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- All Subjects: artificial intelligence
- Creators: Arizona State University
Description
This thesis explores the extent to which entrepreneurship is possible for women in Saudi Arabia, and it's potential to increase Saudi women's socio-cultural autonomy, financial independence, and overall well-being. The study uses interviews and an online surveys to gather information from recognized female entrepreneurs, those officially registered with the Women's Business Center in Alkhober, Saudi Arabia, about how they founded their businesses, the challenges they have experienced, and the effects of business ownership. These women are interesting because their experience seems to run counter to Saudi society, which generally restricts women's activities. The study's findings show that despite their successes, Arab traditions still hinder the success of Alkhober female entrepreneurs, for instance, by requiring male guardianship and prohibiting travel unaccompanied by a man. From an institutional perspective, administrative and legal requirement can prevent women from fully realizing their potential as businesswomen. The existing women's rights legislation lacks authority because political opportunities for Alkhober women are still limited. For Saudi women entrepreneurship remains an alternative to joblessness and dissatisfaction derived from other employment sources. The challenges women entrepreneurs experience while starting businesses are lack of support from the executive branch of government, lack of quality education, and lack of available financial resources, in addition to the cultural barriers caused by Arab traditions restricting the activities of women. However, a key finding from this study is that the women interviewed all showed a high level of resourcefulness and creativity that helped them to circumvent such obstacles. This study recommends that the government provide financial services, or training programs to aspiring female entrepreneurs and offer incentives for women to register their businesses. This will benefit not just Saudi women but for the Saudi economy overall.
ContributorsAlhabidi, Mariam (Author) / C. Parmentier, Mary Jane C. Parmentier Jane (Thesis advisor) / Grossman, Gary M. (Committee member) / Crewe, Katherine (Committee member) / Arizona State University (Publisher)
Created2013
Description
The rapid escalation of technology and the widespread emergence of modern technological equipments have resulted in the generation of humongous amounts of digital data (in the form of images, videos and text). This has expanded the possibility of solving real world problems using computational learning frameworks. However, while gathering a large amount of data is cheap and easy, annotating them with class labels is an expensive process in terms of time, labor and human expertise. This has paved the way for research in the field of active learning. Such algorithms automatically select the salient and exemplar instances from large quantities of unlabeled data and are effective in reducing human labeling effort in inducing classification models. To utilize the possible presence of multiple labeling agents, there have been attempts towards a batch mode form of active learning, where a batch of data instances is selected simultaneously for manual annotation. This dissertation is aimed at the development of novel batch mode active learning algorithms to reduce manual effort in training classification models in real world multimedia pattern recognition applications. Four major contributions are proposed in this work: $(i)$ a framework for dynamic batch mode active learning, where the batch size and the specific data instances to be queried are selected adaptively through a single formulation, based on the complexity of the data stream in question, $(ii)$ a batch mode active learning strategy for fuzzy label classification problems, where there is an inherent imprecision and vagueness in the class label definitions, $(iii)$ batch mode active learning algorithms based on convex relaxations of an NP-hard integer quadratic programming (IQP) problem, with guaranteed bounds on the solution quality and $(iv)$ an active matrix completion algorithm and its application to solve several variants of the active learning problem (transductive active learning, multi-label active learning, active feature acquisition and active learning for regression). These contributions are validated on the face recognition and facial expression recognition problems (which are commonly encountered in real world applications like robotics, security and assistive technology for the blind and the visually impaired) and also on collaborative filtering applications like movie recommendation.
ContributorsChakraborty, Shayok (Author) / Panchanathan, Sethuraman (Thesis advisor) / Balasubramanian, Vineeth N. (Committee member) / Li, Baoxin (Committee member) / Mittelmann, Hans (Committee member) / Ye, Jieping (Committee member) / Arizona State University (Publisher)
Created2013
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
Objective of this thesis project is to build a prototype using Linear Temporal Logic specifications for generating a 2D motion plan commanding an iRobot to fulfill the specifications. This thesis project was created for Cyber Physical Systems Lab in Arizona State University. The end product of this thesis is creation of a software solution which can be used in the academia and industry for research in cyber physical systems related applications. The major features of the project are: creating a modular system for motion planning, use of Robot Operating System (ROS), use of triangulation for environment decomposition and using stargazer sensor for localization. The project is built on an open source software called ROS which provides an environment where it is very easy to integrate different modules be it software or hardware on a Linux based platform. Use of ROS implies the project or its modules can be adapted quickly for different applications as the need arises. The final software package created and tested takes a data file as its input which contains the LTL specifications, a symbols list used in the LTL and finally the environment polygon data containing real world coordinates for all polygons and also information on neighbors and parents of each polygon. The software package successfully ran the experiment of coverage, reachability with avoidance and sequencing.
