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are positioned at known coordinates in the area being monitored. Since each tag transmits data in different, preassigned time slots, multiple access interference is greatly reduced. Due to the drift in the clock of the mobile devices as well as the xed nodes, synchronization between the xed nodes and the mobile devices is performed once every second. This is achieved by broadcasting a beacon from one of the xed nodes. The TOA of the beacon is used as the reference clock for the mobile devices to transmit data according to the preassigned time slots. At any given time, the TOA measurements from a speci c group of xed nodes are collected for position estimation by the system. Since each tag is moving, the group of xed nodes will change over time. In general, the xed nodes with the strongest received signal powers are selected to provide the TOA estimates and their position coordinates are employed for the mobile tag position estimation. There are many position estimation techniques using radio signals. Signal strength, angle of arrival, TOA measurements, time of ight/round trip time, and TDOA can all be exploited for position estimation. The most straightforward way to estimate position is to directly solve a set of simultaneous equations [4] based on the TOA/TDOA measurements. Exact solutions can be obtained for 2-D location with two xed nodes using two TOA measurements (with known transmit time) or with three xed nodes using three TDOA measurements. For a 3-D location, four xed nodes are needed to obtain exact solutions using TDOA measurements. For an over-determined system (with redundant xed nodes), several different approaches have been proposed such as spherical interpolation [5 8], the twostage maximum likelihood method [9], and the linear-correction least square approach [10]. Also several iterative approaches have been investigated for position estimation. Taylor series expansion can be used to iteratively produce a linear least-square solution [11, 12]. However, to maintain good convergence, the Taylor series method may require a close estimate of the actual location as a starting point which may be dif cult to obtain in some practical applications. A different iterative method for location comes from nonlinear optimization theory. The gradient-based algorithms may be employed for position estimation [13, 14]. One is the quasi-Newton algorithm [15], which has been used in the UWB precision assets location system [16]. The other is the Gauss Newton type Levenberg Marquardt method [17]. In this chapter, several location algorithms have been investigated based on noniterative techniques utilizing TOA information. Results will be presented in later sections. 17.5 SYSTEM IMPLEMENTATION
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Figure 14.9 The structure of an Evolutionary Algorithm.
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From now on, it s up to your script whether a certain window can be minimized or maximized. Have a look. Figure 12-5 shows a Notepad window without Minimize and Maximize buttons.
If any unit can be a central one in the infrastructure, and the program can be applied exactly from this unit (unit.3 included), it can be further simpli ed as follows:
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It costs 10 times more to attract and acquire a customer than to retain one. Microsoft Business http://www.microsoft.com/business/crm/crmsupport.asp Did you know that it costs eleven times more to attract a new customer than it does to retain an existing customer Cybeer http://www.cybeer.co.uk/loyalty.htm Since it costs 12 times more to get a customer than to keep one, no business can afford to neglect this vital skill set. Coreplus Workshops http://www.coremap.com/ws-selling.htm It costs twenty times more to attract a new customer than it does to keep an existing one. Basic Success (http://www.basicsuccess.com/aboutus.php) I think I'm going to go with Cisco Systems' assessment: It costs many times more to attract a new customer [than] it does to retain an existing one. Cisco (http://www.cisco.com/warp/public/3/be/discover/customer_care.htm) The question about how many times more it costs can only be answered on an individual basis. The more important question is this: Are you measuring your ability to retain customers When a would-be buyer surfs away from your site before finishing the buying process, that's called abandonment. Attrition is when that would-be buyer never returns. The opposite of abandonment is a sale. The opposite of attrition is retention. Hook 'em and keep 'em. At some specific point in time, a potential customer becomes aware of your offerings. You have reached her. At some point, she shows up at your site. You have acquired her. She becomes more and more qualified, until, at a specific point, she turns into a customer. From then on, continued selling becomes a matter of retention (see Figure 12.9). It's a question of product cycle, lifestyle, and persuasion engineering.
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