Extending Java to dynamic object behaviors

Software Design Patterns are reusable designs providing common solutions to the similar kind of problems in software development. Creational patterns are that category of design patterns which aid in how objects are created, composed and represented. They abstract the creation of objects from clients thus making the application more adaptable to future requirements changes. In this work, it has been proposed and implemented the creation of objects involved in Decorator Design Pattern. (Decorator Pattern Adds Additional responsibilities to the individual objects dynamically and transparently without affecting other objects). This enhanced the reusability of the application design, made application more adaptable to future requirement changes and eased the system maintenance. Proposed DMS (Development Management System) web application is implemented using .NET framework, ASP.NET and C#.

The unceasing change problem of land information systems can be resolved through the refactoring and design pattern. To promote the implementation of design pattern and refactoring methods in developing land information systems reusing software design, applying refactoring methods to the abstract factory and decorator design patterns in land information system development is discussed.

Verification of object-oriented programs: A transformational approach

ACT++ (Actors in C++) is a concurrent object-oriented language being designed for distributed real-time applications. The language is a hybrid of the actor kernel language and the object-oriented language C++. The concurrency abstraction of ACT++ is derived from the actor model as defined by Agha. This paper discusses our experience in building a concurrent extension of C++ with the concurrency abstraction of the actor model. The current design of ACT++ and its implementation are described. Some problems found in the Agha''s actor model are discussed in the context of distributed real-time applications. The use of ACT++ disclosed the difficulty of combining the actor model of concurrency with class inheritance in an object-oriented language.

A dynamic icon is an icon whose graphical representation is computed and varies over time with changes in the properties of the object it represents. Dynamics icons make possible use of iconic representation of objects whose dynamic behavior must be reflected in their representation. The visual language PT incorporates dynamic icons to model dynamic object behavior in executing programs. This use of dynamic icons provides a natural program animation mechanism. Dynamic icons and their use in PT are discussed.< <ETX xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">&gt;</ETX>

Modeling of dynamic friction behaviors of hydraulic cylinders

Dynamic behavior and constitutive modeling of Ti-10-2-3 alloy

SOFL is a formal language and method for system specification and design. It was developed by integrating Petri Nets, Data Flow Diagrams, and VDM-SL. As the major feature of the original SOFL method is to use structured techniques for analysis and specification, and object-oriented techniques for design and implementation, SOFL has its own implementation language that is similar to C++. However during our recent work of applying SOFL to software systems, the transformation of structured specifications to object-oriented implementations creates some difficulties, simply because of paradigms mismatch. In this paper we extend SOFL to a formal object-oriented language and method while keeping its structured features. This will allow powerful object-oriented reuse mechanisms, such as class inheritance and object composition, to be utilized in the early phases, and transformation from SOFL specifications to commercial object-oriented programming languages to be readily achieved.

Class inheritance and method overriding, as provided by standard class-based languages, are not flexible enough to represent the dynamic behavior of objects; with this respect, object composition and delegation are often advocated as a more flexible alternative to class inheritance since they act at run-time, thus permitting the behavior of objects to be specialized dynamically. In this paper we present Incomplete Featherweight Java (IFJ), an extension of Featherweight Java with incomplete objects, i.e., objects that require some missing methods which can be provided at run-time by composition with another (complete) object. The mechanism for method invocation is based on delegation and it is disciplined by static typing, therefore the language enjoys type safety (which implies no message-not-understood run-time errors) and avoids possible accidental overrides due to method clashes.

This research investigates the discrete‐time dynamics of a predator–prey model governed by a ratio‐dependent Ivlev functional response incorporating harvesting on the predator population. Through a detailed algebraic analysis, we show that the system experiences both period‐doubling (PD) and Neimark–Sacker (NS) bifurcations within the positive quadrant of the phase space. Using the center manifold theorem and bifurcation theory, we provide a theoretical understanding of these bifurcations. To support our theoretical results, numerical simulations are performed, revealing chaotic behavior such as phase portraits, period‐12 orbits, invariant closed curves, and attractor chaotic sets. Additionally, we compute the Lyapunov exponents to confirm the chaotic nature of the system. The results demonstrate that parameter values play a crucial role in shaping the model's dynamic behavior. Finally, we showcase the practical application of chaos control by employing state feedback and the OGY method to stabilize chaotic trajectories around an unstable equilibrium point. This study deepens our understanding of complex predator–prey dynamics and highlights the potential for managing chaos in ecological systems. Further, bifurcations are explored in a discrete predator–prey model within a coupled network, with numerical simulations showing that chaotic behavior emerges in such networks when the coupling strength reaches a critical threshold. Furthermore, we implemented the Euler–Maruyama method for stochastic simulations to analyze our system in the context of environmental uncertainties. We examined various cases to investigate different environmental scenarios. All theoretical results on stability, bifurcations, and chaotic transitions in the coupled network are validated through numerical simulations.

