Matching Items (20)

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Mechanisms for quorum sensing in Temnothorax

Description

Temnothorax ants are a model species for studying collective decision-making. When presented with multiple nest sites, they are able to collectively select the best one and move the colony there.

Temnothorax ants are a model species for studying collective decision-making. When presented with multiple nest sites, they are able to collectively select the best one and move the colony there. When a scout encounters a nest site, she will spend some time exploring it. In theory she should explore the site for long enough to determine both its quality and an estimate of the number of ants there. This ensures that she selects a good nest site and that there are enough scouts who know about the new nest site to aid her in relocating the colony. It also helps to ensure that the colony reaches a consensus rather than dividing between nest sites. When a nest site reaches a certain threshold of ants, a quorum has been reached and the colony is committed to that nest site. If a scout visits a good nest site where a quorum has not been reached, she will lead a tandem run to bring another scout there so that they can learn the way and later aid in recruitment. At a site where a quorum has been reached, scouts will instead perform transports to carry ants and brood there from the old nest. One piece that is missing in all of this is the mechanism. How is a quorum sensed? One hypothesis is that the encounter rate (average number of encounters with nest mates per second) that an ant experiences at a nest site allows her to estimate the population at that site and determine whether a quorum has been reached. In this study, encounter rate and entrance time were both shown to play a role in whether an ant decided to lead a tandem run or perform a transport. Encounter rate was shown to have a significant impact on how much time an ant spent at a nest site before making her decision, and encounter rates significantly increased as migrations progressed. It was also shown to individual ants did not differ from each other in their encounter rates, visit lengths, or entrance times preceding their first transports or tandem runs, studied across four different migrations. Ants were found to spend longer on certain types of encounters, but excluding certain types of encounters from the encounter rate was not found to change the correlations that were observed. It was also found that as the colony performed more migrations, it became significantly faster at moving to the new nest.

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Date Created
  • 2013-05

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SoundSwarm: An Interactive Exploration of 3-Dimensional and Behavioral Modeled Sound

Description

This paper outlines the development of a software application that explores the plausibility and potential of interacting with three-dimensional sound sources within a virtual environment. The intention of the software

This paper outlines the development of a software application that explores the plausibility and potential of interacting with three-dimensional sound sources within a virtual environment. The intention of the software application is to allow a user to become engaged with a collection of sound sources that can be perceived both graphically and audibly within a spatial, three-dimensional context. The three-dimensional sound perception is driven primarily by a binaural implementation of a higher order ambisonics framework while graphics and other data are processed by openFrameworks, an interactive media framework for C++. Within the application, sound sources have been given behavioral functions such as flocking or orbit patterns, animating their positions within the environment. The author will summarize the design process and rationale for creating such a system and the chosen approach to implement the software application. The paper will also provide background approaches to spatial audio, gesture and virtual reality embodiment, and future possibilities for the existing project.

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Date Created
  • 2016-05

Optimization of Incoming Inspection

Description

The first step in process improvement is to scope the problem, next is measure the current process, but if data is not readily available and cannot be manually collected, then

The first step in process improvement is to scope the problem, next is measure the current process, but if data is not readily available and cannot be manually collected, then a measurement system must be implemented. General Dynamics Mission Systems (GDMS) is a lean company that is always seeking to improve. One of their current bottlenecks is the incoming inspection department. This department is responsible for finding defects on parts purchased and is critical to the high reliability product produced by GDMS. To stay competitive and hold their market share, a decision was made to optimize incoming inspection. This proved difficult because no data is being collected. Early steps in many process improvement methodologies, such as Define, Measure, Analyze, Improve and Control (DMAIC), include data collection; however, no measurement system was in place, resulting in no available data for improvement. The solution to this problem was to design and implement a Management Information System (MIS) that will track a variety of data. This will provide the company with data that will be used for analysis and improvement. The first stage of the MIS was developed in Microsoft Excel with Visual Basic for Applications because of the low cost and overall effectiveness of the software. Excel allows update to be made quickly, and allows GDMS to collect data immediately. Stage two would be moving the MIS to a more practicable software, such as Access or MySQL. This thesis is only focuses on stage one of the MIS, and GDMS will proceed with stage two.

