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Description
Currently, to interact with computer based systems one needs to learn the specific interface language of that system. In most cases, interaction would be much easier if it could be done in natural language. For that, we will need a module which understands natural language and automatically translates it to

Currently, to interact with computer based systems one needs to learn the specific interface language of that system. In most cases, interaction would be much easier if it could be done in natural language. For that, we will need a module which understands natural language and automatically translates it to the interface language of the system. NL2KR (Natural language to knowledge representation) v.1 system is a prototype of such a system. It is a learning based system that learns new meanings of words in terms of lambda-calculus formulas given an initial lexicon of some words and their meanings and a training corpus of sentences with their translations. As a part of this thesis, we take the prototype NL2KR v.1 system and enhance various components of it to make it usable for somewhat substantial and useful interface languages. We revamped the lexicon learning components, Inverse-lambda and Generalization modules, and redesigned the lexicon learning algorithm which uses these components to learn new meanings of words. Similarly, we re-developed an inbuilt parser of the system in Answer Set Programming (ASP) and also integrated external parser with the system. Apart from this, we added some new rich features like various system configurations and memory cache in the learning component of the NL2KR system. These enhancements helped in learning more meanings of the words, boosted performance of the system by reducing the computation time by a factor of 8 and improved the usability of the system. We evaluated the NL2KR system on iRODS domain. iRODS is a rule-oriented data system, which helps in managing large set of computer files using policies. This system provides a Rule-Oriented interface langauge whose syntactic structure is like any procedural programming language (eg. C). However, direct translation of natural language (NL) to this interface language is difficult. So, for automatic translation of NL to this language, we define a simple intermediate Policy Declarative Language (IPDL) to represent the knowledge in the policies, which then can be directly translated to iRODS rules. We develop a corpus of 100 policy statements and manually translate them to IPDL langauge. This corpus is then used for the evaluation of NL2KR system. We performed 10 fold cross validation on the system. Furthermore, using this corpus, we illustrate how different components of our NL2KR system work.
ContributorsKumbhare, Kanchan Ravishankar (Author) / Baral, Chitta (Thesis advisor) / Ye, Jieping (Committee member) / Li, Baoxin (Committee member) / Arizona State University (Publisher)
Created2013
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Description
Photovoltaic (PV) module nameplates typically provide the module's electrical characteristics at standard test conditions (STC). The STC conditions are: irradiance of 1000 W/m2, cell temperature of 25oC and sunlight spectrum at air mass 1.5. However, modules in the field experience a wide range of environmental conditions which affect their electrical

Photovoltaic (PV) module nameplates typically provide the module's electrical characteristics at standard test conditions (STC). The STC conditions are: irradiance of 1000 W/m2, cell temperature of 25oC and sunlight spectrum at air mass 1.5. However, modules in the field experience a wide range of environmental conditions which affect their electrical characteristics and render the nameplate data insufficient in determining a module's overall, actual field performance. To make sound technical and financial decisions, designers and investors need additional performance data to determine the energy produced by modules operating under various field conditions. The angle of incidence (AOI) of sunlight on PV modules is one of the major parameters which dictate the amount of light reaching the solar cells. The experiment was carried out at the Arizona State University- Photovoltaic Reliability Laboratory (ASU-PRL). The data obtained was processed in accordance with the IEC 61853-2 model to obtain relative optical response of the modules (response which does not include the cosine effect). The results were then compared with theoretical models for air-glass interface and also with the empirical model developed by Sandia National Laboratories. The results showed that all modules with glass as the superstrate had identical optical response and were in agreement with both the IEC 61853-2 model and other theoretical and empirical models. The performance degradation of module over years of exposure in the field is dependent upon factors such as environmental conditions, system configuration, etc. Analyzing the degradation of power and other related performance parameters over time will provide vital information regarding possible degradation rates and mechanisms of the modules. An extensive study was conducted by previous ASU-PRL students on approximately 1700 modules which have over 13 years of hot- dry climatic field condition. An analysis of the results obtained in previous ASU-PRL studies show that the major degradation in crystalline silicon modules having glass/polymer construction is encapsulant discoloration (causing short circuit current drop) and solder bond degradation (causing fill factor drop due to series resistance increase). The power degradation for crystalline silicon modules having glass/glass construction was primarily attributed to encapsulant delamination (causing open-circuit voltage drop).
ContributorsVasantha Janakeeraman, Suryanarayana (Author) / Tamizhmani, Govindasamy (Thesis advisor) / Rogers, Bradley (Committee member) / Macia, Narciso (Committee member) / Arizona State University (Publisher)
Created2013
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Description
The object of this study was a 26 year old residential Photovoltaic (PV) monocrystalline silicon (c-Si) power plant, called Solar One, built by developer John F. Long in Phoenix, Arizona (a hot-dry field condition). The task for Arizona State University Photovoltaic Reliability Laboratory (ASU-PRL) graduate students was to evaluate the