ContributorsPandya, Parth (Author) / Fainekos, Georgios (Thesis advisor) / Dasgupta, Partha (Committee member) / Lee, Yann-Hang (Committee member) / Arizona State University (Publisher)
Created2013
Description
Linear Temporal Logic is gaining increasing popularity as a high level specification language for robot motion planning due to its expressive power and scalability of LTL control synthesis algorithms. This formalism, however, requires expert knowledge and makes it inaccessible to non-expert users. This thesis introduces a graphical specification environment to create high level motion plans to control robots in the field by converting a visual representation of the motion/task plan into a Linear Temporal Logic (LTL) specification. The visual interface is built on the Android tablet platform and provides functionality to create task plans through a set of well defined gestures and on screen controls. It uses the notion of waypoints to quickly and efficiently describe the motion plan and enables a variety of complex Linear Temporal Logic specifications to be described succinctly and intuitively by the user without the need for the knowledge and understanding of LTL specification. Thus, it opens avenues for its use by personnel in military, warehouse management, and search and rescue missions. This thesis describes the construction of LTL for various scenarios used for robot navigation using the visual interface developed and leverages the use of existing LTL based motion planners to carry out the task plan by a robot.
ContributorsSrinivas, Shashank (Author) / Fainekos, Georgios (Thesis advisor) / Baral, Chitta (Committee member) / Burleson, Winslow (Committee member) / Arizona State University (Publisher)
Created2013
Description
A common concern among musical performers in today'’s musical market pertains to their capacity to adapt to the constantly changing climate of the music business. This document focuses on one aspect of the development of a sustainable, entrepreneurship skill set: the production of a recording. While producing the recording Chocolates, the author examined and documented the multiplicity of skills encompassed with a recording project. The first part of the document includes a discussion of various aspects of the recording project, Chocolates, through an entrepreneurial lens, and an evaluation of the skill sets acquired through the recording process. Additionally, the inspiration and relevance behind the recording project and the process of collaboration between the two composers from whom I commissioned new compositions, Noah Taylor and James Grant, and myself is considered. Finally, I describe the recording and editing processes, including the planning involved within each process, how I achieved the final product, and the entrepreneurial skills involved. The second portion of this document examines a broad range of applications of entrepreneurship, marketing, and career management skills not only within the confines of this particular project, but also in relation to the overall sustainability of a twenty-–first century music-–performing career.
ContributorsStuckemeyer, Mary (Author) / Micklich, Albie (Thesis advisor) / Carpenter, Ellon (Committee member) / Hill, Gary (Committee member) / Schuring, Martin (Committee member) / Spring, Robert (Committee member) / Arizona State University (Publisher)
Created2013
Description
Answer Set Programming (ASP) is one of the most prominent and successful knowledge representation paradigms. The success of ASP is due to its expressive non-monotonic modeling language and its efficient computational methods originating from building propositional satisfiability solvers. The wide adoption of ASP has motivated several extensions to its modeling language in order to enhance expressivity, such as incorporating aggregates and interfaces with ontologies. Also, in order to overcome the grounding bottleneck of computation in ASP, there are increasing interests in integrating ASP with other computing paradigms, such as Constraint Programming (CP) and Satisfiability Modulo Theories (SMT). Due to the non-monotonic nature of the ASP semantics, such enhancements turned out to be non-trivial and the existing extensions are not fully satisfactory. We observe that one main reason for the difficulties rooted in the propositional semantics of ASP, which is limited in handling first-order constructs (such as aggregates and ontologies) and functions (such as constraint variables in CP and SMT) in natural ways. This dissertation presents a unifying view on these extensions by viewing them as instances of formulas with generalized quantifiers and intensional functions. We extend the first-order stable model semantics by by Ferraris, Lee, and Lifschitz to allow generalized quantifiers, which cover aggregate, DL-atoms, constraints and SMT theory atoms as special cases. Using this unifying framework, we study and relate different extensions of ASP. We also present a tight integration of ASP with SMT, based on which we enhance action language C+ to handle reasoning about continuous changes. Our framework yields a systematic approach to study and extend non-monotonic languages.
ContributorsMeng, Yunsong (Author) / Lee, Joohyung (Thesis advisor) / Ahn, Gail-Joon (Committee member) / Baral, Chitta (Committee member) / Fainekos, Georgios (Committee member) / Lifschitz, Vladimir (Committee member) / Arizona State University (Publisher)
Created2013
Description
This dissertation examines the role that business counselors in a public entrepreneurial development program play in improving the Entrepreneurial Specific Human Capital (ESHC) of nascent and active entrepreneurs. Through multiple research methodologies, this study identifies the types of ESHC provided by business counselors then compares them to the types of ESHC commonly accepted as necessary for entrepreneurial success. The comparison reveals a number of insights for policy and research, most notably a minimum portfolio of skills necessary for entrepreneurial success. This study also examines the methods counselors use to help entrepreneurs acquire higher levels of ESHC. These methods allow counselors to assist entrepreneurs in recognizing and overcoming common barriers to business growth, and a model of entrepreneurial business growth barriers has been produced which depicts these barriers as conceptual-operational transition points for the entrepreneur. Additionally, this dissertation develops important information about the use of the business plan in entrepreneurial development, and uncovers a number of moderators in the relationship between the use of the business plan and entrepreneurial success. Finally, the study produces detailed information about ESHC which has potential for scale development, and highlights a number of insights for policy and research that have not been identified previously.
