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- Creators: Arizona State University
- Creators: Baral, Chitta
Description
There has been a push to create and implement school wellness policies. Childhood obesity statistics suggest that schools may have an important role to play in promoting wellness. Childhood obesity has become a significant problem in the United States. The percentage of obese children in the United States has more than doubled since 1970, and up to 33% of the children in the United States are currently overweight. Among the 33% of children who are overweight, 25% are obese, and 14% have type 2 diabetes, previously considered to be a condition found only in adults. This mixed-method study with a string qualitative component study examined three aspects of federally mandated local wellness polices. The study investigated the policies themselves, how the policies are understood in the local school setting, with a particular focus on the impact the policies have had on school meals. The bulk of the research data was generated through 8 in-depth interviews. The interviews were conducted with key stakeholders within 2 elementary school districts in Arizona. In addition, the evaluation of 20 local wellness polices was conducted via a rubric scoring system. The primary component found to be lacking in local wellness policies was the evaluation method. Recommendations for school districts include the establishment of a clear method of measurement.
ContributorsCrawford, Sara S (Author) / Mccarty, Teresa L. (Thesis advisor) / Molnar, Alex (Thesis advisor) / Montoya, Araceli (Committee member) / Arizona State University (Publisher)
Created2011
Description
Semiconductor manufacturing facilities are very complex and capital intensive in nature. During the lifecycle of these facilities various disciplines come together, generate and use a tremendous amount of building and process information to support various decisions that enable them to successfully design, build and sustain these advanced facilities. However, a majority of the information generated and processes taking place are neither integrated nor interoperable and result in a high degree of redundancy. The objective of this thesis is to build an interoperable Building Information Model (BIM) for the Base-Build and Tool Installation in a semiconductor manufacturing facility. It examines existing processes and data exchange standards available to facilitate the implementation of BIM and provides a framework for the development of processes and standards that can help in building an intelligent information model for a semiconductor manufacturing facility. To understand the nature of the flow of information between the various stakeholders the flow of information between the facility designer, process tool manufacturer and tool layout designer is examined. An information model for the base build and process tool is built and the industry standards SEMI E6 and SEMI E51 are used as a basis to model the information. It is found that applications used to create information models support interoperable industry standard formats such as the Industry Foundation Classes (IFC) and ISO 15926 in a limited manner. A gap analysis has revealed that interoperability standards applicable to the semiconductor manufacturing industry such as the IFC and ISO15926 need to be expanded to support information transfers unique to the industry. Information modeling for a semiconductor manufacturing facility is unique in that it is a process model (Process Tool Information Model) within a building model (Building Information Model), each of them supported more robustly by different interoperability standards. Applications support interoperability data standards specific to the domain or industry they serve but information transfers need to occur between the various domains. To facilitate flow of information between the different domains it is recommended that a mapping of the industry standards be undertaken and translators between them be developed for business use.
ContributorsPindukuri, Shruthi (Author) / Chasey, Allan D (Thesis advisor) / Wiezel, Avi (Committee member) / Mamlouk, Michael (Committee member) / Arizona State University (Publisher)
Created2011
Description
Parents die during the lives of their children. If the child is an adolescent, that death will impact the student's education immediately or in subsequent years. Findings show the death of a mother does impact the daughter's education. It is imperative educators are willing to work with the student at the time the death occurs as well as in the ensuing months. Seidman's (2006) three-interview format was used as a template for the interviews of 11 women, ranging in age from 19 to 78 and whose mothers died when the women were adolescents. The interviews were primarily conducted in one sitting, transcribed, and then analyzed for common themes that connected to the research on the topic. Those themes include grieving, the role of caring in education, the role of teacher as the second mother, mother-daughter relationships, and the impact of parent death on schooling. These themes from the data cross cut with thematic strands within the study's theoretical framework: the nurturing and empathetic role of the mother, a desire of the daughter not to be different, and the ethics of caring. Findings in this study reveal that the negative impacts of mother loss are felt in diffuse ways, such as a lack of academic or emotional encouragement. Many women discussed the need and availability of support groups including groups at colleges. One practical implication of these findings is schools need to become caring communities in which caring is the norm for all students and teachers, thereby providing all students with needed support in times of crisis. The implications for further research include the impact of the mother death on the education of daughters, how volunteering with an organization related to the cause of the mother's death assists the daughter and types of programs most important to a student's success in post-secondary education. Adolescents are in a time of great change in their lives, and for a daughter, the loss of a mother has an everlasting, life-changing impact.
