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Description
The ability to design high performance buildings has acquired great importance in recent years due to numerous federal, societal and environmental initiatives. However, this endeavor is much more demanding in terms of designer expertise and time. It requires a whole new level of synergy between automated performance prediction with the human capabilities to perceive, evaluate and ultimately select a suitable solution. While performance prediction can be highly automated through the use of computers, performance evaluation cannot, unless it is with respect to a single criterion. The need to address multi-criteria requirements makes it more valuable for a designer to know the "latitude" or "degrees of freedom" he has in changing certain design variables while achieving preset criteria such as energy performance, life cycle cost, environmental impacts etc. This requirement can be met by a decision support framework based on near-optimal "satisficing" as opposed to purely optimal decision making techniques. Currently, such a comprehensive design framework is lacking, which is the basis for undertaking this research. The primary objective of this research is to facilitate a complementary relationship between designers and computers for Multi-Criterion Decision Making (MCDM) during high performance building design. It is based on the application of Monte Carlo approaches to create a database of solutions using deterministic whole building energy simulations, along with data mining methods to rank variable importance and reduce the multi-dimensionality of the problem. A novel interactive visualization approach is then proposed which uses regression based models to create dynamic interplays of how varying these important variables affect the multiple criteria, while providing a visual range or band of variation of the different design parameters. The MCDM process has been incorporated into an alternative methodology for high performance building design referred to as Visual Analytics based Decision Support Methodology [VADSM]. VADSM is envisioned to be most useful during the conceptual and early design performance modeling stages by providing a set of potential solutions that can be analyzed further for final design selection. The proposed methodology can be used for new building design synthesis as well as evaluation of retrofits and operational deficiencies in existing buildings.
ContributorsDutta, Ranojoy (Author) / Reddy, T Agami (Thesis advisor) / Runger, George C. (Committee member) / Addison, Marlin S. (Committee member) / Arizona State University (Publisher)
Created2013
Description
Skyline queries are a well-established technique used in multi criteria decision applications. There is a recent interest among the research community to efficiently compute skylines but the problem of presenting the skyline that takes into account the preferences of the user is still open. Each user has varying interests towards each attribute and hence "one size fits all" methodology might not satisfy all the users. True user satisfaction can be obtained only when the skyline is tailored specifically for each user based on his preferences.
This research investigates the problem of preference aware skyline processing which consists of inferring the preferences of users and computing a skyline specific to that user, taking into account his preferences. This research proposes a model that transforms the data from a given space to a user preferential space where each attribute represents the preference of the user. This study proposes two techniques "Preferential Skyline Processing" and "Latent Skyline Processing" to efficiently compute preference aware skylines in the user preferential space. Finally, through extensive experiments and performance analysis the correctness of the recommendations and the algorithm's ability to outperform the naïve ones is confirmed.
This research investigates the problem of preference aware skyline processing which consists of inferring the preferences of users and computing a skyline specific to that user, taking into account his preferences. This research proposes a model that transforms the data from a given space to a user preferential space where each attribute represents the preference of the user. This study proposes two techniques "Preferential Skyline Processing" and "Latent Skyline Processing" to efficiently compute preference aware skylines in the user preferential space. Finally, through extensive experiments and performance analysis the correctness of the recommendations and the algorithm's ability to outperform the naïve ones is confirmed.
ContributorsRathinavelu, Sriram (Author) / Candan, Kasim Selcuk (Thesis advisor) / Davulcu, Hasan (Committee member) / Sarwat, Mohamed (Committee member) / Arizona State University (Publisher)
Created2014
Efficient processing of skyline queries on static data sources, data streams and incomplete datasets
Description
Skyline queries extract interesting points that are non-dominated and help paint the bigger picture of the data in question. They are valuable in many multi-criteria decision applications and are becoming a staple of decision support systems.
