Matching Items (505)
Filtering by
- All Subjects: Guitar music
Description
Laboratory automation systems have seen a lot of technological advances in recent times. As a result, the software that is written for them are becoming increasingly sophisticated. Existing software architectures and standards are targeted to a wider domain of software development and need to be customized in order to use them for developing software for laboratory automation systems. This thesis proposes an architecture that is based on existing software architectural paradigms and is specifically tailored to developing software for a laboratory automation system. The architecture is based on fairly autonomous software components that can be distributed across multiple computers. The components in the architecture make use of asynchronous communication methodologies that are facilitated by passing messages between one another. The architecture can be used to develop software that is distributed, responsive and thread-safe. The thesis also proposes a framework that has been developed to implement the ideas proposed by the architecture. The framework is used to develop software that is scalable, distributed, responsive and thread-safe. The framework currently has components to control very commonly used laboratory automation devices such as mechanical stages, cameras, and also to do common laboratory automation functionalities such as imaging.
ContributorsKuppuswamy, Venkataramanan (Author) / Meldrum, Deirdre (Thesis advisor) / Collofello, James (Thesis advisor) / Sarjoughian, Hessam S. (Committee member) / Johnson, Roger (Committee member) / Arizona State University (Publisher)
Created2012
ContributorsDaval, Charles (Performer) / ASU Library. Music Library (Publisher)
Created2018-03-26
DescriptionThe purpose of this project is to explore the influence of folk music in guitar compositions by Manuel Ponce from 1923 to 1932. It focuses on his Tres canciones populares mexicanas and Tropico and Rumba.
ContributorsGarcia Santos, Arnoldo (Author) / Koonce, Frank (Thesis advisor) / Rogers, Rodney (Committee member) / Rotaru, Catalin (Committee member) / Arizona State University (Publisher)
Created2014
Description
The wood-framing trade has not sufficiently been investigated to understand the work task sequencing and coordination among crew members. A new mental framework for a performing crew was developed and tested through four case studies. This framework ensured similar team performance as the one provided by task micro-scheduling in planning software. It also allowed evaluation of the effect of individual coordination within the crew on the crew's productivity. Using design information, a list of micro-activities/tasks and their predecessors was automatically generated for each piece of lumber in the four wood frames. The task precedence was generated by applying elementary geometrical and technological reasoning to each frame. Then, the duration of each task was determined based on observations from videotaped activities. Primavera's (P6) resource leveling rules were used to calculate the sequencing of tasks and the minimum duration of the whole activity for various crew sizes. The results showed quick convergence towards the minimum production time and allowed to use information from Building Information Models (BIM) to automatically establish the optimal crew sizes for frames. Late Start (LS) leveling priority rule gave the shortest duration in every case. However, the logic of LS tasks rule is too complex to be conveyed to the framing crew. Therefore, the new mental framework of a well performing framer was developed and tested to ensure high coordination. This mental framework, based on five simple rules, can be easily taught to the crew and ensures a crew productivity congruent with the one provided by the LS logic. The case studies indicate that once the worst framer in the crew surpasses the limit of 11% deviation from applying the said five rules, every additional percent of deviation reduces the productivity of the whole crew by about 4%.
ContributorsMaghiar, Marcel M (Author) / Wiezel, Avi (Thesis advisor) / Mitropoulos, Panagiotis (Committee member) / Cooke, Nancy J. (Committee member) / Arizona State University (Publisher)
Created2011
ContributorsKotronakis, Dimitris (Performer) / ASU Library. Music Library (Publisher)
Created2018-03-01
Description
Highly automated vehicles require drivers to remain aware enough to takeover
during critical events. Driver distraction is a key factor that prevents drivers from reacting
adequately, and thus there is need for an alert to help drivers regain situational awareness
and be able to act quickly and successfully should a critical event arise. This study
examines two aspects of alerts that could help facilitate driver takeover: mode (auditory
and tactile) and direction (towards and away). Auditory alerts appear to be somewhat
more effective than tactile alerts, though both modes produce significantly faster reaction
times than no alert. Alerts moving towards the driver also appear to be more effective
than alerts moving away from the driver. Future research should examine how
multimodal alerts differ from single mode, and see if higher fidelity alerts influence
takeover times.
during critical events. Driver distraction is a key factor that prevents drivers from reacting
adequately, and thus there is need for an alert to help drivers regain situational awareness
and be able to act quickly and successfully should a critical event arise. This study
examines two aspects of alerts that could help facilitate driver takeover: mode (auditory
and tactile) and direction (towards and away). Auditory alerts appear to be somewhat
more effective than tactile alerts, though both modes produce significantly faster reaction
times than no alert. Alerts moving towards the driver also appear to be more effective
than alerts moving away from the driver. Future research should examine how
multimodal alerts differ from single mode, and see if higher fidelity alerts influence
takeover times.
