Matching Items (409)
Filtering by
- Creators: Ira A. Fulton Schools of Engineering
- Resource Type: Text
Description
The flexural behavior of epoxies was investigated by performing mechanical tests and applying statistical Weibull theory and analytical methods to the results. The effects of loading systems and environmental conditions were also considered. Three kinds of epoxies were studied: Epon E863, PRI 2002, and PR520. In total, 53 three-point-bending (3PB) Epon E863 samples and 26 3PB PR520 were tested immediately after curing, together with 26 four-point-bending (4PB) PRI2002 samples stored at 60°C and 90% Rh for 48 weeks. The Weibull parameters were estimated using both linear regression and the moments method. The statistical character of the Weibull model leads to uncertainty in the evaluated parameters, even for a large number of experiments. This study analyzed the ratio of flexural strength to tensile strength in bulk epoxy resin polymers. An analytical method previously developed by the authors to study the relationship between uniaxial tension/compression stress-strain curves and flexural load-deflection response was used to obtain the ratio. The results show that the Weibull model overpredicted the aforementioned ratio in different load arrangements.
ContributorsYekani Fard, Masoud (Author) / Raji, B. (Author) / Chattopadhyay, Aditi (Author) / Ira A. Fulton Schools of Engineering (Contributor) / School for the Engineering of Matter, Transport and Energy (Contributor)
Created2014-12-01
Description
Identification of early damage in polymer composites is of great importance. We have incorporated cyclobutane-containing cross-linked polymers into an epoxy matrix, studied the effect on thermal and mechanical properties, and, more importantly, demonstrated early damage detection through mechanically induced fluorescence generation. Two cinnamate derivatives, 1,1,1-tris(cinnamoyloxymethyl) ethane (TCE) and poly(vinyl cinnamate) (PVCi), were photoirradiated to produce cyclobutane-containing polymer. The effects on the thermal and mechanical properties with the addition of cyclobutane-containing polymer into epoxy matrix were investigated. The emergence of cracks was detected by fluorescence at a strain level just beyond the yield point of the polymer blends, and the fluorescence intensified with accumulation of strain. Overall, the results show that damage can be detected through fluorescence generation along crack propagation.
ContributorsZou, Jin (Author) / Liu, Yingtao (Author) / Shan, Bohan (Author) / Chattopadhyay, Aditi (Author) / Dai, Lenore (Author) / Ira A. Fulton Schools of Engineering (Contributor) / School for the Engineering of Matter, Transport and Energy (Contributor)
Created2014-09-01
Description
The impact of increasing penetration of converter control-based generators (CCBGs) in a large-scale power system is assessed through a model based small signal stability analysis. Three test bed cases for the years 2010, 2020, and 2022 of the Western Electricity Coordinating Council (WECC) in the United States are used for the analysis. Increasing penetration of wind-based Type 3 and wind-based Type 4 and PV Solar CCBGs is used in the tests. The participation and interaction of CCBGs and synchronous generators in traditional electromechanical interarea modes is analyzed. Two new types of modes dominated by CCBGs are identified. The characteristics of these new modes are described and compared to electromechanical modes in the frequency domain. An examination of the mechanism of the interaction between the CCBG control states and the synchronous generator control states is presented and validated through dynamic simulations. Actual system and forecast load data are used throughout.
ContributorsQuintero, Jaime (Author) / Vittal, Vijay (Author) / Heydt, Gerald (Author) / Zhang, Hui (Author) / Ira A. Fulton Schools of Engineering (Contributor) / School of Electrical, Computer and Energy Engineering (Contributor)
Created2014-09-01
Description
The Physics and Chemistry of Surfaces and Interfaces conference has maintained a focus on the interfacial and surface properties of materials since its initiation in 1974. The conference continues to be a major force in this field, bringing together scientists from a variety of disciplines to focus upon the science of interfaces and surfaces. Here, a historical view of the development of the conference and a discussion of some of the themes that have been focal points for many years are presented.
