Hierarchy in Java
Soil saturated at surface
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Neighboring nodes that did not yet receive the full message will reply to the short message with a request to receive it. The sensor will then respond by sending the full message to all nodes that requested it. If an omnidirectional antenna is used, sensors may retransmit the full message upon receipt of the rst request for it. Note, however, that, short request messages may be sent back to the transmitting node only if it is a neighbor in a selected sparse, connected structure, as observed in ref. [20], greatly reducing the amount of short messages needed. For example, if a LMST [18] is used as the sparse structure, the reduction is about 2/d times, where d is the average number of neighbors in the network. This reduction is possible if nodes have 2hop topological or onehop positional information about their neighbors. 13.3.3 Geocasting in Wireless Sensor Networks Data dissemination, or task allocation, from the sink does not need to be propagated to all active sensors. If only sensors that are close to a monitoring event (e.g., a factory that pollutes the environment) need to be alerted, then only sensors located inside a geographic region need to receive the task. This problem is known as geocasting. A survey of existing geocasting schemes is given in ref. [21]. It was shown that most existing geocasting schemes do not guarantee delivery to all nodes inside a region, the main reasons being either the partitioning of the network inside the region, or applying greedy routing instead of one that guarantees delivery. Yu, Govindan, and Estrin [22] considered a geocasting variant of the datagathering problem. They describe the geographic and energyaware routing (GEAR) algorithm, which uses energyaware neighbor selection to route the packet toward the target region, and recursive geographic forwarding, or restricted blind ooding algorithm, to disseminate the packet inside the destination region. Recursive forwarding applies GEAR to send messages to four subregions in the geocast region, which repeats until the region has a single node inside it. Blind ooding does not guarantee delivery to all sensors inside the region, because of possible partition inside the region (but connectivity outside it), and can be replaced by a more intelligent scheme (see 11 in this book). The GEAR algorithm selects a forwarding neighbor (among those that are closer to the destination), which minimizes a linear combination of their distance to the destination and the energy they already spent. This is almost equivalent to the costaware localized scheme by Stojmenovic and Lin [7], originally proposed in 1998 (described in detail in 12). Yu, Govindan, and Estrin [22] also claim that GEAR can avoid holes by applying a learning A algorithmbased approach, without presenting details. To avoid holes, one can use, for example, the depth rst search (DFS) approach [23]. 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They also put little icons (provided by Netscape at no charge) on their pages saying: This site looks best when viewed with Netscape Navigator. What could be more of a pain for designers What could be better for Netscape As it turned out, Microsoft ended up adding support for frames to their own browsers, making frames a standard. Now, both Netscape Communicator 4.7 and Internet Explorer 5.0 support frames. Most sites look identical in either Netscape or IE, as long as you re running the newest version of the browser. technical, cognitive, and emotional. In addition, an overarching requirement is that the person masters the psychological skills of motivational and goalsetting strategies, imagery and mental training, and interpersonal skills. A third focus has been on the coaches who facilitate the pursuit of excellence/expertise (e.g., G. A. Bloom, Stevens, & Wickwire, 2003; C t , Salmela, Trudel, Baria, & Russell, 1995; C t & Sedgwick, 2003; Fahlstrom, 2005; Isberg, 2005; Salmela & Moraes, 2003; Wolfenden & Holt, 2005). Several scholars studying the development of talent and giftedness have noted that the mentor (i.e., the coach, in our context) is quite instrumental in both the identification and development of talent (e.g., B. S. Bloom, 1985; Ericsson, 1996; Heller, M nks, & Passow, 1993; Hemery, 1986; Salmela & Moraes, 2003). Van Rossum (1995) found that his sample of nationallevel Dutch athletes identified their coaches along with their parents as the most important persons in their athletic careers. Even more significant, their respective coaches were most instrumental in identifying them as talented individuals. Based on the premise that most contexts of pursuit of excellence in sport are guided and controlled by coaches, and based on the extant literature, I present next a model of the pursuit of excellence and a set of leader behavior categories best suited to facilitate the pursuit of excellence. Leadership in the Pursuit of Excellence The model of pursuit of excellence in sport is illustrated in Figure 5.4. In brief, the person with the relevant talent, dispositions, and beliefs engages in deliberate practice to master the skills and gain the strategic and tactical knowledge

