The DRUM digital repository system captures, stores, indexes, preserves, and distributes digital research material. http://drum.lib.umd.edu:80 2012-05-16T07:09:33Z 2012-05-16T07:09:33Z Seeler, Katie Cunningham, Maggie http://hdl.handle.net/1903/12482 2012-05-15T02:30:41Z 2012-05-01T00:00:00Z

Title: Library Safari and iPads: Technology to Enhance Student Learning: 2012 Update Authors: Seeler, Katie; Cunningham, Maggie Abstract: The Library Safari program at the University of Maryland Libraries aims at reducing freshmen anxiety about using a large and complex academic library system through exercises and teamwork. Every fall semester instructors who teach the orientation course UNIV 100, "The Student in the University," request this workshop for their students. Once scheduled, students come to a teaching lab in the main campus library and are given a brief introduction. Students are then divided into small teams and assigned a set of exercises to complete. These exercises, designed around the themes and ideas expressed in the First Year Book, teach students how to navigate the main library by learning: how it is organized, how to access its resources, know how to contact a librarian, and learn what public services are available. Printed sets of team exercises and hardwired library computers have traditionally been used to conduct this workshop. In fall 2011, librarians in User Education Services experimented by incorporating emerging technologies or iPads into the way students interfaced with the Libraries. At the conclusion of the fall semester, analysis was conducted to evaluate the students' experience with this mode of instruction. The positive feedback helped us determine the successes made by this modest blended learning approach. Additionally, it has informed us what changes should be made to improve this program of library instruction. Description: Poster presentation at the Innovations in Teaching and Learning Conference, April 26-27, 2012, University of Maryland, College Park and the Maryland Library Association & Delaware Library Association 2012 Joint Library Conference, May 9-12, 2012, Ocean City, Maryland.

2012-05-01T00:00:00Z Wright, Robert http://hdl.handle.net/1903/12481 2012-05-10T02:30:40Z 2010-01-01T00:00:00Z

Title: Evidence Based Collection Development Authors: Wright, Robert Abstract: Poster Evidence Based Collection Development Robert Wright, Health and Life Sciences Librarian University of Maryland Libraries, Shady Grove Introduction Numerous sources in the library literature address the theory and practice of collection development and management. These include monographs on the general principles of collection development (Johnson, 2009) (Evans & Saponaro, 2005), research evaluating collections using materials-based and usage-based methods (Ching & Chennupati, 2002) (Kao, Chang, & Lin, 2003), and research on decision support systems for collection development (Uzoka & Ijatuyi, 2005). This poster departs from previous studies by addressing collection development decision-making at the item level. It presents findings from a study of three evidence based methods applied to the acquisition of chemistry monographs (Wright, 2008). It describes these methods in detail, illustrates their practical application, reports how their efficacy was tested using circulation data, and outlines plans for further research. Methods Three evidence based methods were developed for the selection of chemistry monographs at the University of Houston (UH) Libraries: (1) the analysis of circulation statistics for related titles in the Libraries’ integrated library system (ILS), (2) Google-mediated searching of UH Chemistry Department web pages, and (3) searches in SciFinder Scholar limited to research done by UH faculty and graduate students. Two hundred and ninety-five (295) chemistry monographs were selected between 2005 and 2007 by applying these methods rigorously. The average circulation rate of this cohort of monographs was compared to the average circulation rate of 254 chemistry monographs selected between 2002 and 2004, when the methods were not used or were in an incomplete state of development. Results Circulations/month were on average 9% greater in the cohort of monographs selected with the rigorously-applied evidence based methods. Further statistical analysis, however, found that this apparent increase in circulation was due to natural variations in the rates of circulation among the two cohorts, and that the 9% increase could not be attributed to the different application of these methods. Conclusions While the methods described in this poster provide an evidence base for the selection of chemistry monographs, their application did not change circulation rates in a statistically significant way. Further research is needed to determine if this lack of statistical significance is real or if it is a product of the organic development and application of these methods over time, which might make definitive comparisons difficult. Further Research The evidence based methods described above were developed and perfected incrementally over time, thus making it difficult to determine with certainty the degree to which the methods were applied at different points in time between 2002 and 2007. A different strategy is now being undertaken which compares evidence based selection methods that are fully developed and distinct. These selection methods reflect the unique environment of the Universities at Shady Grove (USG), an institution with a primarily teaching focus that supports programs from nine separate universities: Bowie State University; Salisbury University; Towson University; the University of Baltimore; the University of Maryland, Baltimore; the University of Maryland, Baltimore County; the University of Maryland, College Park; the University of Maryland Eastern Shore; and the University of Maryland University College. The methods also reflect monograph selection in a broad range of disciplines outside of chemistry, including biology, nursing, pharmacy, psychology, public health, respiratory therapy, and social work. These circumstances mean that a straightforward, Google-mediated search is not possible. They also mean that searching SciFinder Scholar for faculty and graduate student research is not relevant to monograph selection decisions. In this new setting, the evidence based selection methods that will be used and compared are (1) the analysis of circulation statistics for related titles in the Library’s ILS, (2) using course descriptions and other documents from online searches of the web sites of USG and its nine partner institutions, and (3) faculty input on selection decisions. Instead of using methods as they are being developed and refined, methods that are fully developed will be used. Instead of testing the impact on monograph circulation of the combined use of all the methods, each method will be tested individually to determine its impact on circulation. In this way, the difficulty of making a definitive case for the value of selection methods should be overcome. References Ching, J. T. Y., & Chennupati, K. R. (2002). Collection evaluation through citation analysis techniques: A case study of the Ministry of Education, Singapore. Library Review 51(8), 398-405. Evans, G. E., & Saponaro, M. Z. (2005). Developing library and information center collections (5th ed.). Westport, CT: Libraries Unlimited. Johnson, P. (2009). Fundamentals of collection development and management (2nd ed.). Chicago, IL: American Library Association. Kao, S. C., Chang, H. C., & Lin, C. H. (2003). Decision support for the academic library acquisition budget allocation via circulation database mining. Information Processing and Management 39(1), 133-147. Uzoka, F.M.E., and Ijatuyi, O. A. (2005). Decision support system for library acquisitions: A framework. The Electronic Library 23(4), 453-462. Wright, R. A. (2008). Three evidence based methods to compensate for a lack of subject background when ordering chemistry monographs. Evidence Based Library and Information Practice, 3(3), 3-17. Retrieved from http://ejournals.library.ualberta.ca/index.php/EBLIP/article/view/1192/3359