ContributorsFerry, David (Author) / Ira A. Fulton Schools of Engineering (Contributor) / School of Electrical, Computer and Energy Engineering (Contributor)
Created2013
Description
As autonomous vehicle development rapidly accelerates, it is important to not lose sight of what the worst case scenario is during the drive of an autonomous vehicle. Autonomous vehicles are not perfect, and will not be perfect for the foreseeable future. These vehicles will shift the responsibility of driving to the passenger in front of the wheel, regardless if said passenger is prepared to do so. However, by studying the human reaction to an autonomous vehicle crash, researchers can mitigate the risk to the passengers in an autonomous vehicle. Located on the ASU Polytechnic campus, there is a car simulation lab, or SIM lab, that enables users to create and simulate various driving scenarios using the Drive Safety and HyperDrive software. Using this simulator and the Window of Intervention, the time a driver has to avoid a crash, vital research into human reaction time while in an autonomous environment can be safely performed. Understanding the Window of Intervention is critical to the development of solutions that can accurately and efficiently help a human driver. After first describing the simulator and its operation in depth, a deeper look will be offered into the autonomous vehicle field, followed by an in-depth explanation into the Window of Intervention and how it is studied and an experiment that looks to study both the Window of Intervention and human reactions to certain events. Finally, additional insight from one of the authors of this paper will be given documenting their contributions to the study as a whole and their concerns about using the simulator for further research.
ContributorsSalceda, Rhiannon (Co-author) / Baratti, Alexander (Co-author) / Gaffar, Ashraf (Thesis director) / Gonzalez Sanchez, Javier (Committee member) / Computer Science and Engineering Program (Contributor) / Barrett, The Honors College (Contributor)
Created2020-05
Learning Sparse Representations for Fruit-Fly Gene Expression Pattern Image Annotation and Retrieval
Description
Background
Fruit fly embryogenesis is one of the best understood animal development systems, and the spatiotemporal gene expression dynamics in this process are captured by digital images. Analysis of these high-throughput images will provide novel insights into the functions, interactions, and networks of animal genes governing development. To facilitate comparative analysis, web-based interfaces have been developed to conduct image retrieval based on body part keywords and images. Currently, the keyword annotation of spatiotemporal gene expression patterns is conducted manually. However, this manual practice does not scale with the continuously expanding collection of images. In addition, existing image retrieval systems based on the expression patterns may be made more accurate using keywords.
Results
In this article, we adapt advanced data mining and computer vision techniques to address the key challenges in annotating and retrieving fruit fly gene expression pattern images. To boost the performance of image annotation and retrieval, we propose representations integrating spatial information and sparse features, overcoming the limitations of prior schemes.
Conclusions
We perform systematic experimental studies to evaluate the proposed schemes in comparison with current methods. Experimental results indicate that the integration of spatial information and sparse features lead to consistent performance improvement in image annotation, while for the task of retrieval, sparse features alone yields better results.
Fruit fly embryogenesis is one of the best understood animal development systems, and the spatiotemporal gene expression dynamics in this process are captured by digital images. Analysis of these high-throughput images will provide novel insights into the functions, interactions, and networks of animal genes governing development. To facilitate comparative analysis, web-based interfaces have been developed to conduct image retrieval based on body part keywords and images. Currently, the keyword annotation of spatiotemporal gene expression patterns is conducted manually. However, this manual practice does not scale with the continuously expanding collection of images. In addition, existing image retrieval systems based on the expression patterns may be made more accurate using keywords.
Results
In this article, we adapt advanced data mining and computer vision techniques to address the key challenges in annotating and retrieving fruit fly gene expression pattern images. To boost the performance of image annotation and retrieval, we propose representations integrating spatial information and sparse features, overcoming the limitations of prior schemes.
Conclusions
We perform systematic experimental studies to evaluate the proposed schemes in comparison with current methods. Experimental results indicate that the integration of spatial information and sparse features lead to consistent performance improvement in image annotation, while for the task of retrieval, sparse features alone yields better results.
