An analysis of completeness and historical accuracy in the most commonly used college jazz history texts

Historical accuracy is only one of the components of a scholarly college textbook used to teach the history of jazz music. Textbooks in this field should include accurate ethnic representation of the most important musical figures as jazz is considered the only original American art form. As college and universities celebrate diversity, it is important that jazz history be accurate and complete. ^ The purpose of this study was to examine the content of the most commonly used jazz history textbooks currently used at American colleges and universities. This qualitative study utilized grounded and textual analysis to explore the existence of ethnic representation in these texts. The methods used were modeled after the work of Kane and Selden each of whom conducted a content analysis focused on a limited field of study. This study is focused on key jazz artists and composers whose work was created in the periods of early jazz (1915-1930), swing (1930-1945) and modern jazz (1945-1960). ^ This study considered jazz notables within the texts in terms of ethnic representation, authors' use of language, contributions to the jazz canon, and place in the standard jazz repertoire. Appropriate historical sections of the selected texts were reviewed and coded using predetermined rubrics. Data were then aggregated into categories and then analyzed according to the character assigned to the key jazz personalities noted in the text as well as the comparative standing afforded each personality. ^ The results of this study demonstrate that particular key African-American jazz artists and composers occupy a significant place in these texts while other significant individuals representing other ethnic groups are consistently overlooked. This finding suggests that while America and the world celebrates the quality of the product of American jazz as great musically and significant socially, many ethnic contributors are not mentioned with the result being a less than complete picture of the evolution of this American art form. ^

Spatial-temporal mining of archived automatic vehicle location (AVL) data for transit service planning applications

An Automatic Vehicle Location (AVL) system is a computer-based vehicle tracking system that is capable of determining a vehicle's location in real time. As a major technology of the Advanced Public Transportation System (APTS), AVL systems have been widely deployed by transit agencies for purposes such as real-time operation monitoring, computer-aided dispatching, and arrival time prediction. AVL systems make a large amount of transit performance data available that are valuable for transit performance management and planning purposes. However, the difficulties of extracting useful information from the huge spatial-temporal database have hindered off-line applications of the AVL data. ^ In this study, a data mining process, including data integration, cluster analysis, and multiple regression, is proposed. The AVL-generated data are first integrated into a Geographic Information System (GIS) platform. The model-based cluster method is employed to investigate the spatial and temporal patterns of transit travel speeds, which may be easily translated into travel time. The transit speed variations along the route segments are identified. Transit service periods such as morning peak, mid-day, afternoon peak, and evening periods are determined based on analyses of transit travel speed variations for different times of day. The seasonal patterns of transit performance are investigated by using the analysis of variance (ANOVA). Travel speed models based on the clustered time-of-day intervals are developed using important factors identified as having significant effects on speed for different time-of-day periods. ^ It has been found that transit performance varied from different seasons and different time-of-day periods. The geographic location of a transit route segment also plays a role in the variation of the transit performance. The results of this research indicate that advanced data mining techniques have good potential in providing automated techniques of assisting transit agencies in service planning, scheduling, and operations control. ^

Actionable pattern analysis in computing and business intelligence systems

With advances in science and technology, computing and business intelligence (BI) systems are steadily becoming more complex with an increasing variety of heterogeneous software and hardware components. They are thus becoming progressively more difficult to monitor, manage and maintain. Traditional approaches to system management have largely relied on domain experts through a knowledge acquisition process that translates domain knowledge into operating rules and policies. It is widely acknowledged as a cumbersome, labor intensive, and error prone process, besides being difficult to keep up with the rapidly changing environments. In addition, many traditional business systems deliver primarily pre-defined historic metrics for a long-term strategic or mid-term tactical analysis, and lack the necessary flexibility to support evolving metrics or data collection for real-time operational analysis. There is thus a pressing need for automatic and efficient approaches to monitor and manage complex computing and BI systems. To realize the goal of autonomic management and enable self-management capabilities, we propose to mine system historical log data generated by computing and BI systems, and automatically extract actionable patterns from this data. This dissertation focuses on the development of different data mining techniques to extract actionable patterns from various types of log data in computing and BI systems. Four key problems—Log data categorization and event summarization, Leading indicator identification , Pattern prioritization by exploring the link structures , and Tensor model for three-way log data are studied. Case studies and comprehensive experiments on real application scenarios and datasets are conducted to show the effectiveness of our proposed approaches.

