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members of the groups, and food and garbage ghts erupted in the dinning hall. In addition, group members regularly exchanged verbal insults (e.g., ladies rst ) and name-calling (e.g., sissies, stinkers, pigs, bums, cheaters, and communists ). During the third week, Sherif and his colleagues arranged intergroup contact under neutral, noncompetitive conditions. These interventions did not calm the ferocity of the exchanges, however. Mere intergroup contact was not suf cient to change the nature of the relations between the groups. Only after the investigators altered the functional relations between the groups by introducing a series of superordinate goals ones that could not be achieved without the full cooperation of both groups and which were successfully achieved did the relations between the two groups become more harmonious. Sherif et al. (1961) proposed that functional relations between groups are critical in determining intergroup attitudes. When groups are competitively interdependent, the interplay between the actions of each group results in positive outcomes for one group and negative outcomes for the other. Thus, in the attempt to obtain favorable outcomes for themselves, the actions of the members of each group are also realistically perceived to be calculated to frustrate the goals of the other group. Therefore, a win-lose, zero-sum competitive relation between groups can initiate mutually negative feelings and stereotypes toward the members of the other group. In contrast, a cooperatively interdependent relation between members of different groups can reduce bias (Worchel, 1986). Functional relations do not have to involve explicit competition with members of other groups to generate biases. In the absence of any direct evidence, people typically presume that members of other groups are competitive and will hinder the attainment of one s goals (Fiske & Ruscher, 1993). Moreover, feelings of interdependence on members of one s own group may be suf cient to produce bias. Rabbie s behavioral interaction model (see Rabbie & Lodewijkx, 1996; Rabbie & Schot, 1990; cf. Bourhis, Turner, & Gagnon, 1997), for example, argues that either intragroup cooperation or intergroup competition can stimulate intergroup bias. Similarly, L. Gaertner and Insko (2000), who unconfounded the effects of categorization and outcome dependence, demonstrated that dependence on in-group members could independently generate intergroup bias among men. Perhaps as a consequence of feelings of outcome dependence, allowing opportunities for greater interaction among in-group members increases intergroup bias (L. Gaertner & Schopler, 1998), whereas increasing interaction between members of different groups (S. Gaertner et al., 1999) or even the anticipation of future
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Figure 14.11 [Ref. 20].)
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Performance evaluation through simulation has the advantage that the resulting precision or accuracy of all nodes does not have to be measured, but is directly accessible. Thus, much larger systems can be evaluated. Systems and Topologies In ref. [32], systems with 200 nodes are evaluated, and in refs. [26] and [32] systems with up to 500 nodes, always randomly placed in a square area. The transmission range of the nodes is 10 m in a square of length 80 m [33] or 120 m [24]; in ref. [26], various transmission ranges from 0.4 m to 1 m are used in a square of length 10 m. In ref. [25], the transmission range is varied between 0.1 and 0.5 times the width of the square area. In ref. [14], a chain of 5 nodes is simulated. Message Delays For simulation, a number of assumptions about the behavior of the system have to be made (e.g., about message delays). In ref. [14], measured delay traces from an 802.11 wireless local area network (LAN) are used, and the authors of refs. [24] and [32] generate delay traces according to a normal distribution. In ref. [32], an additional offset is added that increases when the medium is saturated, that is, when more than 75% of the channel capacity is used. The authors of ref. [25] assume zero message delay, arguing that the synchronization errors induced by delay uncertainty and drift can be studied separately.
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Weinberg, R. S., & Gould, D. (2003). Foundations of sport and exercise psychology (3rd ed.). Champaign, IL: Human Kinetics. Weldon, E., & Weingart, L. R. (1993). Group goals and group performance. British Journal of Social Psychology, 32, 129 152. Widmeyer, W. N., Brawley, L. R., & Carron, A. V. (1990). The effects of group size in sport. Journal of Sport and Exercise Psychology, 12, 177 190. Williams, A. M., & Hodges, N. J. (Eds.). (2004). Skill acquisition in sport: Research, theory, and practice. London: Routledge. Williams, A. M., Ward, P., Herron, K., & Smeeton, N. J. (2004). Using situational probabilities to train perceptual and cognitive skill in novice soccer players. Journal of Sports Sciences, 22, 575 576. Wittenbaum, G. M., Vaughan, S. I., & Stasser, G. (1998). Coordination in task-performing groups. In R. S. Tindale & L. Heath (Eds.), Theory and research on small groups: Social psychological applications to social issues (Vol. 4, pp. 177 204). New York: Plenum Press.
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Throughout this book I have talked about various programs that can be used in the realm of secret communication. To help make this book more valuable to you I have included all of the source code in this appendix, including the techniques described in s 6 and 8. To make your life easier, I have also included the source code and .exe files on the accompanying CD ROM included with this book.
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Total Standard Revenue $ 3,263.00 10,344.00 5,027.00 4,174.50 1,484.00
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residents. The relationship between exposure to air pollution and health is mediated by perceptions of the exposure (Elliot, Cole, Krueger, Voorberg, & Wake eld, 1999). The extent to which people feel that they can control the source of air pollution, for instance, in uences their response to this pollution. Perceptions of air pollution are also important because they in uence people s responses to certain strategies for air pollution management. Whether people perceive air pollution as a problem is of course related to the actual existence of the problem. Generally, people are more likely to perceive environmental problems when they can hear (noise), see (smoke), smell, or feel them. Another important source of information is the media because the media s interpretation of pollution levels may have a social ampli cation effect and in uence public perceptions and attitudes (Kasperson et al., 1988). People believe that heavy-goods vehicles, commuters, and business traf c are the principal sources of urban air pollution. On the other hand, school traf c is often seen as one of the most important causes of transport problems. It is often argued that reducing school trips by car would make a signi cant difference to urban transportation problems. Paradoxically, although considered to be a major source of congestion, school traf c is not seen as a major source of pollution (Gatersleben & Uzzell, 2000). The Visual Impact of Buildings Most of us live in cities. The architecture that surrounds us is more than public sculpture. Research on the visual impact of buildings demonstrates perhaps more than any other area that different user groups perceive and evaluate the environment dissimilarly. The criteria used most widely by the public to assess the visual impact of a building is how contextually compatible it appears to be with the surrounding environment (Uzzell, 2000b). Architects and their clients, however, tend to value more highly the distinctiveness and contrast of buildings. Although there is a place for both, the indication is that there are diverging points of view on what constitutes a desirable building between groups of people (Hubbard, 1994, 1996). Groat (1994) found differences of opinion to be greatest between the public and architects and most similar between the public and planners. Several studies (e.g., Purcell & Nasar, 1992; Nasar, 1993) have demonstrated that architects and educated laypeople differ in their preferences for building styles and in the meanings that they infer from various styles. For example, Devlin and Nasar (1989) found that architects rated more unusual and distinctive residential architecture as more meaningful, clear, coherent, pleasant, and relaxing, whereas nonarchitects judged more conventional and popular residential architecture as such. Similarly, Nasar data matrix generator
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