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- Genre: Masters Thesis
- Creators: Davulcu, Hasan
- Creators: Rogers, Bradley
- Member of: ASU Electronic Theses and Dissertations
- Member of: Theses and Dissertations
Description
The increasing popularity of Twitter renders improved trustworthiness and relevance assessment of tweets much more important for search. However, given the limitations on the size of tweets, it is hard to extract measures for ranking from the tweet's content alone. I propose a method of ranking tweets by generating a reputation score for each tweet that is based not just on content, but also additional information from the Twitter ecosystem that consists of users, tweets, and the web pages that tweets link to. This information is obtained by modeling the Twitter ecosystem as a three-layer graph. The reputation score is used to power two novel methods of ranking tweets by propagating the reputation over an agreement graph based on tweets' content similarity. Additionally, I show how the agreement graph helps counter tweet spam. An evaluation of my method on 16~million tweets from the TREC 2011 Microblog Dataset shows that it doubles the precision over baseline Twitter Search and achieves higher precision than current state of the art method. I present a detailed internal empirical evaluation of RAProp in comparison to several alternative approaches proposed by me, as well as external evaluation in comparison to the current state of the art method.
ContributorsRavikumar, Srijith (Author) / Kambhampati, Subbarao (Thesis advisor) / Davulcu, Hasan (Committee member) / Liu, Huan (Committee member) / Arizona State University (Publisher)
Created2013
Description
Continuous Delivery, as one of the youngest and most popular member of agile model family, has become a popular concept and method in software development industry recently. Instead of the traditional software development method, which requirements and solutions must be fixed before starting software developing, it promotes adaptive planning, evolutionary development and delivery, and encourages rapid and flexible response to change. However, several problems prevent Continuous Delivery to be introduced into education world. Taking into the consideration of the barriers, we propose a new Cloud based Continuous Delivery Software Developing System. This system is designed to fully utilize the whole life circle of software developing according to Continuous Delivery concepts in a virtualized environment in Vlab platform.
ContributorsDeng, Yuli (Author) / Huang, Dijiang (Thesis advisor) / Davulcu, Hasan (Committee member) / Chen, Yinong (Committee member) / Arizona State University (Publisher)
Created2013
Description
Our research focuses on finding answers through decentralized search, for complex, imprecise queries (such as "Which is the best hair salon nearby?") in situations where there is a spatiotemporal constraint (say answer needs to be found within 15 minutes) associated with the query. In general, human networks are good in answering imprecise queries. We try to use the social network of a person to answer his query. Our research aims at designing a framework that exploits the user's social network in order to maximize the answers for a given query. Exploiting an user's social network has several challenges. The major challenge is that the user's immediate social circle may not possess the answer for the given query, and hence the framework designed needs to carry out the query diffusion process across the network. The next challenge involves in finding the right set of seeds to pass the query to in the user's social circle. One other challenge is to incentivize people in the social network to respond to the query and thereby maximize the quality and quantity of replies. Our proposed framework is a mobile application where an individual can either respond to the query or forward it to his friends. We simulated the query diffusion process in three types of graphs: Small World, Random and Preferential Attachment. Given a type of network and a particular query, we carried out the query diffusion by selecting seeds based on attributes of the seed. The main attributes are Topic relevance, Replying or Forwarding probability and Time to Respond. We found that there is a considerable increase in the number of replies attained, even without saturating the user's network, if we adopt an optimal seed selection process. We found the output of the optimal algorithm to be satisfactory as the number of replies received at the interrogator's end was close to three times the number of neighbors an interrogator has. We addressed the challenge of incentivizing people to respond by associating a particular amount of points for each query asked, and awarding the same to people involved in answering the query. Thus, we aim to design a mobile application based on our proposed framework so that it helps in maximizing the replies for the interrogator's query by diffusing the query across his/her social network.
ContributorsSwaminathan, Neelakantan (Author) / Sundaram, Hari (Thesis advisor) / Davulcu, Hasan (Thesis advisor) / Turaga, Pavan (Committee member) / Arizona State University (Publisher)
Created2013
Description
With the advent of social media (like Twitter, Facebook etc.,) people are easily sharing their opinions, sentiments and enforcing their ideologies on others like never before. Even people who are otherwise socially inactive would like to share their thoughts on current affairs by tweeting and sharing news feeds with their friends and acquaintances. In this thesis study, we chose Twitter as our main data platform to analyze shifts and movements of 27 political organizations in Indonesia. So far, we have collected over 30 million tweets and 150,000 news articles from RSS feeds of the corresponding organizations for our analysis. For Twitter data extraction, we developed a multi-threaded application which seamlessly extracts, cleans and stores millions of tweets matching our keywords from Twitter Streaming API. For keyword extraction, we used topics and perspectives which were extracted using n-grams techniques and later approved by our social scientists. After the data is extracted, we aggregate the tweet contents that belong to every user on a weekly basis. Finally, we applied linear and logistic regression using SLEP, an open source sparse learning package to compute weekly score for users and mapping them to one of the 27 organizations on a radical or counter radical scale. Since, we are mapping users to organizations on a weekly basis, we are able to track user's behavior and important new events that triggered shifts among users between organizations. This thesis study can further be extended to identify topics and organization specific influential users and new users from various social media platforms like Facebook, YouTube etc. can easily be mapped to existing organizations on a radical or counter-radical scale.