ContributorsRatti, Theresa Helen McLuskey (Author) / Mccarty, Teresa L (Thesis advisor) / Fischman, Gustavo E. (Committee member) / Powers, Jeanne M. (Committee member) / Arizona State University (Publisher)
Created2011
Description
Currently Java is making its way into the embedded systems and mobile devices like androids. The programs written in Java are compiled into machine independent binary class byte codes. A Java Virtual Machine (JVM) executes these classes. The Java platform additionally specifies the Java Native Interface (JNI). JNI allows Java code that runs within a JVM to interoperate with applications or libraries that are written in other languages and compiled to the host CPU ISA. JNI plays an important role in embedded system as it provides a mechanism to interact with libraries specific to the platform. This thesis addresses the overhead incurred in the JNI due to reflection and serialization when objects are accessed on android based mobile devices. It provides techniques to reduce this overhead. It also provides an API to access objects through its reference through pinning its memory location. The Android emulator was used to evaluate the performance of these techniques and we observed that there was 5 - 10 % performance gain in the new Java Native Interface.
ContributorsChandrian, Preetham (Author) / Lee, Yann-Hang (Thesis advisor) / Davulcu, Hasan (Committee member) / Li, Baoxin (Committee member) / Arizona State University (Publisher)
Created2011
Description
As pointed out in the keynote speech by H. V. Jagadish in SIGMOD'07, and also commonly agreed in the database community, the usability of structured data by casual users is as important as the data management systems' functionalities. A major hardness of using structured data is the problem of easily retrieving information from them given a user's information needs. Learning and using a structured query language (e.g., SQL and XQuery) is overwhelmingly burdensome for most users, as not only are these languages sophisticated, but the users need to know the data schema. Keyword search provides us with opportunities to conveniently access structured data and potentially significantly enhances the usability of structured data. However, processing keyword search on structured data is challenging due to various types of ambiguities such as structural ambiguity (keyword queries have no structure), keyword ambiguity (the keywords may not be accurate), user preference ambiguity (the user may have implicit preferences that are not indicated in the query), as well as the efficiency challenges due to large search space. This dissertation performs an expansive study on keyword search processing techniques as a gateway for users to access structured data and retrieve desired information. The key issues addressed include: (1) Resolving structural ambiguities in keyword queries by generating meaningful query results, which involves identifying relevant keyword matches, identifying return information, composing query results based on relevant matches and return information. (2) Resolving structural, keyword and user preference ambiguities through result analysis, including snippet generation, result differentiation, result clustering, result summarization/query expansion, etc. (3) Resolving the efficiency challenge in processing keyword search on structured data by utilizing and efficiently maintaining materialized views. These works deliver significant technical contributions towards building a full-fledged search engine for structured data.
ContributorsLiu, Ziyang (Author) / Chen, Yi (Thesis advisor) / Candan, Kasim S (Committee member) / Davulcu, Hasan (Committee member) / Jagadish, H V (Committee member) / Arizona State University (Publisher)
Created2011
Description
Reliable extraction of human pose features that are invariant to view angle and body shape changes is critical for advancing human movement analysis. In this dissertation, the multifactor analysis techniques, including the multilinear analysis and the multifactor Gaussian process methods, have been exploited to extract such invariant pose features from video data by decomposing various key contributing factors, such as pose, view angle, and body shape, in the generation of the image observations. Experimental results have shown that the resulting pose features extracted using the proposed methods exhibit excellent invariance properties to changes in view angles and body shapes. Furthermore, using the proposed invariant multifactor pose features, a suite of simple while effective algorithms have been developed to solve the movement recognition and pose estimation problems. Using these proposed algorithms, excellent human movement analysis results have been obtained, and most of them are superior to those obtained from state-of-the-art algorithms on the same testing datasets. Moreover, a number of key movement analysis challenges, including robust online gesture spotting and multi-camera gesture recognition, have also been addressed in this research. To this end, an online gesture spotting framework has been developed to automatically detect and learn non-gesture movement patterns to improve gesture localization and recognition from continuous data streams using a hidden Markov network. In addition, the optimal data fusion scheme has been investigated for multicamera gesture recognition, and the decision-level camera fusion scheme using the product rule has been found to be optimal for gesture recognition using multiple uncalibrated cameras. Furthermore, the challenge of optimal camera selection in multi-camera gesture recognition has also been tackled. A measure to quantify the complementary strength across cameras has been proposed. Experimental results obtained from a real-life gesture recognition dataset have shown that the optimal camera combinations identified according to the proposed complementary measure always lead to the best gesture recognition results.
ContributorsPeng, Bo (Author) / Qian, Gang (Thesis advisor) / Ye, Jieping (Committee member) / Li, Baoxin (Committee member) / Spanias, Andreas (Committee member) / Arizona State University (Publisher)
Created2011
Description
The purpose of this study was to examine compulsory schooling in the United States and its potential to provide an inconsistent avenue to employment for students from neighborhoods of differing socioeconomic status. Specifically, this study asked why do students from privileged neighborhoods typically end up in positions of ownership and management while those from impoverished urban or rural neighborhoods end up in working-class positions or involved in cycles of incarceration and poverty? This research involved the use of qualitative methods, including participant observation and interview, as well as photography, to take a look at a reputable private day school in the southwest. Data was collected over the span of eight weeks and was then analyzed and compared with preexisting data on the schooling experience of students from impoverished urban and rural neighborhoods, particularly data focused on juvenile detention centers. Results showed that compulsory schooling differs in ways that contribute to the preexisting hierarchical class structure. The research suggests that schooling can be detrimental to the future quality of life for students in impoverished neighborhoods, which questions a compulsory school system that exists within the current hierarchical class system.
