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the plaintiff. In contrast, when both the plaintiff and the defendant presented diagrams, only 26% found for the plaintiff. Once again, mock jurors who viewed the computer animations found them to be more vivid and easier to imagine than did jurors who viewed the diagrams. However, unlike jurors in the rst study, they did not believe that the animated displays were the most important factor in deciding their verdicts. Instead, mock jurors believed that the expert testimony itself was most important. One potential explanation for the inconsistent ndings of Study 1 and 2 is that jurors rely more heavily on computer animation in cases involving subject matter with which they are less familiar or have less direct experience (Dunn, 2000). For example, although some jurors undoubtedly have experienced automobile accidents, it is highly unlikely that they have direct experience or increased familiarity with plane crashes. Overall, previous research examining the effects of computer animations on jurors decisions has yielded somewhat mixed ndings. Some studies have failed to observe that technologically advanced demonstrative evidence in uences jurors decisions any differently than other forms of evidence, such as charts, diagrams, or pictures. Although mock jurors in one study had a stronger emotional reaction to a videotape recreation of a drowning accident, that emotion did not translate into any detectable differences in jurors decisions on a variety of measures (Fishfader et al., 1996). However, other studies comparing the presence or absence of demonstrative evidence have observed that computer animations do in uence jurors judgments and that they may be unaware when this occurs. Finally, mock jurors in at least two of the studies we reviewed found computer animations to be more vivid and easier to visualize than the diagrams (Dunn, 2000).

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Adults in their twenties sometimes known as Millennials and other times as Generation Y have entered the workforce and have already begun to change it. Having grown up during a time of affluence and indulgence, they expect companies to bend to what they want and how they want to act rather than the other way around. Their appearance on the workforce scene, along with those who come after them (sometimes known as Generation Z), will hasten the move to bursty styles of work that allow them the autonomy they re used to. Generation Y and those after them expect to be able to connect to other people with new technologies like MySpace and text messaging. Corporate employers will have a hard time limiting use of social software during the workday. But should employers limit it As you ve seen, staying connected during the workday to both personal and professional contacts can mean a

RNC Resources QoS information Congestion info Data UE n MAC-e Capacity grants Data rate requests UE Cell-specific packet scheduler UE 1 MAC-e Capacity grants Data rate requests Node B

Assessing Capabilities, Staff Competency, and User Satisfaction The Three-Step Process to Becoming a World-Class Testing Organization Step 1: Define a World-Class Software Testing Model

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Ward, A., Ramsay, R., Turnbull, S., Benedettini, M. & Treasure, J. (2000) Attachment patterns in eating disorders: Past in the present. International Journal of Eating Disorders, 27, 279 287. Ward, A., Ramsay, R., Turnbull, S., Steele, M., Steele, H. & Treasure, J. (2001) Attachment in anorexia nervosa: A transgenerational perspective. British Journal of Medical Psychology, 74, 497 505. Wentz-Nilsson, E., Gillberg, C. & Rastam, M. (1998) Familial factors in anorexia nervosa. Comprehensive Psychiatry, 39, 392 399. Williams, G. (1997) Internal Landscapes and Foreign Bodies: Eating Disorders and Other Pathologies. London: Duckworth.

2.7.5.3. System requirements Communication capability: the capacity to use the underlying infrastructure wired and wireless and create ad hoc networks when needed. Sensing capability: sensing plays a very important role in Smart Surroundings. A wide variety of sensors will be used to determine phyisiological parameters, environmental data, activity levels, etc. Wireless sensor networks: WSNs will be used both indoors and outdoors for sensing and location functions. Simple sensed data is combined in different ways to obtain more complex information, as explained in the stress management and the Home Care SenseNet settings.

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