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A third source of groundwater quality degradation exists, which does not t neatly into a classi cation of pollutant sources : these are natural bodies of poor quality water which are induced by heavy pumping to enter aquifers which previously contained good quality groundwater. Examples include sea water (see Figure 7.2, Section 7.2.4), deep saline groundwaters, and naturally toxic groundwaters (see Section 8.2.5). These and other sources of poor-quality groundwater whose mobility is aggravated by aquifer exploitation will be considered in some detail in Section 9.3.5. Before we go on to consider particular sources of groundwater pollution, it is necessary to consider the hydrogeological factors which determine the ease or dif culty with which any pollutant might enter a given aquifer. 9.3.2 Aquifer vulnerability Groundwaters tend to be inherently less prone to contamination than surface waters, thanks to the protection afforded by ltration and biogeochemical reactions which occur during subsurface ow (see Section 7.2.3). Recognition of the potency of these natural puri cation processes also provides the rationale for many bank ltration well elds currently operative worldwide (Section 7.4.2; Tufenkji et al. 2002). For all the admirable purifying powers of natural rocks, there are limits to the patience of Mother Earth: expose the ground to a suf cient quantity of pollutants for a suf ciently long period of time, and you will eventually overwhelm the assimilative capacity of the soil, subsoil, and aquifers. Pollution will ensue, with all of its attendant impacts on the economics of water supply and the health of ecosystems which receive discharging groundwaters.

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C Sung and W Wong, Sequential packing algorithm for channel assignment under conchannel and adjacent channel interference constraint, IEEE Trans Veh Techn, 46(3), 1997 35 S W Halpern, Reuse partitioning in cellular systems, in Proc IEEE Conf on Veh Techn, pp 322 327 New York: IEEE, 1983 36 S Ub da and J Zerovnik, Upper bounds for the span in triangular lattice graphs: application to.

EPILOGUE Implementation of VoIP has reached a level of maturity that allows it to migrate easily from laboratory and prototype implementations to deployment in both residential and enterprise networks. Many new Internet protocol- and paradigm-based call control, signaling, and QoS guaranteeing techniques have been developed, and these are continuously evolving. Undoubtedly, they will accelerate the convergence of both voice and data services and the related network infrastructures, resulting in ubiquitous availability of the VoIP service.

Figure 7.2 Spectrograms for the force data (a) and respiration ( b) of a single participant (data from Siegmund et al., 1999). The power spectral density was estimated over consecutive time windows of 10 s. Panel (c) depicts the scaledcross integral as a function of time. In all panels, time (s) is displayed on the x-axis. In (a) and ( b), frequency, f (Hz), is displayed on the y-axis and the spectral power, P (dimensionless), on the z-axis. In (c), the frequency-locking ratio is displayed on the y-axis, and the frequency-locking strength on the z-axis. The relationship between the frequencies with the maximal spectral power, fstroke and fresp, ref lect the frequency-locking ratio. Initially, fstroke: fresp = 1;1, and a switch to fstroke: fresp = 1;2 can be observed.

The author would like to extend thanks to Mr. Xiaowei Zhou, for assistance in tests and experiments, to Dr. Edwin Lughofer, for providing the data for the NOx problem, and to Prof. Fernando Gomide, for useful feedback on the manuscript.

Assumptions About the Error Term 1. Zero-mean assumption. The error term is a random variable, with mean or expected value equal to zero. In other words, E( ) = 0. 2. Constant-variance assumption. The variance of , denoted by 2 , is constant regardless of the value of x. 3. Independence assumption. The values of are independent. 4. Normality assumption. The error term is a normally distributed random variable. In other words, the values of the error term i are independent normal random variables, with mean 0 and variance 2 .

been discussed, the slide shows a routed packet using direct and indirect routing. This is regardless of the routing protocol. In this slide, we can see that a PC (endstation A) is trying to pass a datagram to a host machine, called host D. The host machine is one hop (one router) away. The IP layer of the PC (endstation A) knows that it must use a router (the source and destination network addresses are different), and will use RIP or the default gateway to determine the IP address of the router to use. Upon determining the router s physical address, it will physically (MAC layer) address the packet to the router at port B. The source and destination IP addresses in the IP header of this datagram will be the PC as the source, and the destination IP address as the host. The source (PC) and final destination (the host) IP addresses will be embedded into the IP header and will not change throughout the routing of this datagram.