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Date Created
  • 2017-05

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Developing an Educational Manufacturing Simulation

Description

Simulation games are widely used in engineering education, especially for industrial engineering and operations management. A well-made simulation game aids in achieving learning objectives for students and minimal additional teaching

Simulation games are widely used in engineering education, especially for industrial engineering and operations management. A well-made simulation game aids in achieving learning objectives for students and minimal additional teaching by an instructor. Many simulation games exist for engineering education, but newer technologies now exist that improve the overall experience of developing and using these games. Although current solutions teach concepts adequately, poorly-maintained platforms distract from the key learning objectives, detracting from the value of the activities. A backend framework was created to facilitate an educational, competitive, participatory simulation of a manufacturing system that is intended to be easy to maintain, deploy, and expand.

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Created

Date Created
  • 2018-12

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The Use of Simulation in a Foundry Setting

Description

Woodland/Alloy Casting, Inc. is an aluminum foundry known for providing high-quality molds to their customers in industries such as aviation, electrical, defense, and nuclear power. However, as the company has

Woodland/Alloy Casting, Inc. is an aluminum foundry known for providing high-quality molds to their customers in industries such as aviation, electrical, defense, and nuclear power. However, as the company has grown larger during the past three years, they have begun to struggle with the on-time delivery of their orders. Woodland prides itself on their high-grade process that includes core processing, the molding process, cleaning process, and heat-treat process. To create each mold, it has to flow through each part of the system flawlessly. Throughout this process, significant bottlenecks occur that limit the number of molds leaving the system. To combat this issue, this project uses a simulation of the foundry to test how best to schedule their work to optimize the use of their resources. Simulation can be an effective tool when testing for improvements in systems where making changes to the physical system is too expensive. ARENA is a simulation tool that allows for manipulation of resources and process while also allowing both random and selected schedules to be run through the foundry’s production process. By using an ARENA simulation to test different scheduling techniques, the risk of missing production runs is minimized during the experimental period so that many different options can be tested to see how they will affect the production line. In this project, several feasible scheduling techniques are compared in simulation to determine which schedules allow for the highest number of molds to be completed.

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Created

Date Created
  • 2019-05

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A Strategy for Improved Traffic Flow

Description

Commuting is a significant cost in time and in travel expenses for working individuals and a major contributor to emissions in the United States. This project focuses on increasing the

Commuting is a significant cost in time and in travel expenses for working individuals and a major contributor to emissions in the United States. This project focuses on increasing the efficiency of an intersection through the use of "light metering." Light metering involves a series of lights leading up to an intersection forcing cars to stop further away from the final intersection in smaller queues instead of congregating in a large queue before the final intersection. The simulation software package AnyLogic was used to model a simple two-lane intersection with and without light metering. It was found that light metering almost eliminates start-up delay by preventing a long queue to form in front of the modeled intersection. Shorter queue lengths and reduction in the start-up delays prevents cycle failure and significantly reduces the overall delay for the intersection. However, frequent deceleration and acceleration for a few of the cars occurs before each light meter. This solution significantly reduces the traffic density before the intersection and the overall delay but does not appear to be a better emission alternative due to an increase in acceleration. Further research would need to quantify the difference in emissions for this model compared to a standard intersection.

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Created

Date Created
  • 2018-05

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Optimized Line Calling Strategies in Ultimate Frisbee

Description

Ultimate Frisbee or "Ultimate," is a fast growing field sport that is being played competitively at universities across the country. Many mid-tier college teams have the goal of winning as

Ultimate Frisbee or "Ultimate," is a fast growing field sport that is being played competitively at universities across the country. Many mid-tier college teams have the goal of winning as many games as possible, however they also need to grow their program by training and retaining new players. The purpose of this project was to create a prototype statistical tool that maximizes a player line-up's probability of scoring the next point, while having as equal playing time across all experienced and novice players as possible. Game, player, and team data was collected for 25 different games played over the course of 4 tournaments during Fall 2017 and early Spring 2018 using the UltiAnalytics iPad application. "Amount of Top 1/3 Players" was the measure of equal playing time, and "Line Efficiency" and "Line Interaction" represented a line's probability of scoring. After running a logistic regression, Line Efficiency was found to be the more accurate predictor of scoring outcome than Line Interaction. An "Equal PT Measure vs. Line Efficiency" graph was then created and the plot showed what the optimal lines were depending on what the user's preferences were at that point in time. Possible next steps include testing the model and refining it as needed.

