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Description
The price based marketplace has dominated the construction industry. The majority of owners use price based practices of management (expectation and decision making, control, direction, and inspection.) The price based/management and control paradigm has not worked. Clients have now been moving toward the best value environment (hire contractors who know what they are doing, who preplan, and manage and minimize risk and deviation.) Owners are trying to move from client direction and control to hiring an expert and allowing them to do the quality control/risk management. The movement of environments changes the paradigm for the contractors from a reactive to a proactive, from a bureaucratic
on-accountable to an accountable position, from a relationship based
on-measuring to a measuring entity, and to a contractor who manages and minimizes the risk that they do not control. Years of price based practices have caused poor quality and low performance in the construction industry. This research identifies what is a best value contractor or vendor, what factors make up a best value vendor, and the methodology to transform a vendor to a best value vendor. It will use deductive logic, a case study to confirm the logic and the proposed methodology.
on-accountable to an accountable position, from a relationship based
on-measuring to a measuring entity, and to a contractor who manages and minimizes the risk that they do not control. Years of price based practices have caused poor quality and low performance in the construction industry. This research identifies what is a best value contractor or vendor, what factors make up a best value vendor, and the methodology to transform a vendor to a best value vendor. It will use deductive logic, a case study to confirm the logic and the proposed methodology.
ContributorsPauli, Michele (Author) / Kashiwagi, Dean (Thesis advisor) / Sullivan, Kenneth (Committee member) / Badger, William (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
Phosphorus (P), an essential element for life, is becoming increasingly scarce, and its global management presents a serious challenge. As urban environments dominate the landscape, we need to elucidate how P cycles in urban ecosystems to better understand how cities contribute to — and provide opportunities to solve — problems of P management. The goal of my research was to increase our understanding of urban P cycling in the context of urban resource management through analysis of existing ecological and socio-economic data supplemented with expert interviews in order to facilitate a transition to sustainable P management. Study objectives were to: I) Quantify and map P stocks and flows in the Phoenix metropolitan area and analyze the drivers of spatial distribution and dynamics of P flows; II) examine changes in P-flow dynamics at the urban agricultural interface (UAI), and the drivers of those changes, between 1978 and 2008; III) compare the UAI's average annual P budget to the global agricultural P budget; and IV) explore opportunities for more sustainable P management in Phoenix. Results showed that Phoenix is a sink for P, and that agriculture played a primary role in the dynamics of P cycling. Internal P dynamics at the UAI shifted over the 30-year study period, with alfalfa replacing cotton as the main locus of agricultural P cycling. Results also suggest that the extent of P recycling in Phoenix is proportionally larger than comparable estimates available at the global scale due to the biophysical characteristics of the region and the proximity of various land uses. Uncertainty remains about the effectiveness of current recycling strategies and about best management strategies for the future because we do not have sufficient data to use as basis for evaluation and decision-making. By working in collaboration with practitioners, researchers can overcome some of these data limitations to develop a deeper understanding of the complexities of P dynamics and the range of options available to sustainably manage P. There is also a need to better connect P management with that of other resources, notably water and other nutrients, in order to sustainably manage cities.
ContributorsMetson, Genevieve (Author) / Childers, Daniel (Thesis advisor) / Aggarwal, Rimjhim (Thesis advisor) / Redman, Charles (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
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
Description
The trend towards using recycled materials on new construction projects is growing as the cost for construction materials are ever increasing and the awareness of the responsibility we have to be good stewards of our environment is heightened. While recycled asphalt is sometimes used in pavements, its use as structural fill has been hindered by concern that it is susceptible to large long-term deformations (creep), preventing its use for a great many geotechnical applications. While asphalt/soil blends are often proposed as an alternative to 100% recycled asphalt fill, little data is available characterizing the geotechnical properties of recycled asphalt soil blends. In this dissertation, the geotechnical properties for five different recycled asphalt soil blends are characterized. Data includes the particle size distribution, plasticity index, creep, and shear strength for each blend. Blends with 0%, 25%, 50%, 75% and 100% recycled asphalt were tested. As the recycled asphalt material used for testing had particles sizes up to 1.5 inches, a large 18 inch diameter direct shear apparatus was used to determine the shear strength and creep characteristics of the material. The results of the testing program confirm that the creep potential of recycled asphalt is a geotechnical concern when the material is subjected to loads greater than 1500 pounds per square foot (psf). In addition, the test results demonstrate that the amount of soil blended with the recycled asphalt can greatly influence the creep and shear strength behavior of the composite material. Furthermore, there appears to be an optimal blend ratio where the composite material had better properties than either the recycled asphalt or virgin soil alone with respect to shear strength.