The object of this study was a 26 year old residential Photovoltaic (PV) monocrystalline silicon (c-Si) power plant, called Solar One, built by developer John F. Long in Phoenix, Arizona (a hot-dry field condition). The task for Arizona State University Photovoltaic Reliability Laboratory (ASU-PRL) graduate students was to evaluate the power plant through visual inspection, electrical performance, and infrared thermography. The purpose of this evaluation was to measure and understand the extent of degradation to the system along with the identification of the failure modes in this hot-dry climatic condition. This 4000 module bipolar system was originally installed with a 200 kW DC output of PV array (17 degree fixed tilt) and an AC output of 175 kVA. The system was shown to degrade approximately at a rate of 2.3% per year with no apparent potential induced degradation (PID) effect. The power plant is made of two arrays, the north array and the south array. Due to a limited time frame to execute this large project, this work was performed by two masters students (Jonathan Belmont and Kolapo Olakonu) and the test results are presented in two masters theses. This thesis presents the results obtained on the north array and the other thesis presents the results obtained on the south array. The resulting study showed that PV module design, array configuration, vandalism, installation methods and Arizona environmental conditions have had an effect on this system's longevity and reliability. Ultimately, encapsulation browning, higher series resistance (potentially due to solder bond fatigue) and non-cell interconnect ribbon breakages outside the modules were determined to be the primary causes for the power loss.
ContributorsBelmont, Jonathan (Author) / Tamizhmani, Govindasamy (Thesis advisor) / Henderson, Mark (Committee member) / Rogers, Bradley (Committee member) / Arizona State University (Publisher)
Created2013
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Description
We solve the problem of activity verification in the context of sustainability. Activity verification is the process of proving the user assertions pertaining to a certain activity performed by the user. Our motivation lies in incentivizing the user for engaging in sustainable activities like taking public transport or recycling. Such

We solve the problem of activity verification in the context of sustainability. Activity verification is the process of proving the user assertions pertaining to a certain activity performed by the user. Our motivation lies in incentivizing the user for engaging in sustainable activities like taking public transport or recycling. Such incentivization schemes require the system to verify the claim made by the user. The system verifies these claims by analyzing the supporting evidence captured by the user while performing the activity. The proliferation of portable smart-phones in the past few years has provided us with a ubiquitous and relatively cheap platform, having multiple sensors like accelerometer, gyroscope, microphone etc. to capture this evidence data in-situ. In this research, we investigate the supervised and semi-supervised learning techniques for activity verification. Both these techniques make use the data set constructed using the evidence submitted by the user. Supervised learning makes use of annotated evidence data to build a function to predict the class labels of the unlabeled data points. The evidence data captured can be either unimodal or multimodal in nature. We use the accelerometer data as evidence for transportation mode verification and image data as evidence for recycling verification. After training the system, we achieve maximum accuracy of 94% when classifying the transport mode and 81% when detecting recycle activity. In the case of recycle verification, we could improve the classification accuracy by asking the user for more evidence. We present some techniques to ask the user for the next best piece of evidence that maximizes the probability of classification. Using these techniques for detecting recycle activity, the accuracy increases to 93%. The major disadvantage of using supervised models is that it requires extensive annotated training data, which expensive to collect. Due to the limited training data, we look at the graph based inductive semi-supervised learning methods to propagate the labels among the unlabeled samples. In the semi-supervised approach, we represent each instance in the data set as a node in the graph. Since it is a complete graph, edges interconnect these nodes, with each edge having some weight representing the similarity between the points. We propagate the labels in this graph, based on the proximity of the data points to the labeled nodes. We estimate the performance of these algorithms by measuring how close the probability distribution of the data after label propagation is to the probability distribution of the ground truth data. Since labeling has a cost associated with it, in this thesis we propose two algorithms that help us in selecting minimum number of labeled points to propagate the labels accurately. Our proposed algorithm achieves a maximum of 73% increase in performance when compared to the baseline algorithm.
ContributorsDesai, Vaishnav (Author) / Sundaram, Hari (Thesis advisor) / Li, Baoxin (Thesis advisor) / Turaga, Pavan (Committee member) / Arizona State University (Publisher)
Created2013
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Description
Potential induced degradation (PID) due to high system voltages is one of the major degradation mechanisms in photovoltaic (PV) modules, adversely affecting their performance due to the combined effects of the following factors: system voltage, superstrate/glass surface conductivity, encapsulant conductivity, silicon nitride anti-reflection coating property and interface property (glass/encapsulant; encapsulant/cell;

