This study investigated how mindset intervention in freshman engineering courses influenced students’ implicit intelligence and self-efficacy beliefs. An intervention which bolsters students’ beliefs that they possess the cognitive tools to perform well in their classes can be the deciding factor in their decision to continue in their engineering major. Treatment was administered across four sections of an introductory engineering course where two professors taught two sections. Across three survey points, one course of each professor received the intervention while the other remained neutral, but the second time point switched this condition, so all students received intervention. Robust efficacy and mindset scales quantitatively measured the strength of their beliefs in their abilities, general and engineering, and if they believed they could change their intelligence and abilities. Repeated measures ANOVA and linear regressions revealed that students who embody a growth mindset tended to have stronger and higher self-efficacy beliefs. With the introduction of intervention, the relationship between mindset and self-efficacy grew stronger and more positive over time.

As a result of the increase of pollution related to industrialization in Vietnam, acid rain has become a prevalent issue for Vietnamese farmers who are forced to rinse their crops – risking damage due to overwatering and poor harvest. Thus, the team was motivated to develop a solution to harmful impacts of acidic rainwater by creating a system with the ability to capture rainwater and determine its level of acidity in order to optimize the crop watering process, and promote productive crops. By conducting preliminary research on rainfall and tropical climate in Vietnam, existing products on the market, and pH sensors for monitoring and device material, the team was able to design a number of devices to collect, store, and measure the pH of rainwater. After developing a number of initial design requirements based on the needs of the farmers, a final prototype was developed using the best aspects of each initial design. Tests were conducted with varying structural and aqueous materials to represent a broad range of environmental conditions. While the scope of the project was ultimately limited to prototyping purposes, the principles explored throughout this thesis project can successfully be applied to a fully-functioning production model available for commercial use on Vietnamese farms. Given more time for development, improvements would be made in the extent of materials tested, and the configuration of electronics and data acquisition, in order to further optimize the process of determining rainwater acidity.

As a result of the increase of pollution related to industrialization in Vietnam, acid rain has become a prevalent issue for Vietnamese farmers who are forced to rinse their crops – risking damage due to overwatering and poor harvest. Thus, the team was motivated to develop a solution to harmful impacts of acidic rainwater by creating a system with the ability to capture rainwater and determine its level of acidity in order to optimize the crop watering process, and promote productive crops. By conducting preliminary research on rainfall and tropical climate in Vietnam, existing products on the market, and pH sensors for monitoring and device material, the team was able to design a number of devices to collect, store, and measure the pH of rainwater. After developing a number of initial design requirements based on the needs of the farmers, a final prototype was developed using the best aspects of each initial design. Tests were conducted with varying structural and aqueous materials to represent a broad range of environmental conditions. While the scope of the project was ultimately limited to prototyping purposes, the principles explored throughout this thesis project can successfully be applied to a fully-functioning production model available for commercial use on Vietnamese farms. Given more time for development, improvements would be made in the extent of materials tested, and the configuration of electronics and data acquisition, in order to further optimize the process of determining rainwater acidity.

The goal for this thesis is to construct a quadcopter drone and design a controller for precise movements. The drone will be used to replace dangerous tasks that are currently done by hand like elevated painting, window washing, phoneline repair, etc. There are hundreds of different models and specifications of quadcopter drones, but the focus of the thesis is not on the actual body of the drone. The parts will be ordered online and assembled without rigorous design and analysis. The main goal of the drone design is within the controller to allow for precise movements from one location to another. The best software currently on the market for flight control is a program called ArduPilot. The first step will be to learn the software behind ArduPilot and design the controller in it. Since it is a popular software, the controller design might be very straightforward. If that is the case, the next step will be to design my own controller with a different software. After the controller design it finished, I will test the drone for flying precision and tweak the controller as necessary.

The objective goal of this research is to maximize the speed of the end effector of a three link R-R-R mechanical system with constrained torque input control. The project utilizes MATLAB optimization tools to determine the optimal throwing motion of a simulated mechanical system, while mirroring the physical parameters and constraints of a human arm wherever possible. The analysis of this final result determines if the kinetic chain effect is present in the theoretically optimized solution. This is done by comparing it with an intuitively optimized system based on throwing motion derived from the forehand throw in Ultimate frisbee.

This project compared two optimization-based formulations for solving multi-robot task allocation problems with tether constraints. The first approach, or the ”Iterative Method,” used the common multiple traveling salesman (mTSP) formulation and implemented an algorithm over the formulation to filter out solutions that failed to satisfy the tether constraint. The second approach, named the ”Timing Formulation,” involved constructing a new formulation specifically designed account for robot timings, including the tether constraint in the formulation itself. The approaches were tested against each other in 10-city simulations and the results were compared. The Iterative Method could provide answers in 1- and 2-norm variations quickly, but its mTSP model formulation broke down and became infeasible at low city numbers. The 1-norm Timing Formulation quickly and reliably produced solutions but faced high computation times in its 2-norm manifestation. Ultimately, while the Timing Formulation is a more optimal method for solving tether-constrained task allocation problems, its reliance on the 1-norm for low computation times causes it to sacrifice some realism.

This thesis presents the design and simulation of an energy efficient controller for a system of three drones transporting a payload in a net. The object ensnared in the net is represented as a mass connected by massless stiff springs to each drone. Both a pole-placement approach and an optimal control approach are used to design a trajectory controller for the system. Results are simulated for a single drone and the three drone system both without and with payload.