2010-01-01T00:00:00Z Matei, Ion Baras, John http://hdl.handle.net/1903/12480 2012-05-05T02:30:47Z 2012-05-04T00:00:00Z

Title: A performance comparison between two consensus-based distributed optimization algorithms Authors: Matei, Ion; Baras, John Abstract: In this paper we address the problem of multi-agent optimization for convex functions expressible as sums of convex functions. Each agent has access to only one function in the sum and can use only local information to update its current estimate of the optimal solution. We consider two consensus-based iterative algorithms, based on a combination between a consensus step and a subgradient decent update. The main difference between the two algorithms is the order in which the consensus-step and the subgradient descent update are performed. We show that updating first the current estimate in the direction of a subgradient and then executing the consensus step ensures better performance than executing the steps in reversed order. In support of our analytical results, we give some numerical simulations of the algorithms as well.

2012-05-04T00:00:00Z Ion, Matei Assane, Gueye John, Baras http://hdl.handle.net/1903/12479 2012-05-05T02:30:44Z 2012-02-01T00:00:00Z

Title: Flow Control in Time-Varying, Random Supply Chains Authors: Ion, Matei; Assane, Gueye; John, Baras Abstract: Today’s supply chains are more and more complex. They depend on a network of independent, yet interconnected moving parts. They rely on critical infrastructures and experience a lot of time variability and randomness. Designing strategies that deal with such constantly changing supply chains is necessary in this increasingly globalized economy where supply chain disruptions have impacts that propagate not only locally but also globally. In this paper we propose a randomized flow control algorithm for a time varying, random supply chain network. We formulate a constrained stochastic optimization problem that maximizes the profit function in terms of the long-run, time-average rates of the flows in the supply chain. We show that our algorithm, which is based on queueing theory and stochastic analysis concepts, can get arbitrarily close to the solution of the aforementioned optimization problem. In addition, we describe how the flow control algorithm can be extended to a multiple firms supply chain setup and present numerical simulations of our algorithm for different supply chain topologies.

2012-02-01T00:00:00Z