Potential induced degradation (PID) due to high system voltages is one of the major degradation mechanisms in photovoltaic (PV) modules, adversely affecting their performance due to the combined effects of the following factors: system voltage, superstrate/glass surface conductivity, encapsulant conductivity, silicon nitride anti-reflection coating property and interface property (glass/encapsulant; encapsulant/cell; encapsulant/backsheet). Previous studies carried out at ASU's Photovoltaic Reliability Laboratory (ASU-PRL) showed that only negative voltage bias (positive grounded systems) adversely affects the performance of commonly available crystalline silicon modules. In previous studies, the surface conductivity of the glass surface was obtained using either conductive carbon layer extending from the glass surface to the frame or humidity inside an environmental chamber. This thesis investigates the influence of glass surface conductivity disruption on PV modules. In this study, conductive carbon was applied only on the module's glass surface without extending to the frame and the surface conductivity was disrupted (no carbon layer) at 2cm distance from the periphery of frame inner edges. This study was carried out under dry heat at two different temperatures (60 °C and 85 °C) and three different negative bias voltages (-300V, -400V, and -600V). To replicate closeness to the field conditions, half of the selected modules were pre-stressed under damp heat for 1000 hours (DH 1000) and the remaining half under 200 hours of thermal cycling (TC 200). When the surface continuity was disrupted by maintaining a 2 cm gap from the frame to the edge of the conductive layer, as demonstrated in this study, the degradation was found to be absent or negligibly small even after 35 hours of negative bias at elevated temperatures. This preliminary study appears to indicate that the modules could become immune to PID losses if the continuity of the glass surface conductivity is disrupted at the inside boundary of the frame. The surface conductivity of the glass, due to water layer formation in a humid condition, close to the frame could be disrupted just by applying a water repelling (hydrophobic) but high transmittance surface coating (such as Teflon) or modifying the frame/glass edges with water repellent properties.
ContributorsTatapudi, Sai Ravi Vasista (Author) / Tamizhmani, Govindasamy (Thesis advisor) / Srinivasan, Devarajan (Committee member) / Rogers, Bradley (Committee member) / Arizona State University (Publisher)
Created2012
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Description
ABSTRACT As the use of photovoltaic (PV) modules in large power plants continues to increase globally, more studies on degradation, reliability, failure modes, and mechanisms of field aged modules are needed to predict module life expectancy based on accelerated lifetime testing of PV modules. In this work, a 26+ year