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Created

Date Created
  • 2018-05

The Individual Contribution to Cooperative Transport in the ant Novomessor albisetosus

Description

The desert ant, Novomessor albisetosus, is an ideal model system for studying collective transport in ants and self-organized cooperation in natural systems. Small teams collect and stabilize around objects encountered

The desert ant, Novomessor albisetosus, is an ideal model system for studying collective transport in ants and self-organized cooperation in natural systems. Small teams collect and stabilize around objects encountered by these colonies in the field, and the teams carry them in straight paths at a regulated velocity back to nearby nest entrances. The puzzling finding that teams are slower than individuals contrasts other cases of cooperative transport in ants. The statistical distribution of speeds has been found to be consistent with the slowest-ant model, but the key assumption that individual ants consistently vary in speed has not been tested. To test this, information is needed about the natural distribution of individual ant speeds in colonies and whether some ants are intrinsically slow or fast. To investigate the natural, individual-level variation in ants carrying loads, data were collected on single workers carrying fig seeds in arenas separated from other workers. Using three separate, small arenas, the instantaneous speed of each seed-laden worker was recorded when she picked up a fig seed and transported within the arena. Instantaneous speeds were measured by dividing the distance traveled in each frame by how much time had passed.
There were nine ants who transported a fig seed numerous times and there was a clear variation in their average instantaneous speed. Within an ant, slightly varying speeds were found as well, but within-ant speeds were not as varied as speed across ants. These results support the conclusion that there is intrinsic variation in the speed of an individual which supports the slowest-ant model, but this may require further experimentation to test thoroughly. This information aids in the understanding of the natural variation of ants cooperatively carrying larger loads in groups.

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Created

Date Created
  • 2020-12

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Design of Ant-Inspired Stochastic Control Policies for Collective Transport by Robotic Swarms

Description

In this paper, we present an approach to designing decentralized robot control policies that mimic certain microscopic and macroscopic behaviors of ants performing collective transport tasks. In prior work, we

In this paper, we present an approach to designing decentralized robot control policies that mimic certain microscopic and macroscopic behaviors of ants performing collective transport tasks. In prior work, we used a stochastic hybrid system model to characterize the observed team dynamics of ant group retrieval of a rigid load. We have also used macroscopic population dynamic models to design enzyme-inspired stochastic control policies that allocate a robotic swarm around multiple boundaries in a way that is robust to environmental variations. Here, we build on this prior work to synthesize stochastic robot attachment–detachment policies for tasks in which a robotic swarm must achieve non-uniform spatial distributions around multiple loads and transport them at a constant velocity. Three methods are presented for designing robot control policies that replicate the steady-state distributions, transient dynamics, and fluxes between states that we have observed in ant populations during group retrieval. The equilibrium population matching method can be used to achieve a desired transport team composition as quickly as possible; the transient matching method can control the transient population dynamics of the team while driving it to the desired composition; and the rate matching method regulates the rates at which robots join and leave a load during transport. We validate our model predictions in an agent-based simulation, verify that each controller design method produces successful transport of a load at a regulated velocity, and compare the advantages and disadvantages of each method.

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Date Created
  • 2014-12-01

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ANALYSIS UTILIZING EXPECTATIONS OF A FORAGER’S DECISION-MAKING HEURISTIC TO ENSURE AN OPTIMAL CALORIC STATE WITH MULTIPLE PREY

Description

Optimal foraging theory provides a suite of tools that model the best way that an animal will <br/>structure its searching and processing decisions in uncertain environments. It has been <br/>successful

Optimal foraging theory provides a suite of tools that model the best way that an animal will <br/>structure its searching and processing decisions in uncertain environments. It has been <br/>successful characterizing real patterns of animal decision making, thereby providing insights<br/>into why animals behave the way they do. However, it does not speak to how animals make<br/>decisions that tend to be adaptive. Using simulation studies, prior work has shown empirically<br/>that a simple decision-making heuristic tends to produce prey-choice behaviors that, on <br/>average, match the predicted behaviors of optimal foraging theory. That heuristic chooses<br/>to spend time processing an encountered prey item if that prey item's marginal rate of<br/>caloric gain (in calories per unit of processing time) is greater than the forager's<br/>current long-term rate of accumulated caloric gain (in calories per unit of total searching<br/>and processing time). Although this heuristic may seem intuitive, a rigorous mathematical<br/>argument for why it tends to produce the theorized optimal foraging theory behavior has<br/>not been developed. In this thesis, an analytical argument is given for why this<br/>simple decision-making heuristic is expected to realize the optimal performance<br/>predicted by optimal foraging theory. This theoretical guarantee not only provides support<br/>for why such a heuristic might be favored by natural selection, but it also provides<br/>support for why such a heuristic might a reliable tool for decision-making in autonomous<br/>engineered agents moving through theatres of uncertain rewards. Ultimately, this simple<br/>decision-making heuristic may provide a recipe for reinforcement learning in small robots<br/>with little computational capabilities.

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Created

Date Created
  • 2021-05