THE FEASIBILITY OF USING WEB-BASED TECHNOLOGY FOR THE MANAGEMENT OF DREDGING PROJECTS

The research investigates the feasibility of using web-based project management systems for dredging. To achieve this objective the research assessed both the positive and negative aspects of using web-based technology for the management of dredging projects. Information gained from literature review and prior investigations of dredging projects revealed that project performance, social, political, technical, and business aspects of the organization were important factors in deciding to use web-based systems for the management of dredging projects. These factors were used to develop the research assumptions. An exploratory case study methodology was used to gather the empirical evidence and perform the analysis. An operational prototype of the system was developed to help evaluate developmental and functional requirements, as well as the influence on performance, and on the organization. The evidence gathered from three case study projects, and from a survey of 31 experts, were used to validate the assumptions. Baselines, representing the assumptions, were created as a reference to assess the responses and qualitative measures. The deviation of the responses was used to evaluate for the analysis. Finally, the conclusions were assessed by validating the assumptions with the evidence, derived from the analysis. The research findings are as follows: 1. The system would help improve project performance. 2. Resistance to implementation may be experienced if the system is implemented. Therefore, resistance to implementation needs to be investigated further and more R&D work is needed in order to advance to the final design and implementation. 3. System may be divided into standalone modules in order to simplify the system and facilitate incremental changes. 4. The QA/QC conceptual approach used by this research needs to be redefined during future R&D to satisfy both owners and contractors. Yin (2009) Case Study Research Design and Methods was used to develop the research approach, design, data collection, and analysis. Markus (1983) Resistance Theory was used during the assumptions definition to predict potential problems to the implementation of web-based project management systems for the dredging industry. Keen (1981) incremental changes and facilitative approach tactics were used as basis to classify solutions, and how to overcome resistance to implementation of the web-based project management system. Davis (1989) Technology Acceptance Model (TAM) was used to assess the solutions needed to overcome the resistances to the implementation of web-base management systems for dredging projects.

Digital Conversion and Media Reformatting: Management and Production of Digital Collections

The Digital Conversion and Media Reformatting plan was written in 2012 and revised 2013-2014, as a five-year plan for the newly established department at the University of Maryland Libraries under the Digital Systems and Stewardship Division. The plan focuses on increasing digitization production, both in-house and through vendors, and creates a model for the management of this production.

A Thermal Management Solution for Compact Power Converters

Regulated Transformer Rectifier Units contain several power electronic boards to facilitate AC to DC power conversion. As these units become smaller, the number of devices on each board increases while their distance from each other decreases, making active cooling essential to maintaining reliable operation. Although it is widely accepted that liquid is a far superior heat transfer medium to air, the latter is still capable of yielding low device operating temperatures with proper heat sink and airflow design. The purpose of this study is to describe the models and methods used to design and build the thermal management system for one of the power electronic boards in a compact, high power regulated transformer rectifier unit. Maximum device temperature, available pressure drop and manufacturability were assessed when selecting the final design for testing. Once constructed, the thermal management system’s performance was experimentally verified at three different power levels.

Untangling Knots: Determining E-book Suitability for Course Reserves

E-books on their own are complex; they become even more so in the context of course reserves. In FY2016 the Resource Sharing & Reserves and Acquisitions units developed a new workflow for vetting requested e-books to ensure that they were suitable for course reserves (i.e. they permit unlimited simultaneous users) before posting links to them within the university’s online learning management system. In the Spring 2016 semester 46 e-books were vetted through this process, resulting in 18 purchases. Preliminary data analysis sheds light on the suitability of the Libraries’ current e-book collections for course reserves as well as faculty preferences, with potential implications for the Libraries’ ordering process. We hope this lightening talk will generate discussion about these issues among selectors, collection managers, and reserves staff alike.

SPACE-DEPLOYED, THIN-WALLED ENCLOSURE FOR A CRYOGENICALLY-COOLED HIGH TEMPERATURE SUPERCONDUCTING COIL

The interaction of magnetic fields generated by large superconducting coils has multiple applications in space, including actuation of spacecraft or spacecraft components, wireless power transfer, and shielding of spacecraft from radiation and high energy particles. These applications require coils with major diameters as large as 20 meters and a thermal management system to maintain the superconducting material of the coil below its critical temperature. Since a rigid thermal management system, such as a heat pipe, is unsuitable for compact stowage inside a 5 meter payload fairing, a thin-walled thermal enclosure is proposed. A 1.85 meter diameter test article consisting of a bladder layer for containing chilled nitrogen vapor, a restraint layer, and multilayer insulation was tested in a custom toroidal vacuum chamber. The material properties found during laboratory testing are used to predict the performance of the test article in low Earth orbit. Deployment motion of the same test article was measured using a motion capture system and the results are used to predict the deployment in space. A 20 meter major diameter and coil current of 6.7 MA is selected as a point design case. This design point represents a single coil in a high energy particle shielding system. Sizing of the thermal and structural components of the enclosure is completed. The thermal and deployment performance is predicted.

Generating Discriminative Objective Proposals via Submodular Ranking

Object recognition has long been a core problem in computer vision. To improve object spatial support and speed up object localization for object recognition, generating high-quality category-independent object proposals as the input for object recognition system has drawn attention recently. Given an image, we generate a limited number of high-quality and category-independent object proposals in advance and used as inputs for many computer vision tasks. We present an efficient dictionary-based model for image classification task. We further extend the work to a discriminative dictionary learning method for tensor sparse coding. In the first part, a multi-scale greedy-based object proposal generation approach is presented. Based on the multi-scale nature of objects in images, our approach is built on top of a hierarchical segmentation. We first identify the representative and diverse exemplar clusters within each scale. Object proposals are obtained by selecting a subset from the multi-scale segment pool via maximizing a submodular objective function, which consists of a weighted coverage term, a single-scale diversity term and a multi-scale reward term. The weighted coverage term forces the selected set of object proposals to be representative and compact; the single-scale diversity term encourages choosing segments from different exemplar clusters so that they will cover as many object patterns as possible; the multi-scale reward term encourages the selected proposals to be discriminative and selected from multiple layers generated by the hierarchical image segmentation. The experimental results on the Berkeley Segmentation Dataset and PASCAL VOC2012 segmentation dataset demonstrate the accuracy and efficiency of our object proposal model. Additionally, we validate our object proposals in simultaneous segmentation and detection and outperform the state-of-art performance. To classify the object in the image, we design a discriminative, structural low-rank framework for image classification. We use a supervised learning method to construct a discriminative and reconstructive dictionary. By introducing an ideal regularization term, we perform low-rank matrix recovery for contaminated training data from all categories simultaneously without losing structural information. A discriminative low-rank representation for images with respect to the constructed dictionary is obtained. With semantic structure information and strong identification capability, this representation is good for classification tasks even using a simple linear multi-classifier.