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- Genre: Academic theses
- Genre: Music--19th century--History and criticism.
- Creators: Li, Baoxin
- Member of: Theses and Dissertations
- Resource Type: Text
- Status: Published
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
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
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
A systematic approach to composition has been used by a variety of composers to control an assortment of musical elements in their pieces. This paper begins with a brief survey of some of the important systematic approaches that composers have employed in their compositions, devoting particular attention to Pierre Boulez's Structures Ia . The purpose of this survey is to examine several systematic approaches to composition by prominent composers and their philosophy in adopting this type of approach. The next section of the paper introduces my own systematic approach to composition: the Take-Away System. The third provides several musical applications of the system, citing my work, Octulus for two pianos, as an example. The appendix details theorems and observations within the system for further study.
ContributorsHarbin, Doug (Author) / Hackbarth, Glenn (Thesis advisor) / DeMars, James (Committee member) / Etezady, Roshanne, 1973- (Committee member) / Rockmaker, Jody (Committee member) / Rogers, Rodney (Committee member) / Arizona State University (Publisher)
Created2011
Description
During the twentieth-century, the dual influence of nationalism and modernism in the eclectic music from Latin America promoted an idiosyncratic style which naturally combined traditional themes, popular genres and secular music. The saxophone, commonly used as a popular instrument, started to develop a prominent role in Latin American classical music beginning in 1970. The lack of exposure and distribution of the Latin American repertoire has created a general perception that composers are not interested in the instrument, and that Latin American repertoire for classical saxophone is minimal. However, there are more than 1100 works originally written for saxophone in the region, and the amount continues to grow. This Modern Latin American Repertoire for Classical Saxophone: Recording Project and Performance Guide document establishes and exhibits seven works by seven representative Latin American composers.The recording includes works by Carlos Gonzalo Guzman (Colombia), Ricardo Tacuchian (Brazil), Roque Cordero (Panama), Luis Naón (Argentina), Andrés Alén-Rodriguez (Cuba), Alejandro César Morales (Mexico) and Jose-Luis Maúrtua (Peru), featuring a range of works for solo alto saxophone to alto saxophone with piano, alto saxophone with vibraphone, and tenor saxophone with electronic tape; thus forming an important selection of Latin American repertoire. Complete recorded performances of all seven pieces are supplemented by biographical, historical, and performance practice suggestions. The result is a written and audio guide to some of the most important pieces composed for classical saxophone in Latin America, with an emphasis on fostering interest in, and research into, composers who have contributed in the development and creation of the instrument in Latin America.
ContributorsOcampo Cardona, Javier Andrés (Author) / McAllister, Timothy (Thesis advisor) / Spring, Robert (Committee member) / Hill, Gary (Committee member) / Pilafian, Sam (Committee member) / Rogers, Rodney (Committee member) / Gardner, Joshua (Committee member) / Arizona State University (Publisher)
Created2011
Description
There are many wireless communication and networking applications that require high transmission rates and reliability with only limited resources in terms of bandwidth, power, hardware complexity etc.. Real-time video streaming, gaming and social networking are a few such examples. Over the years many problems have been addressed towards the goal of enabling such applications; however, significant challenges still remain, particularly, in the context of multi-user communications. With the motivation of addressing some of these challenges, the main focus of this dissertation is the design and analysis of capacity approaching coding schemes for several (wireless) multi-user communication scenarios. Specifically, three main themes are studied: superposition coding over broadcast channels, practical coding for binary-input binary-output broadcast channels, and signalling schemes for two-way relay channels. As the first contribution, we propose an analytical tool that allows for reliable comparison of different practical codes and decoding strategies over degraded broadcast channels, even for very low error rates for which simulations are impractical. The second contribution deals with binary-input binary-output degraded broadcast channels, for which an optimal encoding scheme that achieves the capacity boundary is found, and a practical coding scheme is given by concatenation of an outer low density parity check code and an inner (non-linear) mapper that induces desired distribution of "one" in a codeword. The third contribution considers two-way relay channels where the information exchange between two nodes takes place in two transmission phases using a coding scheme called physical-layer network coding. At the relay, a near optimal decoding strategy is derived using a list decoding algorithm, and an approximation is obtained by a joint decoding approach. For the latter scheme, an analytical approximation of the word error rate based on a union bounding technique is computed under the assumption that linear codes are employed at the two nodes exchanging data. Further, when the wireless channel is frequency selective, two decoding strategies at the relay are developed, namely, a near optimal decoding scheme implemented using list decoding, and a reduced complexity detection/decoding scheme utilizing a linear minimum mean squared error based detector followed by a network coded sequence decoder.
ContributorsBhat, Uttam (Author) / Duman, Tolga M. (Thesis advisor) / Tepedelenlioğlu, Cihan (Committee member) / Li, Baoxin (Committee member) / Zhang, Junshan (Committee member) / Arizona State University (Publisher)
Created2011
Description
This study examined attitudes and perspectives of classroom guitar students toward the reading of staff notation in music. The purpose of this qualitative research was to reveal these perceptions in the student's own words, and compare them to those of orchestra and band students of comparable experience. Forty-seven students from four suburban middle and high schools on the east coast were selected through purposeful sampling techniques. Research instruments included a Musical Background Questionnaire and a thirty-five question Student Survey. Follow-up interviews were conducted with students to clarify or expound upon collected data. Guitar, orchestra, and band teachers were interviewed in order to provide their perspectives on the issues discussed. The Student Survey featured a five-point Likert-type scale, which measured how much students agreed or disagreed with various statements pertaining to their feelings about music, note-reading, or their class at school. Collected data were coded and used to calculate mean scores, standard deviations, and percentages of students in agreement or disagreement with each statement. Interviews were audio recorded and transcribed into a word processing document for analysis. The study found that while a variety of perspectives exist within a typical guitar class, some students do not find note-reading to be necessary for the types of music they desire to learn. Other findings included a perceived lack of relevance toward the classical elements of the guitar programs in the schools, a lack of educational consistency between classroom curricula and private lesson objectives, and the general description of the struggle some guitarists experience with staff notation. Implications of the collected data were discussed, along with recommendations for better engaging these students.