ContributorsDahlstrom, Timothy R (Author) / Chapman, Jeffrey I. (Thesis advisor) / Phillips, Rhonda (Committee member) / Knopf, Richard (Committee member) / Arizona State University (Publisher)
Created2013
Description
This thesis introduces the Model-Based Development of Multi-iRobot Toolbox (MBDMIRT), a Simulink-based toolbox designed to provide the means to acquire and practice the Model-Based Development (MBD) skills necessary to design real-time embedded system. The toolbox was developed in the Cyber-Physical System Laboratory at Arizona State University. The MBDMIRT toolbox runs under MATLAB/Simulink to simulate the movements of multiple iRobots and to control, after verification by simulation, multiple physical iRobots accordingly. It adopts the Simulink/Stateflow, which exemplifies an approach to MBD, to program the behaviors of the iRobots. The MBDMIRT toolbox reuses and augments the open-source MATLAB-Based Simulator for the iRobot Create from Cornell University to run the simulation. Regarding the mechanism of iRobot control, the MBDMIRT toolbox applies the MATLAB Toolbox for the iRobot Create (MTIC) from United States Naval Academy to command the physical iRobots. The MBDMIRT toolbox supports a timer in both the simulation and the control, which is based on the local clock of the PC running the toolbox. In addition to the build-in sensors of an iRobot, the toolbox can simulate four user-added sensors, which are overhead localization system (OLS), sonar sensors, a camera, and Light Detection And Ranging (LIDAR). While controlling a physical iRobot, the toolbox supports the StarGazer OLS manufactured by HAGISONIC, Inc.
ContributorsSu, Shih-Kai (Author) / Fainekos, Georgios E (Thesis advisor) / Sarjoughian, Hessam S. (Committee member) / Artemiadis, Panagiotis K (Committee member) / Arizona State University (Publisher)
Created2012
Description
The jobless recovery of the Great Recession has led policymakers and citizens alike to ask what can be done to better protect regions from the cascading effects of an economic downturn. Economic growth strategies that aim to redevelop a waterfront for tourism or attract high growth companies to the area, for example, have left regions vulnerable by consolidating resources in just a few industry sectors or parts of town. A promising answer that coincided with growing interest in regional innovation policy has been to promote entrepreneurship for bottom-up, individual-led regional development. However, these policies have also failed to maximize the potential for bottom-up development by focusing on high skill entrepreneurs and high tech industry sectors, such as green energy and nanotechnology. This dissertation uses the extended case method to determine whether industry cluster theory can be usefully extended from networks of high skill innovators to entrepreneurs in traditional trades. It uses U.S. Census data and in-person interviews in cluster and non-cluster neighborhoods in Dayton, Ohio to assess whether traditional entrepreneurs cluster and whether social networks explain high rates of neighborhood self-employment. Entrepreneur interviews are also conducted in Raleigh, North Carolina to explore regional resilience by comparing the behavior of traditional entrepreneurs in the ascendant tech-hub region of Raleigh and stagnant Rustbelt region of Dayton. The quantitative analysis documents, for the first time, a minor degree of neighborhood-level entrepreneur clustering. In interviews, entrepreneurs offered clear examples of social networks that resemble those shown to make regional clusters successful, and they helped clarify that a slightly larger geography may reveal more clustering. Comparing Raleigh and Dayton entrepreneurs, the study found few differences in their behavior to explain the regions' differing long-term economic trends. However, charitable profit-seeking and trial and error learning are consistent behaviors that may distinguish traditional, small scale entrepreneurs from larger export-oriented business owners and contribute to a region's ability to withstand recessions and other shocks. The research informs growing policy interest in bottom-up urban development by offering qualitative evidence for how local mechanics, seamstresses, lawn care businesses and many others can be regional assets. Future research should use larger entrepreneur samples to systematically test the relationship between entrepreneur resilience behaviors to regional economic outcomes.
ContributorsAuer, Jennifer Claire (Author) / Chapman, Jeffrey (Thesis advisor) / Johnston, Erik W., 1977- (Committee member) / Jurik, Nancy (Committee member) / Arizona State University (Publisher)
Created2013