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(1 - 5 of 5)
- Title
- Collaborative Mobile Robot Surveyors (Fall 2003) IPRO 308: Collaborative Mobile Robot Surveyors IPRO308 Fall2003 Final Presentation
- Creator
- Stein, Sterling Stuart, Cantrell, Case, Collver, Aaron, Reed, Michael, Meyers, Chris, Lau, Sheryl, Yohman, Chance, Roberts, Williams, Stephenson, Garret, Malas, Robert
- Date
- 2003, 2003-12
- Description
-
Examine the need for error correction Develop means for measuring the distance the robot has traveled Create algorithm to dynamically adjust...
Show moreExamine the need for error correction Develop means for measuring the distance the robot has traveled Create algorithm to dynamically adjust the signals sent to the motors to compensate for deviations
Sponsorship: NA
Project Plan for IPRO 308: Collaborative Mobile Robot Surveyors for Fall 2003 semester
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- Title
- GUARANTEED ADAPTIVE MONTE CARLO METHODS FOR ESTIMATING MEANS OF RANDOM VARIABLES
- Creator
- Jiang, Lan
- Date
- 2016, 2016-05
- Description
-
Monte Carlo is a versatile computational method that may be used to approximate the means, μ, of random variables, Y , whose distributions are...
Show moreMonte Carlo is a versatile computational method that may be used to approximate the means, μ, of random variables, Y , whose distributions are not known explicitly. This thesis investigates how to reliably construct fixed width confidence intervals for μ with some prescribed absolute error tolerance, "a, relative error tolerance, "r or some generalized error criterion. To facilitate this, it is assumed that the kurtosis, , of the random variable, Y , does not exceed a user specified bound max. The key idea is to confidently estimate the variance of Y by applying Cantelli’s Inequality. A Berry-Esseen Inequality makes it possible to determine the sample size required to construct such a confidence interval. When relative error is involved, this requires an iterative process. This idea for computing μ = E(Y ) can be used to develop a numerical integration method by writing the integral as μ = E(f(x)) = RRd f(x)⇢(x)dx, where x is a d dimensional random vector with probability density function ⇢. A similar idea is used to develop an algorithm for computing p = E(Y) where Y is a Bernoulli random variable. All of the algorithms have been implemented in the Guaranteed Automatic Integration Library (GAIL).
Ph.D. in Applied Mathematics, May 2016
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- Title
- THE DESIGN AND ANALYSIS OF A MULTI-PERFORMANCE 3D PRINTED CONSTRUCTION UNIT: AN ALGORITHM TO UPGRADE THE STRUCTURAL, ENVIRONMENTAL AND ASSEMBLY PERFORMANCE IN MASONRY UNITS CONSTRUCTION
- Creator
- Kalkatechi, Maryam
- Date
- 2016, 2016-12
- Description
-
This dissertation investigates the design and prototyping process of a new masonry unit. Drawing on the advantages offered by 3D printing...
Show moreThis dissertation investigates the design and prototyping process of a new masonry unit. Drawing on the advantages offered by 3D printing industry, it seeks to improve the unit’s structural efficiency and at the same time experiment with the potential benefits of ABS plastic for its realization. The first step of this process was to formulate a parametric algorithm based on a construction unit that provided different data-sketches. Through a case-by-case analysis, the research process either used these data-sketches as the preliminary step of analysis, or used trial and error to experiment first-hand with 3D printing processes to delineate the scope of their implementation and to account for the design consequences that production techniques brought upon the final product. By such examinations, the aim is to propose a new structural system that forms a new tectonic language and offers constructability solutions for a new wall system. As the most inexpensive and available plastic, using ABS plastic for 3D printed masonry units is a promising endeavor, which all the more necessitates addressing its design challenges. To do so, this research conceived of a 3D printed unit as an arrangement of cells that combined different considerations such as handling the unit, its structural performance and modularity in a uniform, ergonomic and sustainable wall system. The key features of this assembly comprised of a waffle plate that attached the EPS panel to the slab, a sprayed EPS, the ABS plastic unit that had ties as a design element for EPS installation, an interlocking snap-fit joint that vertically fastened the units together, and a custom-designed dovetail joint for horizontal connections. The parametric algorithm modified and redefined individual cells in the corners to realize these connections. The final step of this process entailed a comprehensive comparison of the proposed wall system to alternative wall systems, namely a solid wall system, an ICF wall system, and a cavity wall system for thickness, weight and thermal performance. Using Rescheck software, I compared these wall systems to a base model set in Chicago. Ultimately, this research is a detailed elaboration of a problem-solving process that exploits the capabilities of parametric design beyond its common emphasis on creating new geometries, by means of which the proposed system offers practical solutions to the prevalent challenges in masonry unit construction.
Ph.D. in Architecture, December 2016
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- Title
- COMPREHENSIVE ALWAYS-ON SENSING (CAS) PLATFORM FOR MOBILE CONTEXTUAL AWARENESS
- Creator
- Lautner, Douglas
- Date
- 2018, 2018-05
- Description
-
From conception and for decades, a cell phone was used solely for wireless communication purposes [1]. Recently however, over the past nine...