An assumption commonly made by many skyline algorithms is that a skyline query is applied to a single static data source or data stream. Unfortunately, this assumption does not hold in many applications in which a skyline query may involve attributes belonging to multiple data sources and requires a join operation to be performed before the skyline can be produced. Recently, various skyline-join algorithms have been proposed to address this problem in the context of static data sources. However, these algorithms suffer from several drawbacks: they often need to scan the data sources exhaustively to obtain the skyline-join results; moreover, the pruning techniques employed to eliminate tuples are largely based on expensive tuple-to-tuple comparisons. On the other hand, most data stream techniques focus on single stream skyline queries, thus rendering them unsuitable for skyline-join queries.
Another assumption typically made by most of the earlier skyline algorithms is that the data is complete and all skyline attribute values are available. Due to this constraint, these algorithms cannot be applied to incomplete data sources in which some of the attribute values are missing and are represented by NULL values. There exists a definition of dominance for incomplete data, but this leads to undesirable consequences such as non-transitive and cyclic dominance relations both of which are detrimental to skyline processing.
Based on the aforementioned observations, the main goal of the research described in this dissertation is the design and development of a framework of skyline operators that effectively handles three distinct types of skyline queries: 1) skyline-join queries on static data sources, 2) skyline-window-join queries over data streams, and 3) strata-skyline queries on incomplete datasets. This dissertation presents the unique challenges posed by these skyline queries and addresses the shortcomings of current skyline techniques by proposing efficient methods to tackle the added overhead in processing skyline queries on static data sources, data streams, and incomplete datasets.
An assumption commonly made by many skyline algorithms is that a skyline query is applied to a single static data source or data stream. Unfortunately, this assumption does not hold in many applications in which a skyline query may involve attributes belonging to multiple data sources and requires a join operation to be performed before the skyline can be produced. Recently, various skyline-join algorithms have been proposed to address this problem in the context of static data sources. However, these algorithms suffer from several drawbacks: they often need to scan the data sources exhaustively to obtain the skyline-join results; moreover, the pruning techniques employed to eliminate tuples are largely based on expensive tuple-to-tuple comparisons. On the other hand, most data stream techniques focus on single stream skyline queries, thus rendering them unsuitable for skyline-join queries.
Another assumption typically made by most of the earlier skyline algorithms is that the data is complete and all skyline attribute values are available. Due to this constraint, these algorithms cannot be applied to incomplete data sources in which some of the attribute values are missing and are represented by NULL values. There exists a definition of dominance for incomplete data, but this leads to undesirable consequences such as non-transitive and cyclic dominance relations both of which are detrimental to skyline processing.
Based on the aforementioned observations, the main goal of the research described in this dissertation is the design and development of a framework of skyline operators that effectively handles three distinct types of skyline queries: 1) skyline-join queries on static data sources, 2) skyline-window-join queries over data streams, and 3) strata-skyline queries on incomplete datasets. This dissertation presents the unique challenges posed by these skyline queries and addresses the shortcomings of current skyline techniques by proposing efficient methods to tackle the added overhead in processing skyline queries on static data sources, data streams, and incomplete datasets.
ContributorsNagendra, Mithila (Author) / Candan, Kasim Selcuk (Thesis advisor) / Chen, Yi (Committee member) / Davulcu, Hasan (Committee member) / Silva, Yasin N. (Committee member) / Sundaram, Hari (Committee member) / Arizona State University (Publisher)
Created2014
Description
Sinaloa, a coastal state in the northwest of Mexico, is known for irrigated conventional agriculture, and is considered one of the greatest successes of the Green Revolution. With the neoliberal reforms of the 1990s, Sinaloa farmers shifted out of conventional wheat, soy, cotton, and other commodities and into white maize, a major food staple in Mexico that is traditionally produced by millions of small-scale farmers. Sinaloa is now a major contributor to the national food supply, producing 26% of total domestic white maize production. Research on Sinaloa's maize has focused on economic and agronomic components. Little attention, however, has been given to the environmental sustainability of Sinaloa's expansion in maize. With uniquely biodiverse coastal and terrestrial ecosystems that support economic activities such as fishing and tourism, the environmental consequences of agriculture in Sinaloa are important to monitor. Agricultural sustainability assessments have largely focused on alternative agricultural approaches, or espouse alternative philosophies that are biased against conventional production. Conventional agriculture, however, provides a significant portion of the world's calories. In addition, incentives such as federal subsidies and other institutions complicate transitions to alternative modes of production. To meet the agricultural sustainability goals of food production and environmental stewardship, we must put conventional agriculture on a more sustainable path. One step toward achieving this is structuring agricultural sustainability assessments around achievable goals that encourage continual adaptations toward sustainability. I attempted this in my thesis by assessing conventional maize production in Sinaloa at the regional/state scale using network analysis and incorporating stakeholder values through a multicriteria decision analysis approach. The analysis showed that the overall sustainability of Sinaloa maize production is far from an ideal state. I made recommendations on how to improve the sustainability of maize production, and how to better monitor the sustainability of agriculture in Sinaloa.