ContributorsBrogdon, Michael A (Author) / Gray, Robert (Thesis advisor) / Branaghan, Russell (Committee member) / Chiou, Erin (Committee member) / Arizona State University (Publisher)
Created2018
Description
For as long as humans have been working, they have been looking for ways to get that work done better, faster, and more efficient. Over the course of human history, mankind has created innumerable spectacular inventions, all with the goal of making the economy and daily life more efficient. Today, innovations and technological advancements are happening at a pace like never seen before, and technology like automation and artificial intelligence are poised to once again fundamentally alter the way people live and work in society. Whether society is prepared or not, robots are coming to replace human labor, and they are coming fast. In many areas artificial intelligence has disrupted entire industries of the economy. As people continue to make advancements in artificial intelligence, more industries will be disturbed, more jobs will be lost, and entirely new industries and professions will be created in their wake. The future of the economy and society will be determined by how humans adapt to the rapid innovations that are taking place every single day. In this paper I will examine the extent to which automation will take the place of human labor in the future, project the potential effect of automation to future unemployment, and what individuals and society will need to do to adapt to keep pace with rapidly advancing technology. I will also look at the history of automation in the economy. For centuries humans have been advancing technology to make their everyday work more productive and efficient, and for centuries this has forced humans to adapt to the modern technology through things like training and education. The thesis will additionally examine the ways in which the U.S. education system will have to adapt to meet the demands of the advancing economy, and how job retraining programs must be modernized to prepare workers for the changing economy.
ContributorsCunningham, Reed P. (Author) / DeSerpa, Allan (Thesis director) / Haglin, Brett (Committee member) / School of International Letters and Cultures (Contributor) / Department of Finance (Contributor) / Barrett, The Honors College (Contributor)
Created2018-05
Description
The foundations of legacy media, especially the news media, are not as strong as they once were. A digital revolution has changed the operation models for and journalistic organizations are trying to find their place in the new market. This project is intended to analyze the effects of new/emerging technologies on the journalism industry. Five different categories of technology will be explored. They are as follows: the semantic web, automation software, data analysis and aggregators, virtual reality and drone journalism. The potential of these technologies will be broken up according to four guidelines, ethical implications, effects on the reportorial process, business impacts and changes to the consumer experience. Upon my examination, it is apparent that no single technology will offer the journalism industry the remedy it has been searching for. Some combination of emerging technologies however, may form the basis for the next generation of news. Findings are presented on a website that features video, visuals, linked content, and original graphics. Website found at http://www.explorenewstech.com/
ContributorsMaxwell, Gavin William (Author) / McGuire, Tim (Thesis director) / Cornelius, David (Committee member) / Walter Cronkite School of Journalism and Mass Communication (Contributor) / School of Politics and Global Studies (Contributor) / Barrett, The Honors College (Contributor)
Created2016-05
Description
Artificial intelligence (AI) is a burgeoning technology, industry, and field of study. While interest levels regarding its applications in marketing have not yet translated into widespread adoption, AI holds tremendous potential for vastly altering how marketing is done. As such, AI in marketing is a crucial topic to research. By analyzing its current applications, its potential use cases in the near future, how to implement it and its areas for improvement, we can achieve a high-level understanding of AI's long-term implications in marketing. AI offers an improvement to current marketing tactics, as well as entirely new ways of creating and distributing value to customers. For example, programmatic advertising and social media marketing can allow for a more comprehensive view of customer behavior, predictive analytics, and deeper insights through integration with AI. New marketing tools like biometrics, voice, and conversational user interfaces offer novel ways to add value for brands and consumers alike. These innovations all carry similar characteristics of hyper-personalization, efficient spending, scalable experiences, and deep insights. There are important issues that need to be addressed before AI is extensively implemented, including the potential for it to be used maliciously, its effects on job displacement, and the technology itself. The recent progression of AI in marketing is indicative that it will be adopted by a majority of companies soon. The long-term implications of vast implementation are crucial to consider, as an AI-powered industry entails fundamental changes to the skill-sets required to thrive, the way marketers and brands work, and consumer expectations.
ContributorsCannella, James (Author) / Ostrom, Amy (Thesis director) / Giles, Charles (Committee member) / Department of Marketing (Contributor) / Department of Management and Entrepreneurship (Contributor) / Barrett, The Honors College (Contributor)
Created2018-05
Description
Many fear that the growth of automation and artificial intelligence will lead to massive unemployment since human labor would no longer be needed. Although automation does displace workers from their current jobs, it is unclear the total net effect on jobs this period of advancement will have. One possible solution to help displaced workers is a Universal Basic Income. A Universal Basic Income(UBI) is a set payment paid to all members of society regardless of working status. Compared to current unemployment programs, a Universal Basic Income does not restrict participants in how to spend the money and is more inclusive. This paper examines the effects of a UBI on a person's motivation to work through a study on current college students. There is reason to believe that a Universal Basic Income will lead to fewer people working as people may become dependent on a base payment to meet their basic needs and not look for work. In addition, some people may drop out of their current jobs and rely on a UBI as their main form of income. The current literature does not offer a consensus opinion on this relationship and more studies are being completed with the threat of mass unemployment looming. This study shows the effects of a UBI on participants' willingness to work and then applies these results to the current economic model. With these results and new economic model, a decision about future policies surrounding a UBI can be made.
ContributorsAgarwal, Raghav (Author) / Pulido Hernadez, Carlos (Thesis director) / Foster, William (Committee member) / School of Mathematical and Statistical Sciences (Contributor) / Department of Economics (Contributor) / Barrett, The Honors College (Contributor)
Created2018-05