AEXPAnalyst Experience
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Proposed prediction model of software development effort estimation has been used to predict software development effort by using sixteen independent parameters such as rely, data, cplx, time, stor, virt, turn, acap, aexp, pcab, vexp, lexp, modp, tool, seed, and kloc.
These sixteen attributes of project such as rely, data, cplx, time, stor, virt, turn, acap, aexp, pcab, vexp, lexp, modp, tool, seed, and kloc are correlated with the development effort.
M (t) = Aexp (-t/[T.sub.21]) + Bexp (-t/[T.sub.22] + Offset (7)
1: Drivers de Coste para el modelo de post-arquitectura de COCOMO II Driver de Coste (Post-arquitectura) Descripcion RELY Fiabilidad requerida del software DATA Tamano de la base de datos CPLX Complejidad del producto RUSE Reusabilidad requerida DOCU Documentacion de acuerdo a las necesidades del ciclo de vida TIME Restriccion de tiempo de restriccion STOR Restriccion de almacenamiento principal PVOL Volatilidad de la plataforma ACAP Capacidad de analistas PCAP Capacidad de programadores PCON Continuidad del personal AEXP Experiencia en aplicaciones PEXP Experiencia de plataforma LTEX Experiencia de lenguajes y herramientas TOOL Uso de herramientas de software SITE Desarrollo en multiples lugares Tabla No.
d[alfa]/dt = Aexp (-E/RT)[(1 - [alfa]).sup.n], (10)
Other distinguishing differences between HBCUs and non-HBCUs include lower average experience (AEXP) of faculty at HBCUs, lower average salaries (SALARY), and slightly lower student quality (SQUAL).
Our findings for AEXP and its square significantly indicate the concavity of the experience-research profile for economics departments at teaching institutions; that is, teaching institutions with economics faculty with more average experience have significantly larger JEL output.
Rate Constant k = Aexp (-E/[R.sub.1]T-[DELTA]vP/[R.sub.2]T) A(L/mol.s) E (cal/mol) [DELTA]v ([cm.sup.3]/mol) [] 6.04 x [10.sup.3] 38660.61 -- [K.sub.P] 5.12 x [10.sup.5] 4210.00 -5.6 [] 2.53 x [10.sup.9] 3374.94 9.21 [K.sub.ffm] 1.20 x [10.sup.5] 14400.00 -20 [K.sub.fp] 1.8 x [10.sup.5] 9400.00 -- [K.sub.b] 3.27 x [10.sup.5] 7474.13 -- [K.sub.[beta]] 1.4 x [10.sup.9] 19300.00 9.9 TABLE 3.
[tau] = Aexp [x[DELTA][h.sup.*]/k[T.sub.a] + (1 - x)[DELTA][h.sup.*]/k[T.sub.f]]] (6)
[k.sub.d] = Aexp (E/RT) A ([s.sup.-1]) E (cal/mol) A2 2.49 X [10.sup.15] 3.43 X [10.sup.4] A1 1.98 X [10.sup.12] 2.97 X [10.sup.4] All samples collected were ground for further analysis.
The results were then related to the absolute temperature by means of an Arrhenius dependence [[eta].sub.o] = Aexp ([E.sub.act]/(RT)), where A is a pre-exponential factor, [E.sub.act] is an energy of activation constant, R is the universal gas constant, and T is again the absolute temperature.