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REMARK The vector * and, consequently, the final state of a neutral or generating continuous MG, is single and independent of the value of the initial marking. Thus, to obtain the final vector, it is possible to choose any value of the initial marking such that the continuous MG is live. From this characterization of final speeds, it is possible to determine the strongly, weakly or not enabled transitions of the net at the final state, and for a neutral continuous MG, to give its final state explicitly. 18.3.4.2. Final markings of neutral continuous marked graphs Let N be a weighted continuous MG with m places and n transitions. We note:

Unplanned activities, such as the need for clari cation of requirements, redesign, or additional debugging Through the iterative approach to planning, some of the estimation problems can be alleviated As the project progresses, a higher degree of approximation accuracy can be achieved The software development plan described in this chapter is a living document and its rst version should be created after the core requirements have been speci ed and a high-level architecture has been outlined Ideally, the plan should be reviewed after each iteration and updated as needed As the project progresses, the technology infrastructure might require further adjustments, customization, and expansion At the same time, the people infrastructure might need to be reassessed and augmented to match the needs of the project While not limited to this phase, these activities should have high priority during extended planning.

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In this chapter, we explain how to create an initial software development plan and how this plan should be adjusted as the product iterations progress We also show examples of the extended infrastructures necessary to meet the needs of applications such as embedded systems, web applications, web services, and databases The expected work products for this phase are:.

Study and instruction per se are indeed important, but learning is also deeply rooted in other everyday activities and experiences as well Most of the relevant knowhow that distinguishes an expert from a novice is acquired on a day-today basis by acting and re ecting, ie, by thinking about what we are doing and why, and talking about it with others (Sch n, 1983) In the second place, the view of learning as a totally individual activity, like ingesting food, can be misleading Learning is much more than, and very different from, nding and acquiring items of organizational knowledge As much in everyday life as in work organizations, people and groups create knowledge by negotiating the meaning of words, actions, situations and material artefacts.

Key factors in the prognosis for individuals with math learning disability include the effectiveness of classroom instruction and interventions. Because the component of math dif culty may vary across individuals, interventions need to vary depending on the type(s) of problems encountered. Many times the studies that are available related to math interventions do not meet methodological criteria, often not specifying how low math achievement was de ned or conceptualized (S. Baker, Gersten, & Lee, 2002); variation in how math disability is de ned further complicates review of math interventions. Table 3.2 provides a listing of interventions; however, many of the studies reviewed and referenced may be speci c to children with low math achievement as opposed to a math disability. From a neuropsychological perspective, the metacognitive skills and use of strategies (e.g., executive function processes) also may be the target of interventions. There is some support for the use of mnemonics, explicit goal setting, and self-monitoring, for example, to address de cits in executive processes, including attention and working memory, that affect math performance (Hayden & McLaughlin, 2004; Hayter, Scott, McLaughlin, & Weber, 2007; Schraw, 1998; Seabaugh & Schumaker, 1994). Teaching of metacognitive strategies has been found to result in improved math performance for children with math learning disability (Montague, 2008; Montague, Applegate, & Marquard, 1993).

11.2.1. Tensor products The tensor product allows us to obtain a tensor expression of the transition probabilities matrices of discrete time processes with K components. But it also translates at the generators level of the CTMC of continuous time processes, the impact of synchronization transitions which simultaneously produce state modi cations in several subsystems. It is mainly this property that we will use since we will study continuous time models. DEFINITION 11.2 (Tensor product). Let A Mn1 ,p1 and B Mn2 ,p2 . The tensor product ( ) of A and B is the matrix C Mn1 n2 ,p1 p2 : C=A B with cij = ai1 j1 bi2 j2

The paranoid personality is a challenging psychotherapy case. Most paranoids resist serious delusions; they come into contact with psychological services only at the request of others, as in two of the case studies in this chapter. A spouse may insist on either therapy

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