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century is to discover which aspects of behavior are likely to be altered by environmental events at speci c points in development and which aspects remain more plastic and open to in uence across wide spans of development In terms of units of analysis, researchers have begun to conceptualize the unit of analysis as dyads within the family system, such as the parent child dyad, the husband wife dyad, and the sibling dyad (Belsky, 1984; Cowan & McHale, 1996; Parke, 1988) Moreover, units beyond the dyad have been recognized as important as well Several researchers have recently begun to investigate triads (Hinde & StevensonHinde, 1988; Kreppner, 1988) as well as the family as units of analysis (Dickstein et al, 1998).

At present, this shift toward units beyond the individual is evident in cognitive as well as social development and is due, in part, to the revival of interest in Vygotskian theory Lev Vygotsky (1896 1934), a Russian psychologist, championed the view that mental functioning is a kind of action that may be exercised by individuals or by dyads or larger groups (Wertsch, 1991) His view was one in which mind is understood as extending beyond the skin Mind, cognition and memory are understood not as attributes or properties of individuals but as functions that may be carried out intermentally or intramentally (Wertsch & Tulviste, 1992, p 549) Such terms as socially shared cognition (Resnick, Levine, & Teasley, 1991), socially distributed cognition (Hutchins, 1991), and collaborative problem solving (Rogoff, 1990) re ect the increasing awareness that cognition can be a social as well as an individual enterprise.

In terms of methods, variety best describes the contemporary period In the 1990s, the use of longitudinal designs increased markedly, motivated in part by an increased interest in issues of developmental stability and change Two types of longitudinal studies are evident Short-term longitudinal studies, in which a particular issue is traced over a short time period of a few months to a year, are currently popular (Clarke-Stewart, Gruber, & Fitzgerald, 1994; Hetherington & Clingempeel, 1992) These studies are of value for detecting short-term stability or for tracking development across a time period of assumed rapid change in an emerging developmental process or structure Other longitudinal studies have a long-term character and have continued from infancy through childhood and into adolescence For example, a number of investigators have followed families from infancy to the preadolescent or adolescent years (Sameroff, 1994; Sroufe, 1996).

This strategy has permitted a more de nitive evaluation of a variety of theoretical issues, especially those concerning the effect of early experience, including the role of sensitive and critical periods on later development Nonetheless, because of the expense.

shared emotions, by what clinicians call empathy. His sexual nature may yet lead him to widening ambits of human affection, his acquisitive propensities to an optimum balance of work and leisure, and his aggressive drives to heightened social ef ciency through attacks on perils common to all men. (p. 457)

Now that you have the sensor data in a little 26-byte array, the task is to figure out how to parse it. Recall from Figures 2-5, 2-6, and 2-7 the organization of the sensor data packet. For SENSORS_ALL, Roomba sends the data as a single 26-byte chunk. The first byte is the bumps and wheeldrops bit field, the second byte is the wall value, and so on. The data has different formats: Word values: Two bytes joined together form a 16-bit value. Bit fields: A single sensor byte contains several independent binary values. Enumerations: A non-numeric byte with arbitrary values. Byte values: A byte contains a byte. This is the easy case, mostly. And for the non-bit values, there are the unsigned and signed (positive and negative) variants. Dealing with just the raw byte array with all these different types of data would be a big pain in the neck, so it s time to design some wrappers.

Specifically, the effective bit error rates in wireless networks are significantly higher than that in a wireline network because of higher cochannel interference, host mobility, multipath fading, disconnections due to coverage limitations, etc Packet error rates ranging from 1% in microcell wireless networks up to 10% in macrocell networks have been reported in experimental studies [4, 17] Although the higher packet error rates in wireless networks inherently degrade the performance experienced by connections traversing such networks, they cause an even more severe degradation in the throughput of connections using TCP as the transport protocol As described in the previous section, TCP multiplicatively decreases its congestion window upon experiencing losses The decrease is performed because TCP assumes that all losses in the network are due to congestion, and such a multiplicative decrease is essential to avoid congestion collapse in the event of congestion [8].