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Energy ef ciency and network capacity are two of the most important issues in wireless sensor networks. Topology-control algorithms have been proposed to maintain network connectivity while reducing energy consumption and improving network capacity. Several studies have also been performed to investigate critical conditions on several network parameters in order to ensure network k-connectivity (in the asymptotic sense). In this chapter, several problems (and their corresponding solutions) related to topology construction, maintenance, and connectivity in wireless sensor networks are discussed. Speci cally, topics discussed include (1) various communication models and generation of random network topologies; (2) neighbor discovery and maintenance; (3) basic connectivity properties of wireless sensor networks (with the random unit graph model as the underlying model); (4) localized topology construction algorithms, along with their associated geometric structures in both homogeneous and heterogeneous networks; and (5) how to enhance fault tolerance in topology construction and connectivity. 10.1 INTRODUCTION

The following example suggests that the same distinction may apply to human behavior Imagine seeing a cartoon drawing of an unfamiliar animal called a wug If I show you two of them, you will say, There are two wugs Shown two pictures of a creature called wuk, you will say, There are two wuks In saying the plural, your behavior is governed by the rule of English morphology that to make a noun plural, you add an -s Although you probably did not apply the rule consciously, it is not implausible to believe that you did as a child However, your behavior was also governed by a rule of English phonology that an -s following a voiced consonant (eg, /g/) is also voiced wugz while an -s following an unvoiced consonant (such as /k/) is also unvoiced wuks.

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THE SOCIAL-COGNITIVE PERSPECTIVE In this section, the primary variables studied using the social-cognitive approach in psychology are reviewed. The social-cognitive approach, in particular, self-efficacy theory (Bandura, 1977, 1982, 1986, 1997), when applied to exercise behavior, emphasizes the role that task-specific states have on perceiving and coping with exercise stimuli (e.g., physical effort). Goal Orientation Goal orientations reflect individual differences in assigning subjective meaning to outcomes (Ames, 1984; Maehr & Braskamp, 1986). The subjective meaning given to success and failure is linked to either a differentiated or an undifferentiated concept of ability. A differentiated concept of ability is determined by comparing one s performance and outcome to others . Ability can be evidenced by performing better than others, by surpassing normative-based standards, or by achieving success with little effort (Covington, 1984). This goal orientation is termed ego orientation. An undifferentiated concept of ability is utilized when subjective achievements are compared to self-referenced standards. This orientation is termed task orientation and is evoked by the need to meet and improve personal standards (Nicholls, 1984, 1989). Task goal orientation is associated with behaviors such as skill improvement, task mastery, working hard, and persistence. In contrast, ego goal orientation is associated with maladaptive or inhibitive behaviors when social comparisons are avoided; as a consequence, effort and confidence decrease (Jagacinski & Nicholls, 1990). Task and ego goal orientations are independent of each other and important determinants of motivation (see Duda & Hall, 2001, for a review). It is assumed that

Let P2 be the set of probability mass functions on X satisfying p(x) = 1,

4. 5. 6. 7. 8.

It is unlikely you ever consciously knew this rule at all Having developed the distinction between rule-governed and rule-following behaviors, we can state the algorithm-level distinction between the symbol-system and the connectionist architectures of cognition All psychologists accept the idea that human behavior is rule governed, because if it were not, there could be no science of human behavior The issue separating the symbol-system hypothesis from connectionism concerns whether and when human behavior is rule following According to the symbol system view, both the conscious processor and the intuitive processor are rule-following and rule-governed systems When we think or decide consciously, we formulate rules and follow them in behaving Intuitive thinking is likewise rule following In the case of behaviors, that were once consciously followed, the procedures of the intuitive processor are the same as the procedures once followed in consciousness, but with awareness subtracted.

is called the cochannel interference reduction factor or reuse factor and is the measure of cochannel interference. The Q factor determines spectral efficiency within a cell and is related to the number of cells in the cluster K. Assuming that all the cells transmit the same power, the frequency reuse distance D can be increased by increasing K. One could expect that by making K as large as possible, all problems concerning cochannel interference could be solved. An advantage of large clusters is the fact that the interference from cochannel cells decreases because the distance between the cochannel cells also increases with the increase in cluster size. On the other hand, the available bandwidth and therefore the available number of channels is fixed. When K is large, the number of channels per cell is small. That causes spectrum inefficiency. 3.3.2 Cosite and Adjacent Channel Interference In addition to cochannel interference, a second source of noise is the interference between two adjacent channels of the same (cosite interference) or adjacent cells (adjacent channel

Becker, Heimberg, & Bellack (1987)

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