ContributorsSchaper, Jeffery M (Author) / Kavazanjian, Edward (Thesis advisor) / Houston, Sandra L. (Committee member) / Zapata, Claudia E (Committee member) / Arizona State University (Publisher)
Created2011
Description
This thesis explores concept of "global bioethics" in both its development as well as its current state in an effort to understand exactly where it fits into the larger field of bioethics. Further, the analysis poses specific questions regarding what it may contribute to this field and related fields, and the possibility and scope associated with the continued development of global bioethics as its own discipline. To achieve this, the piece addresses questions regarding current opinions on the subject, the authorities and their associated publications related to global bioethics, and what the aims of the subject should be given its current state. "Global Bioethics" is a term that, while seen frequently in bioethics literature, is difficult to define succinctly. While many opinions are provided on the concept, little consensus exists regarding its application and possible contributions and, in some cases, even its very possibility. Applying ethical principles of health and medicine globally is undoubtedly complicated by the cultural, social, and geographical considerations associated with understanding health and medicine in different populations, leading to a dichotomy between two schools of thought in relation to global bioethics. These two sides consist of those who think that universality of bioethics is possible whereas the opposing viewpoint holds that relativism is the key to applying ethics on a global scale. Despite the aforementioned dichotomy in addressing applications of global bioethics, this analysis shows that the goals of the subject should be more focused on contributing to ethical frameworks and valuable types of thinking related to the ethics health and medicine on a global scale. This is achieved through an exploration of bioethics in general, health as a function of society and culture, the history and development of global bioethics itself, and an exploration of pertinent global health topics. While primarily descriptive in nature, this analysis critiques some of the current discussions and purported goals surrounding global bioethics, recommending that the field focus on fostering valuable discussion and framing of issues rather than the pursuit of concrete judgments on moral issues in global health and medicine.
ContributorsRuffenach, Stephen Charles (Author) / Robert, Jason S (Thesis advisor) / Maienschein, Jane (Committee member) / Hruschka, Daniel J (Committee member) / Arizona State University (Publisher)
Created2011
Description
Though it is a widespread adaptation in humans and many other animals, parental care comes in a variety of forms and its subtle physiological costs, benefits, and tradeoffs related to offspring are often unknown. Thus, I studied the hydric, respiratory, thermal, and fitness dynamics of maternal egg-brooding behavior in Children's pythons (Antaresia childreni). I demonstrated that tight coiling detrimentally creates a hypoxic developmental environment that is alleviated by periodic postural adjustments. Alternatively, maternal postural adjustments detrimentally elevate rates of egg water loss relative to tight coiling. Despite ventilating postural adjustments, the developmental environment becomes increasingly hypoxic near the end of incubation, which reduces embryonic metabolism. I further demonstrated that brooding-induced hypoxia detrimentally affects offspring size, performance, locomotion, and behavior. Thus, parental care in A. childreni comes at a cost to offspring due to intra-offspring tradeoffs (i.e., those that reflect competing offspring needs, such as water balance and respiration). Next, I showed that, despite being unable to intrinsically produce body heat, A. childreni adjust egg-brooding behavior in response to shifts in nest temperature, which enhances egg temperature (e.g., reduced tight coiling during nest warming facilitated beneficial heat transfer to eggs). Last, I demonstrated that A. childreni adaptively adjust their egg-brooding behaviors due to an interaction between nest temperature and humidity. Specifically, females' behavioral response to nest warming was eliminated during low nest humidity. In combination with other studies, these results show that female pythons sense environmental temperature and humidity and utilize this information at multiple time points (i.e., during gravidity [egg bearing], at oviposition [egg laying], and during egg brooding) to enhance the developmental environment of their offspring. This research demonstrates that maternal behaviors that are simple and subtle, yet easily quantifiable, can balance several critical developmental variables (i.e., thermoregulation, water balance, and respiration).
ContributorsStahlschmidt, Zachary R (Author) / DeNardo, Dale F (Thesis advisor) / Harrison, Jon (Committee member) / McGraw, Kevin (Committee member) / Rutowski, Ronald (Committee member) / Walsberg, Glenn (Committee member) / Arizona State University (Publisher)
Created2011