ContributorsPoornachandran, Sathishkumar (Author) / Davulcu, Hasan (Thesis advisor) / Sen, Arunabha (Committee member) / Woodward, Mark (Committee member) / Arizona State University (Publisher)
Created2013
Description
Smoke entering a flight deck cabin has been an issue for commercial aircraft for many years. The issue for a flight crew is how to mitigate the smoke so that they can safely fly the aircraft. For this thesis, the feasibility of having a Negative Pressure System that utilizes the cabin altitude pressure and outside altitude pressure to remove smoke from a flight deck was studied. Existing procedures for flight crews call for a descent down to a safe level for depressurizing the aircraft before taking further action. This process takes crucial time that is critical to the flight crew's ability to keep aware of the situation. This process involves a flight crews coordination and fast thinking to manually take control of the aircraft; which has become increasing more difficult due to the advancements in aircraft automation. Unfortunately this is the only accepted procedure that is used by a flight crew. Other products merely displace the smoke. This displacement is after the time it takes for the flight crew to set up the smoke displacement unit with no guarantee that a flight crew will be able to see or use all of the aircraft's controls. The Negative Pressure System will work automatically and not only use similar components already found on the aircraft, but work in conjunction with the smoke detection system and pressurization system so smoke removal can begin without having to descend down to a lower altitude. In order for this system to work correctly many factors must be taken into consideration. The size of a flight deck varies from aircraft to aircraft, therefore the ability for the system to efficiently remove smoke from an aircraft is taken into consideration. For the system to be feasible on an aircraft the cost and weight must be taken into consideration as the added fuel consumption due to weight of the system may be the limiting factor for installing such a system on commercial aircraft.
ContributorsDavies, Russell (Author) / Rogers, Bradley (Thesis advisor) / Palmgren, Dale (Committee member) / Rajadas, John (Committee member) / Arizona State University (Publisher)
Created2013
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 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
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 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
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; 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
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 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
Description
A semiconductor supply chain modeling and simulation platform using Linear Program (LP) optimization and parallel Discrete Event System Specification (DEVS) process models has been developed in a joint effort by ASU and Intel Corporation. A Knowledge Interchange Broker (KIBDEVS/LP) was developed to broker information synchronously between the DEVS and LP models. Recently a single-echelon heuristic Inventory Strategy Module (ISM) was added to correct for forecast bias in customer demand data using different smoothing techniques. The optimization model could then use information provided by the forecast model to make better decisions for the process model. The composition of ISM with LP and DEVS models resulted in the first realization of what is now called the Optimization Simulation Forecast (OSF) platform. It could handle a single echelon supply chain system consisting of single hubs and single products In this thesis, this single-echelon simulation platform is extended to handle multiple echelons with multiple inventory elements handling multiple products. The main aspect for the multi-echelon OSF platform was to extend the KIBDEVS/LP such that ISM interactions with the LP and DEVS models could also be supported. To achieve this, a new, scalable XML schema for the KIB has been developed. The XML schema has also resulted in strengthening the KIB execution engine design. A sequential scheme controls the executions of the DEVS-Suite simulator, CPLEX optimizer, and ISM engine. To use the ISM for multiple echelons, it is extended to compute forecast customer demands and safety stocks over multiple hubs and products. Basic examples for semiconductor manufacturing spanning single and two echelon supply chain systems have been developed and analyzed. Experiments using perfect data were conducted to show the correctness of the OSF platform design and implementation. Simple, but realistic experiments have also been conducted. They highlight the kinds of supply chain dynamics that can be evaluated using discrete event process simulation, linear programming optimization, and heuristics forecasting models.
ContributorsSmith, James Melkon (Author) / Sarjoughian, Hessam S. (Thesis advisor) / Davulcu, Hasan (Committee member) / Fainekos, Georgios (Committee member) / Arizona State University (Publisher)
Created2012