ABSTRACT As the use of photovoltaic (PV) modules in large power plants continues to increase globally, more studies on degradation, reliability, failure modes, and mechanisms of field aged modules are needed to predict module life expectancy based on accelerated lifetime testing of PV modules. In this work, a 26+ year old PV power plant in Phoenix, Arizona has been evaluated for performance, reliability, and durability. The PV power plant, called Solar One, is owned and operated by John F. Long's homeowners association. It is a 200 kWdc, standard test conditions (STC) rated power plant comprised of 4000 PV modules or frameless laminates, in 100 panel groups (rated at 175 kWac). The power plant is made of two center-tapped bipolar arrays, the north array and the south array. Due to a limited time frame to execute this large project, this work was performed by two masters students (Jonathan Belmont and Kolapo Olakonu) and the test results are presented in two masters theses. This thesis presents the results obtained on the south array and the other thesis presents the results obtained on the north array. Each of these two arrays is made of four sub arrays, the east sub arrays (positive and negative polarities) and the west sub arrays (positive and negative polarities), making up eight sub arrays. The evaluation and analyses of the power plant included in this thesis consists of: visual inspection, electrical performance measurements, and infrared thermography. A possible presence of potential induced degradation (PID) due to potential difference between ground and strings was also investigated. Some installation practices were also studied and found to contribute to the power loss observed in this investigation. The power output measured in 2011 for all eight sub arrays at STC is approximately 76 kWdc and represents a power loss of 62% (from 200 kW to 76 kW) over 26+ years. The 2011 measured power output for the four south sub arrays at STC is 39 kWdc and represents a power loss of 61% (from 100 kW to 39 kW) over 26+ years. Encapsulation browning and non-cell interconnect ribbon breakages were determined to be the primary causes for the power loss.
ContributorsOlakonu, Kolapo (Author) / Tamizhmani, Govindasamy (Thesis advisor) / Srinivasan, Devarajan (Committee member) / Rogers, Bradley (Committee member) / Arizona State University (Publisher)
Created2012
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Description
This is a two-part thesis: Part 1 of this thesis tests and validates the methodology and mathematical models of the International Electrotechnical Commission (IEC) 61853-2 standard for the measurement of angle of incidence (AOI) effects on photovoltaic modules. Flat-plate photovoltaic modules in the field operate under a wide range of

This is a two-part thesis: Part 1 of this thesis tests and validates the methodology and mathematical models of the International Electrotechnical Commission (IEC) 61853-2 standard for the measurement of angle of incidence (AOI) effects on photovoltaic modules. Flat-plate photovoltaic modules in the field operate under a wide range of environmental conditions. The purpose of IEC 61853-2 is to characterize photovoltaic modules' performance under specific environmental conditions. Part 1 of this report focuses specifically on AOI. To accurately test and validate IEC 61853-2 standard for measuring AOI, meticulous experimental setup and test procedures were followed. Modules of five different photovoltaic technology types with glass superstrates were tested. Test results show practically identical relative light transmission plots for all five test modules. The experimental results were compared to theoretical and empirical models for relative light transmission of air-glass interface. IEC 61853-2 states "for the flat glass superstrate modules, the AOI test does not need to be performed; rather, the data of a flat glass air interface can be used." The results obtained in this thesis validate this statement. This work was performed in collaboration with another Master of Science student (Surynarayana Janakeeraman) and the test results are presented in two masters theses. Part 2 of this thesis is to develop non-intrusive techniques to accurately measure the quantum efficiency (QE) of a single-junction crystalline silicon cell within a commercial module. This thesis will describe in detail all the equipment and conditions necessary to measure QE and discuss the factors which may influence this measurement. The ability to utilize a non-intrusive test to measure quantum efficiency of a cell within a module is extremely beneficial for reliability testing of commercial modules. Detailed methodologies for this innovative test procedure are not widely available in industry because equipment and measurement techniques have not been explored extensively. This paper will provide a literature review describing relevant theories and measurement techniques related to measuring the QE of a cell within a module. The testing methodology and necessary equipment will be described in detail. Results and conclusions provide the overall accuracy of the measurements and discuss the parameters affecting these measurements.
ContributorsKnisely, Brett (Author) / Tamizhmani, Govindasamy (Thesis advisor) / Rogers, Bradley (Committee member) / Macia, Narciso (Committee member) / Arizona State University (Publisher)
Created2013
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Description
New Pastoral journeys through the altered states of the American West. Readers witness dream-fields at harvest time, watch humans become agro-industrial test subjects, and overhear an exchange of letters set in an alternate (?), [more] dystopian present. Fractured, fragmented, leaping, and stitched, the poems use disjuncture, within and/or between poems,

New Pastoral journeys through the altered states of the American West. Readers witness dream-fields at harvest time, watch humans become agro-industrial test subjects, and overhear an exchange of letters set in an alternate (?), [more] dystopian present. Fractured, fragmented, leaping, and stitched, the poems use disjuncture, within and/or between poems, to see with clarity and complexity a landscape that is increasingly all ecotone. In addition to environmental violence, this work explores disclosure and secrecy, intimacy and estrangement, voyeurism, political policing, and, inevitably, the mysteries of making art. Pastoral landscapes have often been compared to patchwork. Now, heavy with guilt, we walk a wounded quilt, searching, with little hope, for bandages.
ContributorsSlinker, Nathan (Author) / Dubie Jr, Norman (Thesis advisor) / Hummer, Terry (Committee member) / Ball, Sara (Committee member) / Arizona State University (Publisher)
Created2014
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Description
Software has a great impact on the energy efficiency of any computing system--it can manage the components of a system efficiently or inefficiently. The impact of software is amplified in the context of a wearable computing system used for activity recognition. The design space this platform opens up is immense