ContributorsTheodoropoulos, Eftyhia (Author) / Margolis, Eric (Thesis advisor) / Nakagawa, Kathryn (Committee member) / Appleton, Nicholas (Committee member) / Arizona State University (Publisher)
Created2011
Description
Concrete columns constitute the fundamental supports of buildings, bridges, and various other infrastructures, and their failure could lead to the collapse of the entire structure. As such, great effort goes into improving the fire resistance of such columns. In a time sensitive fire situation, a delay in the failure of critical load bearing structures can lead to an increase in time allowed for the evacuation of occupants, recovery of property, and access to the fire. Much work has been done in improving the structural performance of concrete including reducing column sizes and providing a safer structure. As a result, high-strength (HS) concrete has been developed to fulfill the needs of such improvements. HS concrete varies from normal-strength (NS) concrete in that it has a higher stiffness, lower permeability and larger durability. This, unfortunately, has resulted in poor performance under fire. The lower permeability allows for water vapor to build up causing HS concrete to suffer from explosive spalling under rapid heating. In addition, the coefficient of thermal expansion (CTE) of HS concrete is lower than that of NS concrete. In this study, the effects of introducing a region of crumb rubber concrete into a steel-reinforced concrete column were analyzed. The inclusion of crumb rubber concrete into a column will greatly increase the thermal resistivity of the overall column, leading to a reduction in core temperature as well as the rate at which the column is heated. Different cases were analyzed while varying the positioning of the crumb-rubber region to characterize the effect of position on the improvement of fire resistance. Computer simulated finite element analysis was used to calculate the temperature and strain distribution with time across the column's cross-sectional area with specific interest in the steel - concrete region. Of the several cases which were investigated, it was found that the improvement of time before failure ranged between 32 to 45 minutes.
ContributorsZiadeh, Bassam Mohammed (Author) / Phelan, Patrick (Thesis advisor) / Kaloush, Kamil (Thesis advisor) / Jiang, Hanqing (Committee member) / Arizona State University (Publisher)
Created2011
Description
This thesis describes a synthetic task environment, CyberCog, created for the purposes of 1) understanding and measuring individual and team situation awareness in the context of a cyber security defense task and 2) providing a context for evaluating algorithms, visualizations, and other interventions that are intended to improve cyber situation awareness. CyberCog provides an interactive environment for conducting human-in-loop experiments in which the participants of the experiment perform the tasks of a cyber security defense analyst in response to a cyber-attack scenario. CyberCog generates the necessary performance measures and interaction logs needed for measuring individual and team cyber situation awareness. Moreover, the CyberCog environment provides good experimental control for conducting effective situation awareness studies while retaining realism in the scenario and in the tasks performed.
ContributorsRajivan, Prashanth (Author) / Femiani, John (Thesis advisor) / Cooke, Nancy J. (Thesis advisor) / Lindquist, Timothy (Committee member) / Gary, Kevin (Committee member) / Arizona State University (Publisher)
Created2011
Description
With the introduction of compressed sensing and sparse representation,many image processing and computer vision problems have been looked at in a new way. Recent trends indicate that many challenging computer vision and image processing problems are being solved using compressive sensing and sparse representation algorithms. This thesis assays some applications of compressive sensing and sparse representation with regards to image enhancement, restoration and classication. The first application deals with image Super-Resolution through compressive sensing based sparse representation. A novel framework is developed for understanding and analyzing some of the implications of compressive sensing in reconstruction and recovery of an image through raw-sampled and trained dictionaries. Properties of the projection operator and the dictionary are examined and the corresponding results presented. In the second application a novel technique for representing image classes uniquely in a high-dimensional space for image classification is presented. In this method, design and implementation strategy of the image classification system through unique affine sparse codes is presented, which leads to state of the art results. This further leads to analysis of some of the properties attributed to these unique sparse codes. In addition to obtaining these codes, a strong classier is designed and implemented to boost the results obtained. Evaluation with publicly available datasets shows that the proposed method outperforms other state of the art results in image classication. The final part of the thesis deals with image denoising with a novel approach towards obtaining high quality denoised image patches using only a single image. A new technique is proposed to obtain highly correlated image patches through sparse representation, which are then subjected to matrix completion to obtain high quality image patches. Experiments suggest that there may exist a structure within a noisy image which can be exploited for denoising through a low-rank constraint.
ContributorsKulkarni, Naveen (Author) / Li, Baoxin (Thesis advisor) / Ye, Jieping (Committee member) / Sen, Arunabha (Committee member) / Arizona State University (Publisher)
Created2011