly choose available channels and the jammers jam different channels randomly. We propose a multi-tier proxy-based cooperative defense strategy to exploit the temporal and spatial diversity for the legitimate secondary users in an infrastructure-based centralized cognitive radio network. Illustrative results on spectrum availability rates show how to improve resiliency in cognitive radio networks in the presence of jammers.     

资产管理软件帮助节省成本

最近,一家厂商的自动润滑系统在人为地进行了一次未知的定时改动之后,损失了超过100,000美元与停工相关的费用。一个定时器之前是每20分钟注入一次润滑油,后来被设定为每8小时注入一次润滑油,导致机械轴承需要进行一次提前到来的改装。     

Engineering the Irish Software Tiger

Information and communication technologies, particularly software, play a crucial role in the Republic of Ireland's remarkable economic growth. Successful globalization has posed many challenges and fostered a major strategic investment in research. Ireland's unique position has a major influence on the realization of the software engineering research agenda.     

Remote flood monitoring system based on plastic optical fibres and wireless motes

This paper summarises an effort in the development of a remote flood monitoring system based on plastic optical fibre (POF) sensors and a wireless mote network. The wireless mote, comprising of a network of MICA2DOT™ units, was used as a platform to monitor and record the signal from the POF sensors and transmit this information to a base station wirelessly. A prototype of the integrated wireless POF sensor unit has been constructed, rendering it possible to deploy the autonomous unit remotely at multiple monitoring points as required. A flood monitoring simulation was carried out in a 24 m × 10 m × 0.9 m wave basin where four of these wireless optical fibre mote sensors were used to detect the rising water level in the basin. The novelty of the work lies in the successful integration of the wireless platform to a POF-based liquid level sensor and the subsequent demonstration of the prototype of the system for the purposes of flood monitoring applications.The sensing principle of the POF sensor developed here is well-known and is based on the loss of total internal reflection of the optical signal as the sensor probe comes in contact with the liquid. Compared to optical fibre-based sensors reported previously in the literature, the probe profile used in this study differs in terms of its simplicity in design, while exhibiting an excellent signal intensity loss ratio without the need for additional attachments to the probe such as optical prisms. The tests carried out showed that the POF sensor is capable of detecting a variety of fluids. Exhibiting good signal stability, the sensor also detects the liquid level reliably when the liquid rises or falls to the predetermined level. The responsiveness of the optical fibre sensor was evaluated by simulating different rates at which the liquid rises by immersing the sensor tip into the liquid and vice-versa at various speeds ranging from 1 mm/min to 500 mm/min.     

RBF neural networks for solving the inverse problem of backscattering spectra

This paper investigates a new method to solve the inverse problem of Rutherford backscattering (RBS) data. The inverse problem is to determine the sample structure information from measured spectra, which can be defined as a function approximation problem. We propose using radial basis function (RBF) neural networks to approximate an inverse function. Each RBS spectrum, which may contain up to 128 data points, is compressed by the principal component analysis, so that the dimensionality of input data and complexity of the network are reduced significantly. Our theoretical consideration is tested by numerical experiments with the example of the SiGe thin film sample and corresponding backscattering spectra. A comparison of the RBF method with multilayer perceptrons reveals that the former has better performance in extracting structural information from spectra. Furthermore, the proposed method can handle redundancies properly, which are caused by the constraint of output variables. This study is the first method based on RBF to deal with the inverse RBS data analysis problem.     

少花钱，多办事 华硕BM5320

BM5320是华硕新近推出的商用台式电脑,采用塔式机箱,外观设计简单朴实。 这款产品配备了Pentium E2220处理器、2GB DDR2 800内存、Radeon HD 3450独立显卡、DVD刻录机等主流硬件配置,机箱还采用了全免工具设计,拆卸检修十分方便。同时．其性能不仅能够胜任日常办公应用．还具备一定的图形处理能力,适合预算有限却又对产品性能有一定要求的企业用户。     

融合服务战略推动英国电信开启亚太市场之门

英国电信是第一个吹响转型号角的传统电信公司,也是第一家提出做“综合信息服务提供商”的运营商。目前它已经牢固确立了其作为网络IT解决方案提供商的核心定位。在全球经济危机蔓延,金融风暴影响实体经济的当下,作为经济结构中承担基础性架构角色的电信行业面临前所未有的挑战与机遇。英国电信（BT）清醒的认识到了这一点,借助IT与网络、数据与通讯融合的趋势浪潮,英国电信正在开启亚太市场的大门。     

Maximum Penalized Likelihood Kernel Regression for Fast Adaptation

This paper proposes a nonlinear generalization of the popular maximum-likelihood linear regression (MLLR) adaptation algorithm using kernel methods. The proposed method, called maximum penalized likelihood kernel regression adaptation (MPLKR), applies kernel regression with appropriate regularization to determine the affine model transform in a kernel-induced high-dimensional feature space. Although this is not the first attempt of applying kernel methods to conventional linear adaptation algorithms, unlike most of other kernelized adaptation methods such as kernel eigenvoice or kernel eigen-MLLR, MPLKR has the advantage that it is a convex optimization and its solution is always guaranteed to be globally optimal. In fact, the adapted Gaussian means can be obtained analytically by simply solving a system of linear equations. From the Bayesian perspective, MPLKR can also be considered as the kernel version of maximum a posteriori linear regression (MAPLR) adaptation. Supervised and unsupervised speaker adaptation using MPLKR were evaluated on the Resource Management and Wall Street Journal 5K tasks, respectively, achieving a word error rate reduction of 23.6% and 15.5% respectively over the speaker-independently model.     

Characterisation of flucloxacillin and 5-hydroxymethyl flucloxacillin haptenated HSA in vitro and in vivo

Flucloxacillin is a synthetic penicillin used in the treatment of Staphylococcal infections. Adverse reactions to the drug are believed to arise through covalent modification of proteins, with tissue damage occurring secondary to an immune reaction. Serum proteins have been shown by adduct-specific antibodies to be modified by flucloxacillin, but the nature and sites of modification have not been characterised. Here, in vitro studies on HSA have shown by MS that the modification of protein lysine residues occurs in a dose-, time- and site-dependent manner. Affinity, cation exchange and reversed phase chromatography prior to MS revealed in vivo modification of HSA with flucloxacillin in tolerant patients, with up to nine modified lysine residues being detected in each patient, and with modification of Lys190 and Lys212 being detected in 8/8 patients. It was also revealed for the first time that plasma proteins could be modified with the 5-hydroxymethyl metabolite of flucloxacillin, and that essentially the same Lys residues were targeted by both the parent drug and its metabolite. This study provides a detailed characterisation of sites of chemical modification of an endogenous target and reveals candidate peptides for T-cell and antibody assays of flucloxacillin hypersensitivity.