Students in the Modeling and Simulation graduate program have often focused their study and research efforts in one or more of the following research areas:. Typical problem areas for behavioral aspects of cybersecurity include insider threats, hacker motivations, user training and education, digital ethics, cyber law and policy, senior leader education, and cyber workforce development and education.
Students in this research area typically have an interest in the area of Emerging Media, which focuses on the development of new forms of interactive media and the creation of story-driven content for them such as interactive works of art, electronic games, virtual reality, the Internet, portable devices and mobile applications, wearable computers, etc.
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The Simulation Modeling and Analysis research area attracts those who desire to gain expertise in using simulation as a optimization tool for effective design, planning, analysis, and decision-making. The emphasis of this area is on problem definition, model formulation, design of simulation experiments, and model-based analysis. This area attracts those who seek to develop skills in the application of advanced quantitative methods to modeling and simulation.
Building on backgrounds in operations research, mathematics or statistics, they should gain experience in modeling and simulation through the application of optimization, mathematical and statistical theory to build multidisciplinary simulation models and conducting rigorous simulation experimentation. A graduate will be prepared to work with corporate and government decision-makers as they model and evaluate the impacts of proposed policies and system designs.
Issues related to bringing down the cost of healthcare and reducing costly medical errors are generating many new opportunities related to systems analysis, communication between healthcare providers and patients, and simulation-based training, to name a few. Currently a disproportionate amount of the US economy goes to healthcare, at least twice as much as the average of the 25 richest nations, and health outcomes in the US place the country near the bottom of this group of countries.
Graduates specializing in this research area typically are interested in creating designs for simulators and simulator-based training systems and to apply expert systems and other intelligent systems in a simulation setting. The research area of Simulation Infrastructure attracts those who wish to gain an in-depth understanding of the basic components of simulation systems and their patterns of configuration and communication, including hardware and software issues.
They will gain experience in the development of distributed simulation and training environments. The emphasis on iterative models is that software development is a knowledge-intensive process and that things like analysis can't really be completely understood without understanding design issues, that coding issues can affect design, that testing can yield information about how the code or even the design should be modified, etc.
Although it is possible to do object-oriented development using a waterfall model, in practice most object-oriented systems are developed with an iterative approach. As a result, in object-oriented processes "analysis and design" are often considered at the same time. The object-oriented paradigm emphasizes modularity and re-usability.
The goal of an object-oriented approach is to satisfy the "open closed principle". A module is open if it supports extension, or if the module provides standardized ways to add new behaviors or describe new states. In the object-oriented paradigm this is often accomplished by creating a new subclass of an existing class. A module is closed if it has a well defined stable interface that all other modules must use and that limits the interaction and potential errors that can be introduced into one module by changes in another.
In the object-oriented paradigm this is accomplished by defining methods that invoke services on objects. Methods can be either public or private, i. This reduces a source of many common errors in computer programming.
The distinction between analysis and design is often described as "what vs. In analysis developers work with users and domain experts to define what the system is supposed to do. Implementation details are supposed to be mostly or totally depending on the particular method ignored at this phase. The goal of the analysis phase is to create a functional model of the system regardless of constraints such as appropriate technology. In object-oriented analysis this is typically done via use cases and abstract definitions of the most important objects. The subsequent design phase refines the analysis model and makes the needed technology and other implementation choices.
In object-oriented design the emphasis is on describing the various objects, their data, behavior, and interactions. The design model should have all the details required so that programmers can implement the design in code. The purpose of any analysis activity in the software life-cycle is to create a model of the system's functional requirements that is independent of implementation constraints.
The main difference between object-oriented analysis and other forms of analysis is that by the object-oriented approach we organize requirements around objects, which integrate both behaviors processes and states data modeled after real world objects that the system interacts with.
In other or traditional analysis methodologies, the two aspects: processes and data are considered separately. For example, data may be modeled by ER diagrams , and behaviors by flow charts or structure charts.
Object-Oriented Modeling (Current Issues in Electronic Modeling) | KSA | Souq
Common models used in OOA are use cases and object models. Use cases describe scenarios for standard domain functions that the system must accomplish.
Object models describe the names, class relations e. Circle is a subclass of Shape , operations, and properties of the main objects. User-interface mockups or prototypes can also be created to help understanding. During object-oriented design OOD , a developer applies implementation constraints to the conceptual model produced in object-oriented analysis.
Such constraints could include the hardware and software platforms, the performance requirements, persistent storage and transaction, usability of the system, and limitations imposed by budgets and time. Concepts in the analysis model which is technology independent, are mapped onto implementing classes and interfaces resulting in a model of the solution domain, i. Important topics during OOD also include the design of software architectures by applying architectural patterns and design patterns with object-oriented design principles.
Object-oriented modeling OOM is a common approach to modeling applications, systems, and business domains by using the object-oriented paradigm throughout the entire development life cycles.
Object-oriented modeling typically divides into two aspects of work: the modeling of dynamic behaviors like business processes and use cases , and the modeling of static structures like classes and components. Users typically have difficulties in understanding comprehensive documents and programming language codes well. Visual model diagrams can be more understandable and can allow users and stakeholders to give developers feedback on the appropriate requirements and structure of the system.
A key goal of the object-oriented approach is to decrease the "semantic gap" between the system and the real world, and to have the system be constructed using terminology that is almost the same as the stakeholders use in everyday business. Object-oriented modeling is an essential tool to facilitate this. Modeling helps coding. A goal of most modern software methodologies is to first address "what" questions and then address "how" questions, i.