Discussion On Obstacle Categories And Prevention Please Resp

Discussion 1obstacle Categories And Prevention Please Respond To The

Suppose that you are performing an obstacle analysis of the software that you developed for the self-parking car discussed previously. Determine which of the following obstacle categories you would apply during the analysis: hazard obstacles, threat obstacles, dissatisfaction obstacles, misinformation obstacles, inaccuracy obstacles, and usability obstacles. Defend the selected category that you selected with two examples.

The alternative techniques for obstacle prevention are goal weakening, obstacle reduction, goal restoration, obstacle mitigation, and doing nothing. Examine the alternative techniques and select the one that you would use for obstacle presentation. Defend your selection.

Paper For Above instruction

The development of autonomous vehicle software, particularly for self-parking cars, involves intricate considerations to ensure safety, reliability, and user satisfaction. When analyzing obstacles within such a system, it is essential to categorize potential issues to plan effective prevention strategies. In this context, the most suitable obstacle category appears to be usability obstacles. Usability obstacles pertain to issues that hinder users from effectively interacting with the system, potentially leading to errors or hesitations that compromise safety.

For instance, one usability obstacle is the ambiguity in system prompts or instructions. If the self-parking software provides unclear signals to the user—such as vague visual cues indicating parking boundaries—the user may misinterpret these signals, leading to improper positioning or unnecessary adjustments. Another example involves the interface design of the control panel. If the buttons or touch interface are not intuitive or are poorly responsive, users might struggle to initiate, cancel, or override parking procedures, which could cause delays or unsafe maneuvers.

Regarding obstacle prevention, among the various techniques—goal weakening, obstacle reduction, goal restoration, obstacle mitigation, and doing nothing—the most appropriate for obstacle presentation is obstacle mitigation. Obstacle mitigation involves implementing measures to lessen the impact or likelihood of obstacles without completely eliminating the obstacle, which is often impractical. For example, integrating redundant sensors to cross-verify obstacle detection reduces the risk of false positives or negatives, thus mitigating the impact of sensor-related obstacles.

This approach allows the system to handle environmental uncertainties more robustly. If one sensor fails or provides incorrect data, others can compensate, thereby maintaining accurate obstacle detection. Additionally, obstacle mitigation such as smooth deceleration algorithms can reduce the safety impact if an obstacle is detected suddenly, providing ample time for safe maneuvering. The choice of obstacle mitigation over other techniques stems from the need to balance system complexity, cost, and the critical demand for safety and robustness in autonomous parking systems.

Discussion 2 "Obstacle Diagrams and Obstacle Identification"

The goal model diagrams and obstacle diagrams share similarities in that both visually represent system objectives and the potential hindrances to achieving those objectives. While goal models focus on the intended outcomes and their hierarchies, obstacle diagrams highlight the specific barriers that prevent goal achievement. A key dissimilarity is that goal models often emphasize process flows and decision points, whereas obstacle diagrams concentrate on points of failure or risk factors within the process.

An example where the tautology-based refinement technique is applicable is during refinement of safety constraints. For instance, refining a goal like "Ensure vehicle safety" with the tautology "Either the vehicle is safe, or it is not safe" helps to explicitly state that safety is either achieved or not, serving as a logical base. An example of using the obstructed target technique would be when a navigation system's target location becomes unreachable due to obstacles; explicitly modeling this obstruction helps to understand failure modes and plan compensatory actions. I chose these techniques because tautology refinement clarifies fundamental logical boundaries, whereas obstructed target modeling explicitly addresses specific failure scenarios and their impacts on system goals.

Discussion 3 "Term Paper Discussion"

In preparation for the term paper on reengineering the course enrollment process at Strayer University, I would discuss with the professor, acting as the stakeholder, to clarify several points. First, I would inquire about the current pain points experienced by both students and staff in the existing web-based enrollment system. For example, are there specific steps that are consistently confusing or time-consuming? Perhaps there are issues related to system access or data accuracy. Understanding these will guide the requirements gathering phase.

Additionally, I would ask about the scope of input modes to consider beyond the web, such as mobile app integration or in-person registration processes. Clarifying stakeholder expectations regarding automation, user interface preferences, and data security concerns would also be crucial. Lastly, I would request specific examples or scenarios that illustrate the current system's failures or inefficiencies—this will inform the analysis and help prioritize features in the proposed system-to-be. Engaging with the professor in this manner ensures that the reengineering effort aligns with university needs and stakeholder expectations, ultimately leading to a more effective and user-centered enrollment system.

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