ContributorsYuan, Lei (Author) / Woodard, Alexander (Author) / Ji, Shuiwang (Author) / Jiang, Yuan (Author) / Zhou, Zhi-Hua (Author) / Kumar, Sudhir (Author) / Ye, Jieping (Author) / Biodesign Institute (Contributor) / Center for Evolution and Medicine (Contributor) / Ira A. Fulton Schools of Engineering (Contributor) / College of Liberal Arts and Sciences (Contributor) / School of Life Sciences (Contributor)
Created2012-05-23
Description
Intelligence is a loosely defined term, but it is a quality that we try to measure in humans, animals, and recently machines. Progress in artificial intelligence is slow, but we have recently made breakthroughs by paying attention to biology and neuroscience. We have not fully explored what biology has to offer us in AI research, and this paper explores aspects of intelligent behavior in nature that machines still struggle with.
ContributorsLahtinen, David (Author) / Gaffar, Ashraf (Thesis director) / Sanchez, Javier Gonzalez (Committee member) / Software Engineering (Contributor) / Barrett, The Honors College (Contributor)
Created2018-05
Description
This reports investigates the general day to day problems faced by small businesses, particularly small vendors, in areas of marketing and general management. Due to lack of man power, internet availability and properly documented data, small business cannot optimize their business. The aim of the research is to address and find a solution to these problems faced, in the form of a tool which utilizes data science. The tool will have features which will aid the vendor to mine their data which they record themselves and find useful information which will benefit their businesses. Since there is lack of properly documented data, One Class Classification using Support Vector Machine (SVM) is used to build a classifying model that can return positive values for audience that is likely to respond to a marketing strategy. Market basket analysis is used to choose products from the inventory in a way that patterns are found amongst them and therefore there is a higher chance of a marketing strategy to attract audience. Also, higher selling products can be used to the vendors' advantage and lesser selling products can be paired with them to have an overall profit to the business. The tool, as envisioned, meets all the requirements that it was set out to have and can be used as a stand alone application to bring the power of data mining into the hands of a small vendor.
ContributorsSharma, Aveesha (Author) / Ghazarian, Arbi (Thesis advisor) / Gaffar, Ashraf (Committee member) / Bansal, Srividya (Committee member) / Arizona State University (Publisher)
Created2016
Description
Despite the various driver assistance systems and electronics, the threat to life of driver, passengers and other people on the road still persists. With the growth in technology, the use of in-vehicle devices with a plethora of buttons and features is increasing resulting in increased distraction. Recently, speech recognition has emerged as an alternative to distraction and has the potential to be beneficial. However, considering the fact that automotive environment is dynamic and noisy in nature, distraction may not arise from the manual interaction, but due to the cognitive load. Hence, speech recognition certainly cannot be a reliable mode of communication.
The thesis is focused on proposing a simultaneous multimodal approach for designing interface between driver and vehicle with a goal to enable the driver to be more attentive to the driving tasks and spend less time fiddling with distractive tasks. By analyzing the human-human multimodal interaction techniques, new modes have been identified and experimented, especially suitable for the automotive context. The identified modes are touch, speech, graphics, voice-tip and text-tip. The multiple modes are intended to work collectively to make the interaction more intuitive and natural. In order to obtain a minimalist user-centered design for the center stack, various design principles such as 80/20 rule, contour bias, affordance, flexibility-usability trade-off etc. have been implemented on the prototypes. The prototype was developed using the Dragon software development kit on android platform for speech recognition.
In the present study, the driver behavior was investigated in an experiment conducted on the DriveSafety driving simulator DS-600s. Twelve volunteers drove the simulator under two conditions: (1) accessing the center stack applications using touch only and (2) accessing the applications using speech with offered text-tip. The duration for which user looked away from the road (eyes-off-road) was measured manually for each scenario. Comparison of results proved that eyes-off-road time is less for the second scenario. The minimalist design with 8-10 icons per screen proved to be effective as all the readings were within the driver distraction recommendations (eyes-off-road time < 2sec per screen) defined by NHTSA.