ContributorsBausch, Julia Christine (Author) / Eakin, Hallie (Thesis advisor) / Bojórquez-Tapia, Luis (Committee member) / Childers, Daniel L. (Committee member) / Arizona State University (Publisher)
Created2011
Description
One of the key infrastructures of any community or facility is the energy system which consists of utility power plants, distributed generation technologies, and building heating and cooling systems. In general, there are two dimensions to “sustainability” as it applies to an engineered system. It needs to be designed, operated, and managed such that its environmental impacts and costs are minimal (energy efficient design and operation), and also be designed and configured in a way that it is resilient in confronting disruptions posed by natural, manmade, or random events. In this regard, development of quantitative sustainability metrics in support of decision-making relevant to design, future growth planning, and day-to-day operation of such systems would be of great value. In this study, a pragmatic performance-based sustainability assessment framework and quantitative indices are developed towards this end whereby sustainability goals and concepts can be translated and integrated into engineering practices.
New quantitative sustainability indices are proposed to capture the energy system environmental impacts, economic performance, and resilience attributes, characterized by normalized environmental/health externalities, energy costs, and penalty costs respectively. A comprehensive Life Cycle Assessment is proposed which includes externalities due to emissions from different supply and demand-side energy systems specific to the regional power generation energy portfolio mix. An approach based on external costs, i.e. the monetized health and environmental impacts, was used to quantify adverse consequences associated with different energy system components.
Further, this thesis also proposes a new performance-based method for characterizing and assessing resilience of multi-functional demand-side engineered systems. Through modeling of system response to potential internal and external failures during different operational temporal periods reflective of diurnal variation in loads and services, the proposed methodology quantifies resilience of the system based on imposed penalty costs to the system stakeholders due to undelivered or interrupted services and/or non-optimal system performance.
A conceptual diagram called “Sustainability Compass” is also proposed which facilitates communicating the assessment results and allow better decision-analysis through illustration of different system attributes and trade-offs between different alternatives. The proposed methodologies have been illustrated using end-use monitored data for whole year operation of a university campus energy system.
New quantitative sustainability indices are proposed to capture the energy system environmental impacts, economic performance, and resilience attributes, characterized by normalized environmental/health externalities, energy costs, and penalty costs respectively. A comprehensive Life Cycle Assessment is proposed which includes externalities due to emissions from different supply and demand-side energy systems specific to the regional power generation energy portfolio mix. An approach based on external costs, i.e. the monetized health and environmental impacts, was used to quantify adverse consequences associated with different energy system components.
Further, this thesis also proposes a new performance-based method for characterizing and assessing resilience of multi-functional demand-side engineered systems. Through modeling of system response to potential internal and external failures during different operational temporal periods reflective of diurnal variation in loads and services, the proposed methodology quantifies resilience of the system based on imposed penalty costs to the system stakeholders due to undelivered or interrupted services and/or non-optimal system performance.
A conceptual diagram called “Sustainability Compass” is also proposed which facilitates communicating the assessment results and allow better decision-analysis through illustration of different system attributes and trade-offs between different alternatives. The proposed methodologies have been illustrated using end-use monitored data for whole year operation of a university campus energy system.