ContributorsWard, Stephen Michael (Author) / Koonce, Frank (Thesis advisor) / Schmidt, Margaret (Thesis advisor) / Buck, Nancy (Committee member) / Rogers, Rodney (Committee member) / McLin, Katherine (Committee member) / Arizona State University (Publisher)
Created2011
Description
Bridging semantic gap is one of the fundamental problems in multimedia computing and pattern recognition. The challenge of associating low-level signal with their high-level semantic interpretation is mainly due to the fact that semantics are often conveyed implicitly in a context, relying on interactions among multiple levels of concepts or low-level data entities. Also, additional domain knowledge may often be indispensable for uncovering the underlying semantics, but in most cases such domain knowledge is not readily available from the acquired media streams. Thus, making use of various types of contextual information and leveraging corresponding domain knowledge are vital for effectively associating high-level semantics with low-level signals with higher accuracies in multimedia computing problems. In this work, novel computational methods are explored and developed for incorporating contextual information/domain knowledge in different forms for multimedia computing and pattern recognition problems. Specifically, a novel Bayesian approach with statistical-sampling-based inference is proposed for incorporating a special type of domain knowledge, spatial prior for the underlying shapes; cross-modality correlations via Kernel Canonical Correlation Analysis is explored and the learnt space is then used for associating multimedia contents in different forms; model contextual information as a graph is leveraged for regulating interactions among high-level semantic concepts (e.g., category labels), low-level input signal (e.g., spatial/temporal structure). Four real-world applications, including visual-to-tactile face conversion, photo tag recommendation, wild web video classification and unconstrained consumer video summarization, are selected to demonstrate the effectiveness of the approaches. These applications range from classic research challenges to emerging tasks in multimedia computing. Results from experiments on large-scale real-world data with comparisons to other state-of-the-art methods and subjective evaluations with end users confirmed that the developed approaches exhibit salient advantages, suggesting that they are promising for leveraging contextual information/domain knowledge for a wide range of multimedia computing and pattern recognition problems.
ContributorsWang, Zhesheng (Author) / Li, Baoxin (Thesis advisor) / Sundaram, Hari (Committee member) / Qian, Gang (Committee member) / Ye, Jieping (Committee member) / Arizona State University (Publisher)
Created2011
Description
Many of the works of Dominick Argento have been researched and analyzed, but his choral work Evensong: Of Love and Angels s has received limited attention thus far. Written in memoriam for his wife Carolyn Bailey Argento, Evensong draws its musical material from her initials C.B.A. These letters, translated into note names, form a conspicuous head motive that is present in each movement of the work, and it serves multiple functions: as a melodic feature, as the foundation for a twelve-tone row, and as a harmonic base. This paper provides an overview of the work's conception with specific relation to Argento's biographical details, compositional style, and work habits; a brief review of the critical reception of the work; and a succinct analysis of the form and cyclical materials found in each movement.
ContributorsPage, Carrie Leigh, 1980- (Author) / Rogers, Rodney (Thesis advisor) / DeMars, James (Committee member) / Levy, Benjamin (Committee member) / Oldani, Robert (Committee member) / Arizona State University (Publisher)
Created2011
Description
Everyday Arias for soprano and orchestra was composed largely in Arizona and completed in February 2011. The text was taken from a small collection of the composer's own poetry referencing her memories of life in rural Mississippi. Everyday Arias endeavors to elevate these prosaic experiences and settings to art, expressing the everyday as beautiful and worthy of artistic treatment. The primary compositional model for this work was Samuel Barber's Knoxville: Summer of 1915, but other influences included Charles Ives, Aaron Copland, Benjamin Britten, and Dominick Argento. Barber's and Argento's musical treatment of prose style seemed particularly appropriate to the goals of Everyday Arias. Ives and Copland used hymn tunes both to evoke certain associations of worship and as sources of interesting material. The vocal writing of all five composers was influential, but the orchestration techniques for winds are largely a product of studying Ives and Argento, while many string gestures are more obviously tied to Britten and - more historically - Debussy.The primary motive that weaves through the work features an ascending major second followed by a descending perfect fourth, in a long-short-long rhythmic pattern. As a melodic fragment, the motive is often inverted to a descending-ascending pattern, or distorted slightly by expanding the second interval to a perfect fifth, or used in retrograde. The motive was derived from the first measure of the melody "Toplady" (1830) by Thomas Hastings, better known as the hymn "Rock of Ages." In the first movement, the motive is used most frequently in sequences. The second movement treats the motive as a melodic element and as a unit in ostinati. The final movement humorously transforms it into a syncopated gesture to evoke ragtime.
ContributorsPage, Carrie Leigh (Composer) / Rogers, Rodney (Thesis advisor) / DeMars, James (Committee member) / Levy, Benjamin (Committee member) / Oldani, Robert (Committee member) / Arizona State University (Publisher)
Created2011