Show moreFrom conception and for decades, a cell phone was used solely for wireless communication purposes [1]. Recently however, over the past nine years after the Android™ and iOS™ operating systems were released to the market, its definition has changed. With increasing capabilities, importance of data generation, data collection and processing functionalities, a cell phone has evolved into a mobile smart device e.g. smartphone. Smart devices are emerging into new roles such as a portable computing devices [2], sensor hubs [3] and Internet access terminals [4]. As embedded technologies and systems advance, not only smartphones, but all commercial smart devices [5], such as wearables, smartwatches or head mounted displays, extend with these capabilities. Amongst all, the function of contextual sensing is unique on a mobile smart device more than on any other commercial computing platform. Mobile smart devices are carried in close proximity of users, traveling with them throughout a day sensing what the user experiences. Ambient and on-body contexts are shared with the user and hence the sensing data can accurately reflect an individual’s real environment better than any other computing or sensing device. It is likely that most domesticated living beings i.e. humans, pets, livestock, etc. would be associated with a mobile smart device in the future [6]. As the Internet of Things (IoT) wireless capabilities become more cost effective and are connected to more objects [7][8], pervasive deployment can be realized and hence becomes an important information source in contextual sensing. More important, as IoT wireless items can be equipped with various sensing techniques, such as geofencing data [10] or information acquired from any kind of sensor attached to them e.g. temperature, force, strain, pressure, etc. [11][12], the sensing result is comprehensive and highly configurable which is impractical for traditional sensors. The following three challenges are the major causes of limited IoT contextual sensing in smart devices. First, if implementing such sensing capability on a traditional smart device platform, its high current drain becomes intolerable. Second, prevailing smart device platforms are not able to accommodate all IoT contextual sensors and their requirements. Third, there is no solution for the smart device to schedule sensing tasks from different IoT contextual sensors and pre-process sensing raw data at the system’s low layer. To conquer these three problems, and the goal of the thesis is to research, design and implement a novel platform in between a smart device’s system’s hardware layer and operation system layer to accommodate IoT contextual sensors and conduct always-on sensing tasks.
Ph.D. in Computer Science, May 2018
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- Title
- ESTIMATING PM2.5 INFILTRATION FACTORS FROM REAL-TIME OPTICAL PARTICLE COUNTERS DEPLOYED IN CHICAGO HOMES BEFORE AND AFTER MECHANICAL VENTILATION RETROFITS
- Creator
- Wang, Mingyu
- Date
- 2021
- Description
-
PM2.5 are fine inhalable particles that are 2.5 micrometers or smaller in size. Indoor PM2.5 consists of outdoor PM2.5 (ambient PM2.5) that is...
Show morePM2.5 are fine inhalable particles that are 2.5 micrometers or smaller in size. Indoor PM2.5 consists of outdoor PM2.5 (ambient PM2.5) that is infiltrated into the indoor environment and indoor generated PM2.5 (non-ambient PM2.5). As people spend nearly 90% of their lifetimes indoors, with most of that time in their homes, PM2.5 exposure in homes results in severe health effects such as asthma. One strategy increasingly being used to dilute air pollutants generated indoors and improve indoor air quality (IAQ) in homes is the introduction of mechanical ventilation systems. However, mechanical ventilation systems also have the potential to introduce more ambient PM2.5 than relying on infiltration alone, although limited data exist to demonstrate the magnitude of impacts in occupied homes. The objective of this paper is to estimate the infiltration factor (Finf) of PM2.5 before and after installing mechanical ventilation systems in a subset of occupied homes. The data source utilized comes from the Breathe Easy Project, a more than 2-year-long study conducted in 40 existing homes in Chicago, IL aiming to explore the effects of three different types of mechanical ventilation system retrofits on IAQ and asthma. An automated algorithm was developed to remove indoor PM2.5 peaks in time-series data collected from optical particle counters deployed inside and outside of each home. The Finf was estimated using the resulting indoor/outdoor ratio with indoor peaks removed. Before mechanical ventilation retrofits, the weekly median Finf was 0.29 (summer median = 0.41, fall median = 0.26, winter median = 0.29, spring median = 0.30); after mechanical ventilation retrofits, the median Finf was 0.34 (winter median= 0.28, spring median = 0.45, summer median = 0.54, fall median = 0.20). Differences in Finf between pre- and post-intervention periods were not statistically significant (p = 0.23 from Wilcoxon signed rank tests). The median PM2.5 infiltration factor increased ~22% (from 0.27 to 0.33) with the installation of balanced ventilation systems with energy recovery ventilators (ERV), although differences were not statistically significant (Wilcoxon signed rank p = 0.35). The median PM2.5 infiltration factor decreased ~4% (from 0.28 to 0.27) after installing intermittent CFIS systems, which intermittently supply ventilation air through the existing central air handling units and associated filters (which were upgraded to a minimum of MERV 10 in all CFIS homes), although differences were not statistically significant (Wilcoxon signed rank p = 0.24). The median PM2.5 infiltration factor increased ~26% (from 0.35 to 0.44) with the installation of continuous exhaust-only systems, and differences were significant (Wilcoxon signed rank p = 0.04). These results suggest that the filtration mechanisms used on the CFIS and balanced systems were adequate for maintaining similar distributions of Finf values pre- and post-interventions whereas the increased delivery of outdoor air via the building envelope by exhaust-only systems significantly increased Finf following retrofits.
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