ContributorsMoslehi, Salim (Author) / Reddy, T. Agami (Thesis advisor) / Lackner, Klaus S (Committee member) / Parrish, Kristen (Committee member) / Pendyala, Ram M. (Committee member) / Phelan, Patrick (Committee member) / Arizona State University (Publisher)
Created2018
Description
How do you convey what’s interesting and important to you as an artist in a digital world of constantly shifting attentions? For many young creatives, the answer is original characters, or OCs. An OC is a character that an artist creates for personal enjoyment, whether based on an already existing story or world, or completely from their own imagination.
As creations made for purely personal interests, OCs are an excellent elevator pitch to talk one creative to another, opening up opportunities for connection in a world where communication is at our fingertips but personal connection is increasingly harder to make. OCs encourage meaningful interaction by offering themselves as muses, avatars, and story pieces, and so much more, where artists can have their characters interact with other creatives through many different avenues such as art-making, table top games, or word of mouth.
In this thesis, I explore the worlds and aesthetics of many creators and their original characters through qualitative research and collaborative art-making. I begin with a short survey of my creative peers, asking general questions about their characters and thoughts on OCs, then move to sketching characters from various creators. I focus my research to a group of seven core creators and their characters, whom I interview and work closely with in order to create a series of seven final paintings of their original characters.
As creations made for purely personal interests, OCs are an excellent elevator pitch to talk one creative to another, opening up opportunities for connection in a world where communication is at our fingertips but personal connection is increasingly harder to make. OCs encourage meaningful interaction by offering themselves as muses, avatars, and story pieces, and so much more, where artists can have their characters interact with other creatives through many different avenues such as art-making, table top games, or word of mouth.
In this thesis, I explore the worlds and aesthetics of many creators and their original characters through qualitative research and collaborative art-making. I begin with a short survey of my creative peers, asking general questions about their characters and thoughts on OCs, then move to sketching characters from various creators. I focus my research to a group of seven core creators and their characters, whom I interview and work closely with in order to create a series of seven final paintings of their original characters.
ContributorsCote, Jacqueline (Author) / Button, Melissa M (Thesis director) / Dove-Viebahn, Aviva (Committee member) / School of Art (Contributor) / Barrett, The Honors College (Contributor)
Created2020-05
Description
In the past ten years, the United States’ sound recording industries have experienced significant decreases in employment opportunities for aspiring audio engineers from economic imbalances in the music industry’s digital streaming era and reductions in government funding for career and technical education (CTE). The Recording Industry Association of America reports promises of music industry sustainability based on increasing annual revenues in paid streaming services and artists’ high creative demand. The rate of new audio engineer entries in the sound recording subsection of the music industry is not viable to support streaming artists’ high demand to engineer new music recordings. Offering CTE programs in secondary education is rare for aspiring engineers with insufficient accessibility to pursue a post-secondary or vocational education because of financial and academic limitations. These aspiring engineers seek alternatives for receiving an informal education in audio engineering on the Internet using video sharing services like YouTube to search for tutorials and improve their engineering skills. The shortage of accessible educational materials on the Internet restricts engineers from advancing their own audio engineering education, reducing opportunities to enter a desperate job market in need of independent, home studio-based engineers. Content creators on YouTube take advantage of this situation and commercialize their own video tutorial series for free and selling paid subscriptions to exclusive content. This is misleading for newer engineers because these tutorials omit important understandings of fundamental engineering concepts. Instead, content creators teach inflexible engineering methodologies that are mostly beneficial to their own way of thinking. Content creators do not often assess the incompatibility of teaching their own methodologies to potential entrants in a profession that demands critical thinking skills requiring applied fundamental audio engineering concepts and techniques. This project analyzes potential solutions to resolve the deficiencies in online audio engineering education and experiments with structuring simple, deliverable, accessible educational content and materials to new entries in audio engineering. Designing clear, easy to follow material to these new entries in audio engineering is essential for developing a strong understanding for the application of fundamental concepts in future engineers’ careers. Approaches to creating and designing educational content requires translating complex engineering concepts through simplified mediums that reduce limitations in learning for future audio engineers.
