This section outlines how function point analysis can be applied to projects utilizing SOA. It is intended to provide general guidelines that should be followed to arrive at a useful function point size. For simplicity, the example framework in Figure 1 will be used in description of how FPA can be applied in SOA projects. While it is only one example of a SOA environment, the concepts described can be applied to other frameworks as well. The standard, repeatable process for conducting function point analysis, refer to Figure 2, should be followed when attempting to size projects with functionpoints in a SOA environment. The key factor in applying FPA is the determination of the user and count boundary as these combine to provide the foundation for what can and cannot be counted. A conscious decision must be made as to who or what the user is and where the boundary lies, both of which are based on the underlying purpose of the count. Once the user and boundary are established, the remainder of the function point analysis process can be applied.
Section 2 describes the future software marketplace model being used to guide the development of COCOMO 2.0. Section 3 presents the overall COCOMO 2.0 strategy and its rationale. Section 4 summarizes the COCOMO 2.0 software sizing approach, involving a tailorable mix of Object Points, FunctionPoints, and Source Lines of Code, with new adjustment models for reuse and re-engineering. Section 5 discusses the new exponent-driver approach to modeling relative project diseconomies of scale, replacing the previous COCOMO development modes. Section 6 summarizes the revisions to the COCOMO effort-multiplier cost drivers, including a number of additions, deletions, and updates. Section 7 presents the resulting conclusions based on COCOMO 2.0’s current state.
In each of the above problem, there is something common, i.e., we wish to find out the maximum or minimum values of the given functions. In order to tackle such problems, we first formally define maximum or minimum values of a function, points of local maxima and minima and test for determining such points.
oftware effort and cost estimation are necessary at the early stage of the software development life cycle for the project manager to be able to successfully plan for the software project. Unfortunately, most of the estimation models depend on details that will be available at the later stage of the development process. For example, the object oriented estimation models depend on the UML models – Use cases, Class diagrams and so on, which will not be available until the design stage. This situation –the need for information at the early stage but is available at the later, is referred to as software estimation paradox . This paper proposes to use dataflow diagram to solve this timing critical problem. At the requirement stage, the DFD can be used to depict the functionality of the software system. The information available in the dataflow can be used to obtain FunctionPoints and serve as the basis for software effort estimation.
Crossbows... The last wave front drawn (right of Figure 5) represents an exact La- grangian immersion of the circle with two double points, which is regularly homotopic to the standard embedding (exactness meaning that the total area enclosed by this curve is zero). It appeared in Arnold’s papers on Lagrangian cobordisms : this is the generator of the cobordism group in dimension 1. Arnold calls it “the crossbow”. Which reminds me of something Stein is supposed to have told Remmert in 1953 when he learned the use Cartan and Serre made of sheaves and their cohomology to solve problems in complex analysis: “The French have tanks. We only have bows and arrows” .
A lab study was conducted with 20 participants. At the time of registration user selects a click points on sequence of images. At login time an image is given to user from user profile. User makes a click point on the image. An algorithm calculates the hash value and measures system tolerance. If the click point is less than the system tolerance, next image is fetched else random image is given to user and login fail flag is activated. Participants were very accurate in entering click points during login phase.
Figure 6. The generalized exponential function in comparison with a second-degree polynomial and the Schnute function with b S 1 . Left: All three models are able to pass exactly through three points, which in the case of the generalized exponential function and the Schnute function have to represent increasing quantities with time (hence, these are growth curve functions). In contrast, the polynomial connects any three data points, but may have a maximum (above at t 1.725 ) or minimum (below at t 0.275 ) in between points. Only the generalized exponential function can be sigmoid with three points to go through (above). The functions can be calculated for negative time. Right: The underlying relationship of instantaneous logarithmic relative growth as a function of quantity is linear for the generalized exponential function, but highly nonlinear for the other two functions. The second-degree polynomial presents limits q L , where it reaches
Let f : [1, 2] → R where f(x) = x + 1. The graph of y = f(x) is a straight line segment as shown. It can be sketched without lifting pen from paper, so informally the function is continuous for all points in its domain. However, the formal definition of continuity above does not apply at the endpoints, since the two-sided limit in the definition makes no sense in this case.
It is easy to know that stability of CNNs play a important role for the application of CNNs. There have been abundant researches about stability of CNNs. Some sufficient conditions for CNNs to be stable were obtained by constructing Lyapunov Function [6-7], and these conditions generally made equilibrium point global asymptotically stable. However, some authors presented some conditions which made equilibrium points locally stable, and there generally were multiple equilibrium points [8-11]. In [8-9], the region of the number of equilibrium points of every cell in cellular neural networks is researched, however, the activation functions are the unity gain activation function and thresholding activation function, respectively. Therefore, in the paper, the region of the number of equilibrium points of every cell in cellular neural networks with negative slope activation function will be considered. If the activation function of CNNs is f x ( ) = − ( x + − − 1 x 1 2 ) , we call the activation function as negative slope activation function.
