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.

Legacy Resource Management Program Archaeological Reconnaissance Survey, United States Naval Academy, Annapolis, MD.

The Archaeological Reconnaissance Survey of United States Naval Academy will provide the Navy with a rich understanding of the history of this property. A National Register of Historic Places District, such as the Academy, deserves a thorough analysis of its past, in order to preserve what exists and to plan for the future. The goal of this project is to investigate the history of the Academy through traditional historic research, innovative computer analysis of historic maps, oral history interviews, and tract histories. This information has been synthesized to provide the Navy with a planning tool for Public Works, a concise look at the cartographic history of the Academy, and reference manual of the vast amounts of information which have been gathered during the course of this project. This information can serve as a reference tool to help the Public Works department comply with Section 106 regulations of the Historic Sites Preservation Act, with regard to construction. It can also serve as a source of cartographic history for those interested in the Academy's physical development, and as a way of preserving the culture of residents in Annapolis. This program and archaeological survey will ultimately serve to add to the rich history of the United States Naval Academy while preserving an important part of our nation's heritage.

Implementation of customer relationship management and inventory control software: a multiple case study of small retailers

Gemstone Team Small Business Solutions

BUILDING EFFICIENT AND COST-EFFECTIVE CLOUD-BASED BIG DATA MANAGEMENT SYSTEMS

In today’s big data world, data is being produced in massive volumes, at great velocity and from a variety of different sources such as mobile devices, sensors, a plethora of small devices hooked to the internet (Internet of Things), social networks, communication networks and many others. Interactive querying and large-scale analytics are being increasingly used to derive value out of this big data. A large portion of this data is being stored and processed in the Cloud due the several advantages provided by the Cloud such as scalability, elasticity, availability, low cost of ownership and the overall economies of scale. There is thus, a growing need for large-scale cloud-based data management systems that can support real-time ingest, storage and processing of large volumes of heterogeneous data. However, in the pay-as-you-go Cloud environment, the cost of analytics can grow linearly with the time and resources required. Reducing the cost of data analytics in the Cloud thus remains a primary challenge. In my dissertation research, I have focused on building efficient and cost-effective cloud-based data management systems for different application domains that are predominant in cloud computing environments. In the first part of my dissertation, I address the problem of reducing the cost of transactional workloads on relational databases to support database-as-a-service in the Cloud. The primary challenges in supporting such workloads include choosing how to partition the data across a large number of machines, minimizing the number of distributed transactions, providing high data availability, and tolerating failures gracefully. I have designed, built and evaluated SWORD, an end-to-end scalable online transaction processing system, that utilizes workload-aware data placement and replication to minimize the number of distributed transactions that incorporates a suite of novel techniques to significantly reduce the overheads incurred both during the initial placement of data, and during query execution at runtime. In the second part of my dissertation, I focus on sampling-based progressive analytics as a means to reduce the cost of data analytics in the relational domain. Sampling has been traditionally used by data scientists to get progressive answers to complex analytical tasks over large volumes of data. Typically, this involves manually extracting samples of increasing data size (progressive samples) for exploratory querying. This provides the data scientists with user control, repeatable semantics, and result provenance. However, such solutions result in tedious workflows that preclude the reuse of work across samples. On the other hand, existing approximate query processing systems report early results, but do not offer the above benefits for complex ad-hoc queries. I propose a new progressive data-parallel computation framework, NOW!, that provides support for progressive analytics over big data. In particular, NOW! enables progressive relational (SQL) query support in the Cloud using unique progress semantics that allow efficient and deterministic query processing over samples providing meaningful early results and provenance to data scientists. NOW! enables the provision of early results using significantly fewer resources thereby enabling a substantial reduction in the cost incurred during such analytics. Finally, I propose NSCALE, a system for efficient and cost-effective complex analytics on large-scale graph-structured data in the Cloud. The system is based on the key observation that a wide range of complex analysis tasks over graph data require processing and reasoning about a large number of multi-hop neighborhoods or subgraphs in the graph; examples include ego network analysis, motif counting in biological networks, finding social circles in social networks, personalized recommendations, link prediction, etc. These tasks are not well served by existing vertex-centric graph processing frameworks whose computation and execution models limit the user program to directly access the state of a single vertex, resulting in high execution overheads. Further, the lack of support for extracting the relevant portions of the graph that are of interest to an analysis task and loading it onto distributed memory leads to poor scalability. NSCALE allows users to write programs at the level of neighborhoods or subgraphs rather than at the level of vertices, and to declaratively specify the subgraphs of interest. It enables the efficient distributed execution of these neighborhood-centric complex analysis tasks over largescale graphs, while minimizing resource consumption and communication cost, thereby substantially reducing the overall cost of graph data analytics in the Cloud. The results of our extensive experimental evaluation of these prototypes with several real-world data sets and applications validate the effectiveness of our techniques which provide orders-of-magnitude reductions in the overheads of distributed data querying and analysis in the Cloud.