User-centric music information retrieval

The rapid growth of the Internet and the advancements of the Web technologies have made it possible for users to have access to large amounts of on-line music data, including music acoustic signals, lyrics, style/mood labels, and user-assigned tags. The progress has made music listening more fun, but has raised an issue of how to organize this data, and more generally, how computer programs can assist users in their music experience. An important subject in computer-aided music listening is music retrieval, i.e., the issue of efficiently helping users in locating the music they are looking for. Traditionally, songs were organized in a hierarchical structure such as genre->artist->album->track, to facilitate the users’ navigation. However, the intentions of the users are often hard to be captured in such a simply organized structure. The users may want to listen to music of a particular mood, style or topic; and/or any songs similar to some given music samples. This motivated us to work on user-centric music retrieval system to improve users’ satisfaction with the system. The traditional music information retrieval research was mainly concerned with classification, clustering, identification, and similarity search of acoustic data of music by way of feature extraction algorithms and machine learning techniques. More recently the music information retrieval research has focused on utilizing other types of data, such as lyrics, user-access patterns, and user-defined tags, and on targeting non-genre categories for classification, such as mood labels and styles. This dissertation focused on investigating and developing effective data mining techniques for (1) organizing and annotating music data with styles, moods and user-assigned tags; (2) performing effective analysis of music data with features from diverse information sources; and (3) recommending music songs to the users utilizing both content features and user access patterns.

An analysis of five original compositions

The purpose of this thesis is to analyze in detail five original compositions, each written for the performance of these pieces on March 14, 2009 for a Master's recital. In order to maintain a certain level of musical continuity among these compositions, each was created in such a way as to possess similar musical characteristics of melodic and harmonic structure. These similarities are also reflected within the overall arrangement of each composition and use of instrumentation as well. The following pages will analyze each of these compositions in accordance with several important musical factors. These elements are form and chord analysis, melodic and harmonic content, and meter and rhythm. The author's original scores are included in the appendix.

Zoroastrianism, Cosmology, and Chaos: A Detailed Analysis of the Musical Composition, Druj Aeterni

Druj Aeterni is a large chamber ensemble piece for flute, clarinet, French horn, two trumpets, piano, two percussionists, string quintet, and electric bass. My composition integrates three intellectual pursuits and interests, ancient mythology, cosmology, and mathematics. The title of the piece uses Latin and the language of the Avesta, the holy book of Zoroastrianism, and comments upon a philosophical perspective based in string theory. I abstract the cosmological implications of string theory, apply them to the terminology and theology of Zoroastrianism, and then structure the composition in consideration of a possible reconciliation. The analysis that follows incorporates analytical techniques similar to David Cope’s style of Vectoral Analysis.

An in-depth analysis of original compositions

The purpose of this thesis is two-fold. It presents six original pieces composed and arranged by the author, and it provides a thorough analysis of each. The compositions draw from many different musical genres: contemporary jazz, swing, funk, fusion, soul, neo-soul, and rhythm and blues. The applications of melodic, harmonic, and rhythmic techniques derived from these genres can be found in these original compositions. These compositions are inspired by -- and attempt to narrate --life experiences. Parallels between life and music are drawn and explained. By way of introduction, some information is given regarding the ensemble that first performed these original compositions. The ensemble comprised trumpet, tenor saxophone, keyboards, piano, electric bass, upright acoustic bass, drums, and percussion.

Exploring Armenian keyboard music : roots to modern times

The extended program notes include historical facts of the composers and characteristics of the pieces being performed. The thesis also includes information about Armenian composers starting from 18th to the 20th century, composition's historical background, brief biographies of the composers as well as analysis of form and structure. The graduate piano recital comprised the following compositions: Sayat Nova - R. Andriasian Yes Mi Kharib Blbuli Pes; Komitas - R. Andriasian Garun a, Shoker Jan, Dzirani Dzar, Gakavik; A. Khachaturyan Poem; A. Babadjanyan Elegy in Commemoration of A. Khachaturyan; E. Bagdasarian Humoresque, Prelude in D Minor, Prelude in B Minor; A. Babadjanyan Improvisation and Traditional from six Pictures; A. Babadjanyan Prelude and Vagarshapat Dance; A. Arutyunian Dance of Sasoon; A. Arutyunian - A. Babadjanyan Armenian Rhapsody for Two Pianos.