RACHMANINOFF AND MEDTNER: SELECTED WORKS FROM THE SOLO AND COLLABORATIVE PIANO REPERTOIRE

Sergei Rachmaninoff and Nikolai Medtner occupy a special place in the history of Russian music. Both composers were exceptional pianists and left us some of the greatest works in the piano repertoire. Although these composers shared many similarities, and were often compared, their musical languages and views on composition were very different. Unfortunately, Medtner’s music, which Rachmaninoff admired greatly, has remained neglected for several generations of performers and listeners. In my dissertation I will explore the similarities and contrasts in Rachmaninoff’s and Medtner’s music. Through these performances, I hope to encourage other musicians to discover the imaginative power of Medtner’s music. Of course, no such encouragement is needed for Rachmaninoff’s extremely popular music; however, the technical and musical challenges of performing that repertoire are an invaluable part of every pianist’s education. This dissertation project was presented in three recitals which were performed in Gildenhorn Recital Hall at the Clarice Smith Performing Arts Center of the University of Maryland on May 8, 2014, December 5, 2014 and March 21, 2016. The following pieces comprised the survey of Rachmaninoff music: Vocalise Op. 34, Variations on a Theme of Corelli Op. 42, Piano Concerto No 2 Op. 18, Selected Songs Opp. 4 and 8, and two Moments Musicaux Op. 16 - Nos 3 and 4. The following pieces were included to represent Medtner: Sonata for Violin and Piano Op. 57 in E minor “Epica”, Fairy Tales for solo piano Op. 20 No 1, Op. 26 No 3 and Op. 51 No 1, and Selected Songs Op. 6 and 15. My partners in this project were Lilly Ahn, soprano, Jennifer Lee, violin and Nadezhda Christova, piano. All three recitals can be found in the Digital Repository at the University of Maryland (DRUM).

Analyzing Stories from Canadian Academic Writing Instructors: A Collaborative Autoethnography

Writing instruction in Canadian universities takes a variety of forms. While there are few formal departments for writing studies, many institutions do have a writing centre – a place that offers writing instruction to varying degrees. The writing centre may be housed within a department, a library, or within a student services unit. Its position within a university may indicate the degree to which writing is valued by the administrative body. The goal of our paper is to share insights into the ways that writing professionals perceive, work in, and adapt to current demands for writing instruction in higher education. Using a collaborative ethnographic approach, three scholars at different career stages explore their experiences with writing centre work. Using data consisting of individually written reflections, our analysis revealed four major themes: (a) initial experience with writing centres, (b) community, (c) frustrations and tensions at work, and (d) mentorship. In this paper, we discuss our findings within the framework of positioning theory in order to understand how we position ourselves as scholars, mentors, and educators, and how we are positioned by others within the fields of writing studies and higher education. This study raises awareness about the value of writing centre professionals’ contributions, the place of mentorship within higher education, and the support required for continued writing centre work.

EMMA 2--a MAGE-compliant system for the collaborative analysis and integration of microarray data

Background: Understanding transcriptional regulation by genome-wide microarray studies can contribute to unravel complex relationships between genes. Attempts to standardize the annotation of microarray data include the Minimum Information About a Microarray Experiment (MIAME) recommendations, the MAGE-ML format for data interchange, and the use of controlled vocabularies or ontologies. The existing software systems for microarray data analysis implement the mentioned standards only partially and are often hard to use and extend. Integration of genomic annotation data and other sources of external knowledge using open standards is therefore a key requirement for future integrated analysis systems. Results: The EMMA 2 software has been designed to resolve shortcomings with respect to full MAGE-ML and ontology support and makes use of modern data integration techniques. We present a software system that features comprehensive data analysis functions for spotted arrays, and for the most common synthesized oligo arrays such as Agilent, Affymetrix and NimbleGen. The system is based on the full MAGE object model. Analysis functionality is based on R and Bioconductor packages and can make use of a compute cluster for distributed services. Conclusion: Our model-driven approach for automatically implementing a full MAGE object model provides high flexibility and compatibility. Data integration via SOAP-based web-services is advantageous in a distributed client-server environment as the collaborative analysis of microarray data is gaining more and more relevance in international research consortia. The adequacy of the EMMA 2 software design and implementation has been proven by its application in many distributed functional genomics projects. Its scalability makes the current architecture suited for extensions towards future transcriptomics methods based on high-throughput sequencing approaches which have much higher computational requirements than microarrays.