Brain natriuretic peptide (BNP) has been recognized as a useful marker for acute and chronic left ventricular dysfunction. A study by Wang et al.  was designed to evaluate the clinical relevance of BNP before and after off-pump coronary artery bypass surgery. The authors concluded that baseline BNP level correlated with preoperative ventricular function and longer durations of ventilation and hospital stay after off pump surgery. BNP increased early after operation. However, postoper- ative BNP did not correlate with myocardial injury or clinical results after off pump surgery.
We prove that the set of all common ﬁxed points for a continuous nonexpansive semigroup of nonlinear mappings acting in modular function spaces can be represented as an intersection of ﬁxed points sets of two nonexpansive mappings. This representation is then used to prove convergence of several iterative methods for construction of common ﬁxed points of semigroups of nonlinear mappings. We also demonstrate an example how the results of this paper can be applied for constructing a stationary point of a process deﬁned by the Urysohn integral operator. MSC: Primary 47H09; secondary 46B20; 47H10; 47H20; 47E30; 47J25
In this paper, we approximate ﬁxed points of ρ-nonexpansive multivalued mappings in modular function spaces using a Mann iterative process. We make the ﬁrst ever eﬀort to ﬁll the gap between the existence and the approximation of ﬁxed points of ρ-nonexpansive multivalued mappings in modular function spaces. In a way, the corresponding results of Dehaish and Kozlowski  are also generalized to the case of multivalued mappings.
Diﬀerential equations with turning points have various applications in mathematics, elasticity, optics, geophysics and other branches of natural sciences(see[6,10,11]). The importance of asymptotic analysis in obtaining informa- tion on the solution of a Sturm-Liouville equation with multiple turning points was realized by Leung , Olver [15-16], Heading , and Eberhard, Freiling and schnei- der in . The results of [10,2,3] bring important inno- vations to the asymptotic approximation of solutions of Sturm-Liouville equations with two turning points. Nea- maty and Dabbaghian , authors obtained Asymptotic form of the solution of (i)with m turning points of odd- even order. Marasi and Jodayree , authors considered that the weight function has m turning points that one is of odd order and others are of even order. In , au- thors considered duality for an indeﬁnite inverse Sturm- Liouville problem with one turning point. In this paper we obtain The canonical product of the solution of diﬀer- ential equation with turning points in a case where the weight function has three turning points that x 1 is of even
In this paper, the stress intensity factors for semi-elliptical cracks in a homogeneous isotropic cylinder have been determined. Athick-walled cylinder is subjected to a one-dimensional axisymmetric thermal shock on the outer surface according to the classic thermo elasticity (CTE), Green-Lindsay (G-L), and Green-Naghdi (G-N) theories. The effect of temperature-strain coupling and the effect of inertia term in governing equations are considered. The semi-elliptical crack stress intensity factors (SIFs) at the deepest and surface pointsare determined using weight function method. The comparison between the temperature, stress, and SIF obtained from CTE, G-L, and G-N theories shows the different behavior of generalized theories and CTE. By considering relaxation times, prediction of higher temperature and stress values, in contrast to CTE theory, will be resulted. Furthermore, the SIF resulted from generalized theories is significantly higher than CTE theory. The temper- ature, stress, and maximum SIF obtained for G-N II is higher than G-L theory.
riate real) elementary functions by the ordinary function operations, and the expression g x ( ) is given in so- called triple form ( ) G . This numerically coded form G is easy to learn, but also  gives a Maple code for its preparation. The parameter list of the segment is D D, G G, c c, alp α, m m, nt number of triples in G and the output parameter is
4. Condition on p is nearly optimal. We have shown in Theorem 2 that if the non- negative function p is such that each of its zero points is enclosed by a bounded surface of nonzero points, then equation (P +) has a large positive solution. In this section we show that, if the condition does not hold in the sense that p vanishes in an “outer ring” of the domain, then equation (P+) has no positive large solution.
Noting that points a are “excitation-only” points and that points b are “excitation and response” points, a two- stage measurement is convenient to describe the three ele- ments of the round trip. In the first stage, the structure is excited at a and the response measured simultaneously at b and c [the paths marked (1) in Fig. 1]. Since the product of the first two terms on the rhs of Eq. (9) is equal to the gener- alized transmissibility (T ¼ Y ca Y 1 ba ) (Ref. 16), this can be obtained from matrices of the responses at a and c under a set of different force distributions, without explicit knowl- edge of the applied forces. 17 Thus, the first stage of the mea- surement can potentially use excitation from unknown forces, including naturally occurring sources or operational forces, although this possibility will not be further explored in this paper. The second stage measurement requires excita- tion with known forces at b and measurement of response at c to give the last leg of the round trip [the path marked (2) in Fig. 1]. In practice these measurements would often be done with a force hammer for structural systems or a volume ve- locity source for acoustic systems.