Assessing patient transport conditions during ambulance transit.

BackgroundTranslating a known metabolic network into a dynamic model requires reasonable guesses of all enzyme parameters. In Bayesian parameter estimation, model parameters are described by a posterior probability distribution, which scores the potential parameter sets, showing how well each of them agrees with the data and with the prior assumptions made.ResultsWe compute posterior distributions of kinetic parameters within a Bayesian framework, based on integration of kinetic, thermodynamic, metabolic, and proteomic data. The structure of the metabolic system (i.e., stoichiometries and enzyme regulation) needs to be known, and the reactions are modelled by convenience kinetics with thermodynamically independent parameters. The parameter posterior is computed in two separate steps: a first posterior summarises the available data on enzyme kinetic parameters; an improved second posterior is obtained by integrating metabolic fluxes, concentrations, and enzyme concentrations for one or more steady states. The data can be heterogenous, incomplete, and uncertain, and the posterior is approximated by a multivariate log-normal distribution. We apply the method to a model of the threonine synthesis pathway: the integration of metabolic data has little effect on the marginal posterior distributions of individual model parameters. Nevertheless, it leads to strong correlations between the parameters in the joint posterior distribution, which greatly improve the model predictions by the following Monte-Carlo simulations.ConclusionWe present a standardised method to translate metabolic networks into dynamic models. To determine the model parameters, evidence from various experimental data is combined and weighted using Bayesian parameter estimation. The resulting posterior parameter distribution describes a statistical ensemble of parameter sets; the parameter variances and correlations can account for missing knowledge, measurement uncertainties, or biological variability. The posterior distribution can be used to sample model instances and to obtain probabilistic statements about the model's dynamic behaviour.

The design of mechatronic products requires cooperation and coordination of the involved disciplines. To analyze the dynamic behavior of the product’s subsystems and their components, multiple dynamic behavior models (DBM) are developed in different levels of detail (modeling depths) and domains. However, in order to simulate the complex interactions and dependencies between them, models of the whole system are needed, which fit the varying modeling objectives and analysis goals. These comprehensive models are often extensive and the manual construction presupposes deep insight in the specific model approaches and modeling tools. Furthermore, consistency needs to be ensured. The paper describes a way to automatically configure simulation models of the system adopting a Software Product Line (SPL) approach. With the use of feature models, SPL approach provides a structured method for managing variability. The particular focus of this paper is on handling of components in different tools with more than one level of detail through deployment of feature modeling. Also, it presents the concept of a multifunctional model client (MMC), which facilitates integration of solution and system knowledge.

In this paper, a time-delay structure is included in the neural network architecture to emulate the memory effects of wideband wireless transmitters. A simplified analysis approach is proposed to illustrate that the Real-Valued Time-Delay Neural Network (RVTDNN) is one of the most promising neural networks for modeling a complex dynamic nonlinear system. Then the RVTDNN is utilized to build the complex signal dynamic behavioral model of a wideband transmitter. Finally, a behavioral model with three-layer RVTDNN is employed in an experimental system to demonstrate the effectiveness of RVTDNNs in mimicking the dynamic behaviors of a wideband wireless transmitter.

Assuring the consistency between collaborative services is a challenge problem in service oriented architecture. In this paper, we propose an approach to verifying the consistency of collaborative services based upon model checking. We first introduce an Extended UML Sequence Diagram for modeling dynamic behavior of collaborative service combining with UML State Chart Diagram. And then we define Collaboration-Contracts and obtain the verification model from the dynamic behavior models. Finally, wean automatically verify the consistency of collaborative services in behavior models by using an integrated SPIN-binding modeling tool Trustable MDA we developed to, In addition, a user-friendly service simulator is provided to locate the position of inconsistency.