The thesis is focused on proposing a simultaneous multimodal approach for designing interface between driver and vehicle with a goal to enable the driver to be more attentive to the driving tasks and spend less time fiddling with distractive tasks. By analyzing the human-human multimodal interaction techniques, new modes have been identified and experimented, especially suitable for the automotive context. The identified modes are touch, speech, graphics, voice-tip and text-tip. The multiple modes are intended to work collectively to make the interaction more intuitive and natural. In order to obtain a minimalist user-centered design for the center stack, various design principles such as 80/20 rule, contour bias, affordance, flexibility-usability trade-off etc. have been implemented on the prototypes. The prototype was developed using the Dragon software development kit on android platform for speech recognition.
In the present study, the driver behavior was investigated in an experiment conducted on the DriveSafety driving simulator DS-600s. Twelve volunteers drove the simulator under two conditions: (1) accessing the center stack applications using touch only and (2) accessing the applications using speech with offered text-tip. The duration for which user looked away from the road (eyes-off-road) was measured manually for each scenario. Comparison of results proved that eyes-off-road time is less for the second scenario. The minimalist design with 8-10 icons per screen proved to be effective as all the readings were within the driver distraction recommendations (eyes-off-road time < 2sec per screen) defined by NHTSA.
ContributorsMittal, Richa (Author) / Gaffar, Ashraf (Thesis advisor) / Femiani, John (Committee member) / Gray, Robert (Committee member) / Arizona State University (Publisher)
Created2015
Description
One of the most common errors developers make is to provide incorrect string
identifiers across the HTML5-JavaScript-CSS3 stack. The existing literature shows that a
significant percentage of defects observed in real-world codebases belong to this
category. Existing work focuses on semantic static analysis, while this thesis attempts to
tackle the challenges that can be solved using syntactic static analysis. This thesis
proposes a tool for quickly identifying defects at the time of injection due to
dependencies between HTML5, JavaScript, and CSS3, specifically in syntactic errors in
string identifiers. The proposed solution reduces the delta (time) between defect injection
and defect discovery with the use of a dedicated just-in-time syntactic string identifier
resolution tool. The solution focuses on modeling the nature of syntactic dependencies
across the stack, and providing a tool that helps developers discover such dependencies.
This thesis reports on an empirical study of the tool usage by developers in a realistic
scenario, with the focus on defect injection and defect discovery times of defects of this
nature (syntactic errors in string identifiers) with and without the use of the proposed
tool. Further, the tool was validated against a set of real-world codebases to analyze the
significance of these defects.
identifiers across the HTML5-JavaScript-CSS3 stack. The existing literature shows that a
significant percentage of defects observed in real-world codebases belong to this
category. Existing work focuses on semantic static analysis, while this thesis attempts to
tackle the challenges that can be solved using syntactic static analysis. This thesis
proposes a tool for quickly identifying defects at the time of injection due to
dependencies between HTML5, JavaScript, and CSS3, specifically in syntactic errors in
string identifiers. The proposed solution reduces the delta (time) between defect injection
and defect discovery with the use of a dedicated just-in-time syntactic string identifier
resolution tool. The solution focuses on modeling the nature of syntactic dependencies
across the stack, and providing a tool that helps developers discover such dependencies.
This thesis reports on an empirical study of the tool usage by developers in a realistic
scenario, with the focus on defect injection and defect discovery times of defects of this
nature (syntactic errors in string identifiers) with and without the use of the proposed
tool. Further, the tool was validated against a set of real-world codebases to analyze the
significance of these defects.
ContributorsKalsi, Manit Singh (Author) / Gary, Kevin A (Thesis advisor) / Lindquist, Timothy E (Committee member) / Doupe, Adam (Committee member) / Arizona State University (Publisher)
Created2016