1,531 research outputs found
Moral Responsibility Expressivism, Luck, and Revision
In his 1962 paper “Freedom and Resentment, Peter Strawson attempts to reconcile incompatibilism and compatibilism about moral responsibility and determinism. First, I present the error committed by the proponents of both these traditional views, which Strawson diagnoses as the source of their standoff, and the remedy Strawson offers to avoid the conflict. Second, I reconstruct the two arguments Strawson offers for a theory of moral responsibility that is based on his proposed remedy. Third, I present and respond to two proposed problems for the Strawsonian theory: moral luck and revisionism. I conclude with a summary of my defense of Strawsonian “expressivism” about moral responsibility, and offer suggestions for further research
GIS Modeling of the Prominent Geohazards in Arkansas
The State of Arkansas is prone to numerous geohazards. This thesis is a twofold study of prominent geohazards in Arkansas: the first fold includes a novel triggerless approach for mass wasting susceptibility modeling applied to the Boston Mountains in NW Arkansas, and the second fold is a GIS-based regression modeling of the extreme weather patterns at the state level. Each study fold is presented in this thesis as a separate chapter embracing a published peer-reviewed paper. In the first paper, I have used the analytical hierarchy process to assign preliminary statistical weights to the most cogent variables influencing mass wasting in the central Boston Mountains. These most significant variables are then incorporated in Fuzzy modeling of mass wasting susceptibility within the 1200 km2 study area. For comparison and accuracy assessment, a second model has been established using a conventional weighted overlay (WO) approach. Results indicate that the developed novel approach is superior, with approximately 83% accuracy, to the traditional WO approach that has a marginal success of about 28% accuracy. Road related mass wasting events recorded by the Arkansas Department of Transportation have been used to validate both models. In the second paper, I have conducted a systematically gridded analysis of severe weather events, including tornadoes, derechos, and hail, during 1955-2015. The study examines and statistically determines the most significant explanatory variables contributing to the spatial patterns of severe weather events between 1955 and 2015, consequently it identifies severity indices for the entire state. These weather-related hazards and their associated risk will always abide; therefore, the best defense is employ geospatial technologies to plan for hazard mitigation. The mass wasting model developed in this study contributes pivotal information for identifying zones of high risk along roadways in NW Arkansas, which definitely can be adapted to avoid disastrous road failures. In addition, the weather-related severity indices determined at the state level can profoundly benefit state and federal agencies focused on increasing the availability of public and private storm shelters in previously under-represented zones of high risk. This undoubtedly will save lives from unavoidable catastrophic events across the entire state
Model Predictive Wave Disturbance Rejection for Underwater Soft Robotic Manipulators
Inspired by the octopus and other animals living in water, soft robots should
naturally lend themselves to underwater operations, as supported by encouraging
validations in deep water scenarios. This work deals with equipping soft arms
with the intelligence necessary to move precisely in wave-dominated
environments, such as shallow waters where marine renewable devices are
located. This scenario is substantially more challenging than calm deep water
since, at low operational depths, hydrodynamic wave disturbances can represent
a significant impediment. We propose a control strategy based on Nonlinear
Model Predictive Control that can account for wave disturbances explicitly,
optimising control actions by considering an estimate of oncoming hydrodynamic
loads. The proposed strategy is validated through a set of tasks covering
set-point regulation, trajectory tracking and mechanical failure compensation,
all under a broad range of varying significant wave heights and peak spectral
periods. The proposed control methodology displays positional error reductions
as large as 84% with respect to a baseline controller, proving the
effectiveness of the method. These initial findings present a first step in the
development and deployment of soft manipulators for performing tasks in
hazardous water environments.Comment: To be presented at RoboSoft 2024, San Dieg
- …