Collaborative Filtering with Semantic Neighbour Discovery

Nearest neighbour collaborative filtering (NNCF) algorithms are commonly used in multimedia recommender systems to suggest media items based on the ratings of users with similar preferences. However, the prediction accuracy of NNCF algorithms is affected by the reduced number of items – the subset of items co-rated by both users – typically used to determine the similarity between pairs of users. In this paper, we propose a different approach, which substantially enhances the accuracy of the neighbour selection process – a user-based CF (UbCF) with semantic neighbour discovery (SND). Our neighbour discovery methodology, which assesses pairs of users by taking into account all the items rated at least by one of the users instead of just the set of co-rated items, semantically enriches this enlarged set of items using linked data and, finally, applies the Collinearity and Proximity Similarity metric (CPS), which combines the cosine similarity with Chebyschev distance dissimilarity metric. We tested the proposed SND against the Pearson Correlation neighbour discovery algorithm off-line, using the HetRec data set, and the results show a clear improvement in terms of accuracy and execution time for the predicted recommendations.

Cultivating Collaborative Relationships: A Case Study of Teacher Collaboration and Professional Development

Students often receive instruction from specialists, professionals other than their general educators, such as special educators, reading specialists, and ESOL (English Speakers of Other Languages) teachers. The purpose of this study was to examine how general educators and specialists develop collaborative relationships over time within the context of receiving professional development. While collaboration is considered essential to increasing student achievement, improving teachers’ practice, and creating comprehensive school reform, collaborative partnerships take time to develop and require multiple sources of support. Additionally, both practitioners and researchers often conflate collaboration with structural reforms such as co-teaching. This study used a retrospective single case study with a grounded theory approach to analysis. Data were collected through semi-structured interviews with thirteen teachers and an administrator after three workshops were conducted throughout the school year. The theory, Cultivating Interprofessional Collaboration, describes how interprofessional relationships grow as teachers engage in a cycle of learning, constructing partnership, and reflecting. As relationships deepen some partners experience a seamless dimension to their work. A variety of intrapersonal, interpersonal, and external factors work in concert to promote this growth, which is strengthened through professional development. In this theory, professional development provides a common ground for strengthening relationships, knowledge about the collaborative process, and a reflective space to create new collaborative practices. Effective collaborative practice can lead to aligned instruction and teachers’ own professional growth. This study has implications for school interventions, professional development, and future research on collaboration in schools.

Applying Platform Design to Improve Product-Service Systems Collaborative Development

Part 3: Product-Service Systems

Bioqueries: a collaborative environment to create, explore and share SPARQL queries in Life Sciences

Bioqueries provides a collaborative environment to create, explore, execute, clone and share SPARQL queries (including Federated Queries). Federated SPARQL queries can retrieve information from more than one data source.

Collaborative Systems for Smart Networked Environments

International audience

Integration of Social Concerns in Collaborative Logistics and Transportation Networks

Part 21: Mobility and Logistics

A Collaborative IT Network for Three Adriatic Maritime Ports

Part 21: Mobility and Logistics

Collaborative Management of Intermodal Mobility

Part 21: Mobility and Logistics

An AAL Collaborative System: The AAL4ALL and a Mobile Assistant Case Study

Part 20: Health and Care Networks

Bioqueries: a collaborative environment to create, explore and share SPARQL queries in Life Sciences

Bioqueries provides a collaborative environment to create, explore, execute, clone and share SPARQL queries (including Federated Queries). Federated SPARQL queries can retrieve information from more than one data source.

Forms of Collaboration in Collaborative Enterprises: An Ontological Model

Part 19: Knowledge Management in Networks