Software has a great impact on the energy efficiency of any computing system--it can manage the components of a system efficiently or inefficiently. The impact of software is amplified in the context of a wearable computing system used for activity recognition. The design space this platform opens up is immense and encompasses sensors, feature calculations, activity classification algorithms, sleep schedules, and transmission protocols. Design choices in each of these areas impact energy use, overall accuracy, and usefulness of the system. This thesis explores methods software can influence the trade-off between energy consumption and system accuracy. In general the more energy a system consumes the more accurate will be. We explore how finding the transitions between human activities is able to reduce the energy consumption of such systems without reducing much accuracy. We introduce the Log-likelihood Ratio Test as a method to detect transitions, and explore how choices of sensor, feature calculations, and parameters concerning time segmentation affect the accuracy of this method. We discovered an approximate 5X increase in energy efficiency could be achieved with only a 5% decrease in accuracy. We also address how a system's sleep mode, in which the processor enters a low-power state and sensors are turned off, affects a wearable computing platform that does activity recognition. We discuss the energy trade-offs in each stage of the activity recognition process. We find that careful analysis of these parameters can result in great increases in energy efficiency if small compromises in overall accuracy can be tolerated. We call this the ``Great Compromise.'' We found a 6X increase in efficiency with a 7% decrease in accuracy. We then consider how wireless transmission of data affects the overall energy efficiency of a wearable computing platform. We find that design decisions such as feature calculations and grouping size have a great impact on the energy consumption of the system because of the amount of data that is stored and transmitted. For example, storing and transmitting vector-based features such as FFT or DCT do not compress the signal and would use more energy than storing and transmitting the raw signal. The effect of grouping size on energy consumption depends on the feature. For scalar features energy consumption is proportional in the inverse of grouping size, so it's reduced as grouping size goes up. For features that depend on the grouping size, such as FFT, energy increases with the logarithm of grouping size, so energy consumption increases slowly as grouping size increases. We find that compressing data through activity classification and transition detection significantly reduces energy consumption and that the energy consumed for the classification overhead is negligible compared to the energy savings from data compression. We provide mathematical models of energy usage and data generation, and test our ideas using a mobile computing platform, the Texas Instruments Chronos watch.
ContributorsBoyd, Jeffrey Michael (Author) / Sundaram, Hari (Thesis advisor) / Li, Baoxin (Thesis advisor) / Shrivastava, Aviral (Committee member) / Turaga, Pavan (Committee member) / Arizona State University (Publisher)
Created2014
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Description
This qualitative study examines the major changes in relationship closeness of married couples when one spouse acquires a vision disability. Turning Points analysis and Retrospective Interview Technique (RIT) were utilized which required participants to plot their relational journey on a graph after the onset of the disability. A sample of

This qualitative study examines the major changes in relationship closeness of married couples when one spouse acquires a vision disability. Turning Points analysis and Retrospective Interview Technique (RIT) were utilized which required participants to plot their relational journey on a graph after the onset of the disability. A sample of 32 participants generating 100 unique turning points and 32 RIT graphs lent in-depth insight into the less explored area of the impact of a visual disability on marital relationships. A constant comparison method employed for the analysis of these turning points revealed six major categories, which include Change in Relational Dynamics, Realization of the Disability, Regaining Normality in Life, Resilience, Reactions to Assistance, and Dealing with the Disability. These turning points differ in terms of their positive or negative impact on the relational closeness between partners. In addition, the 32 individual RIT graphs were also analyzed and were grouped into four categories based on visual similarity, which include Erratic Relational Restoration, Erratic Relational Increase, Consistent Closeness and Gradual Relational Increase. Results provide theoretical contributions to disability and marriage literature. Implications for the application of turning points to the study of post-disability marital relationships are also discussed, and research directions identified.
ContributorsBhagchandani, Bhoomika (Author) / Kassing, Jeffrey W. (Thesis advisor) / Kelley, Douglas L. (Committee member) / Fisher, Carla L. (Committee member) / Li, Baoxin (Committee member) / Arizona State University (Publisher)
Created2014