ContributorsBurns, Triston Connor (Author) / Tobias, Evan (Thesis director) / Libman, Jeff (Committee member) / Department of Information Systems (Contributor) / Barrett, The Honors College (Contributor)
Created2020-05
Description
There has been a recent push for queer fiction, especially in the young adult genre, whose focus is gay and lesbian relationships. This growth is much needed in terms of visibility and the furthering of acceptance, but there are still subjects within the LGBTQ+ community that need to be addressed, including bisexual, asexual, and non-binary erasure. There are many people who claim that these identities do not exist, are labels used as a stepping stone on one's journey to discovering that they are homosexual, or are invented excuses for overtly promiscuous or prudish behavior. The existence of negative stereotypes, particularly those of non-binary individuals, is largely due to a lack of visibility and respectful representation within media and popular culture. However, there is still a dearth of non-binary content in popular literature outside of young adult fiction. Can You See Me? aims to fill the gap in bisexual, asexual, and non-binary representation in adult literature. Each of the four stories that make up this collection deals with an aspect of gender and/or sexuality that has been erased, ignored, or denied visibility in American popular culture. The first story, "We'll Grow Lemon Trees," examines bisexual erasure through the lens of sociolinguistics. A bisexual Romanian woman emigrates to Los Angeles in 1989 and must navigate a new culture, learn new languages, and try to move on from her past life under a dictatorship where speaking up could mean imprisonment or death. The second story "Up, Down, All Around," is about a young genderqueer child and their parents dealing with microaggressions, examining gender norms, and exploring personal identity through imaginary scenarios, each involving an encounter with an unknown entity and a colander. The third story, "Aces High," follows two asexual characters from the day they're born to when they are 28 years old, as they find themselves in pop culture. The two endure identity crises, gender discrimination, erasure, individual obsessions, and prejudice as they learn to accept themselves and embrace who they are. In the fourth and final story, "Mile Marker 72," a gay Mexican man must hide in plain sight as he deals with the death of his partner and coming out to his best friend, whose brother is his partner's murderer.
ContributorsOchser, Jordyn M. (Author) / Bell, Matt (Thesis director) / Free, Melissa (Committee member) / Department of English (Contributor) / Barrett, The Honors College (Contributor)
Created2018-05
Description
Pandora is a play exploring our relationship with gendered technology through the lens of artificial intelligence. Can women be subjective under patriarchy? Do robots who look like women have subjectivity? Hoping to create a better version of ourselves, The Engineer must navigate the loss of her creation, and Pandora must navigate their new world. The original premiere run was March 27-28, 2018, original cast: Caitlin Andelora, Rikki Tremblay, and Michael Tristano Jr.
ContributorsToye, Abigail Elizabeth (Author) / Linde, Jennifer (Thesis director) / Abele, Kelsey (Committee member) / Department of Information Systems (Contributor) / Economics Program in CLAS (Contributor) / Barrett, The Honors College (Contributor)
Created2018-05
Description
After freelancing on my own for the past year and a half, I have realized that one of the biggest obstacles to college entrepreneurs is a fear or apprehension to sales. As a computer science major trying to sell my services, I discovered very quickly that I had not been prepared for the difficulty of learning sales. Sales get a bad rap and very often is the last thing that young entrepreneurs want to try, but the reality is that sales is oxygen to a company and a required skill for an entrepreneur. Due to this, I compiled all of my knowledge into an e-book for young entrepreneurs starting out to learn how to open up a conversation with a prospect all the way to closing them on the phone. Instead of starting from scratch like I did, college entrepreneurs can learn the bare basics of selling their own services, even if they are terrified of sales and what it entails. In this e-book, there are tips that I have learned to deal with my anxiety about sales such as taking the pressure off of yourself and prioritizing listening more than pitching. Instead of trying to teach sales expecting people to be natural sales people, this e-book takes the approach of helping entrepreneurs that are terrified of sales and show them how they can cope with this fear and still close a client. In the future, I hope young entrepreneurs will have access to more resources that handle this fear and make it much easier for them to learn it by themselves. This e-book is the first step.
ContributorsMead, Kevin Tyler (Author) / Sebold, Brent (Thesis director) / Kruse, Gabriel (Committee member) / Computer Science and Engineering Program (Contributor) / Barrett, The Honors College (Contributor)
Created2018-05