ENGINEERING DIGITAL SHARING PLATFORM TO CREATE SOCIAL CONTAGION: EVIDENCE FROM LARGE SCALE RANDOMIZED FIELD EXPERIMENTS

Peer-to-peer information sharing has fundamentally changed customer decision-making process. Recent developments in information technologies have enabled digital sharing platforms to influence various granular aspects of the information sharing process. Despite the growing importance of digital information sharing, little research has examined the optimal design choices for a platform seeking to maximize returns from information sharing. My dissertation seeks to fill this gap. Specifically, I study novel interventions that can be implemented by the platform at different stages of the information sharing. In collaboration with a leading for-profit platform and a non-profit platform, I conduct three large-scale field experiments to causally identify the impact of these interventions on customers’ sharing behaviors as well as the sharing outcomes. The first essay examines whether and how a firm can enhance social contagion by simply varying the message shared by customers with their friends. Using a large randomized field experiment, I find that i) adding only information about the sender’s purchase status increases the likelihood of recipients’ purchase; ii) adding only information about referral reward increases recipients’ follow-up referrals; and iii) adding information about both the sender’s purchase as well as the referral rewards increases neither the likelihood of purchase nor follow-up referrals. I then discuss the underlying mechanisms. The second essay studies whether and how a firm can design unconditional incentive to engage customers who already reveal willingness to share. I conduct a field experiment to examine the impact of incentive design on sender’s purchase as well as further referral behavior. I find evidence that incentive structure has a significant, but interestingly opposing, impact on both outcomes. The results also provide insights about senders’ motives in sharing. The third essay examines whether and how a non-profit platform can use mobile messaging to leverage recipients’ social ties to encourage blood donation. I design a large field experiment to causally identify the impact of different types of information and incentives on donor’s self-donation and group donation behavior. My results show that non-profits can stimulate group effect and increase blood donation, but only with group reward. Such group reward works by motivating a different donor population. In summary, the findings from the three studies will offer valuable insights for platforms and social enterprises on how to engineer digital platforms to create social contagion. The rich data from randomized experiments and complementary sources (archive and survey) also allows me to test the underlying mechanism at work. In this way, my dissertation provides both managerial implication and theoretical contribution to the phenomenon of peer-to-peer information sharing.

UNDERSTANDING THE RELATIONSHIP BETWEEN THE BROWN MARMORATED STINK BUG, HALYOMORPHA HALYS (STÅL), AND ITS SYMBIONT, PANTOEA CARBEKII, WITH IMPLICATIONS FOR STINK BUG MANAGEMENT

Symbiotic relationships between insects and beneficial microbes are very common in nature, especially within the Hemiptera. The brown marmorated stink bug, Halyomorpha halys Stål, harbors a symbiont, Pantoea carbekii, within the fourth region of the midgut in specialized crypts. In this dissertation, I explored this insect- microbe relationship. I determined that the brown marmorated stink bug is heavily reliant on its symbiont, and that experimental removal of the symbiont from the egg mass surface prior to nymphal acquisition led to lower survival, longer development, lower fecundity, and aberrant nymphal behavior. Additionally, I determined that even when the symbiont is acquired and housed in the midgut crypts, it is susceptible to stressors. Stink bugs reared at a higher temperature showed lower survival, longer development, and a cease in egg mass production, and when bugs were screened for their symbiont, fewer had successfully retained it while under heat stress. Finally, with the knowledge that the stink bug suffers decreases in fitness when its symbiont is missing or stressed, I wanted to determine if targeting the symbiont was a possible management technique for the stink bug. I tested the efficacy of a number of different insecticidal and antimicrobial products to determine whether prevention of symbiont acquisition from the egg mass was possible, and results indicated that transmission of the symbiont from the egg mass to the newly hatched nymph was negatively impacted when certain products were applied (namely surfactants or products containing surfactants). Additionally, direct effects on hatch rate and survival were reported for certain products, namely the insect growth regulator azadirachtin, which suggests that nymphs can pick up residues from the egg mass surface while probing for the symbiont. I conclude that P. carbekii plays a critically important role in the survival of its host, the brown marmorated stink bug, and its presence on the egg mass surface before nymphal hatch makes it targetable as a potential management technique.

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.

THE DISTRIBUTION AND FUNCTION OF DENITRIFICATION GENES: EXPLORING AGRICULTURAL MANAGEMENT AND SOIL CHEMICAL IMPLICATIONS

Denitrification is a microbially-mediated process that converts nitrate (NO3-) to dinitrogen (N2) gas and has implications for soil fertility, climate change, and water quality. Using PCR, qPCR, and T-RFLP, the effects of environmental drivers and land management on the abundance and composition of functional genes were investigated. Environmental variables affecting gene abundance were soil type, soil depth, nitrogen concentrations, soil moisture, and pH, although each gene was unique in its spatial distribution and controlling factors. The inclusion of microbial variables, specifically genotype and gene abundance, improved denitrification models and highlights the benefit of including microbial data in modeling denitrification. Along with some evidence of niche selection, I show that nirS is a good predictor of denitrification enzyme activity (DEA) and N2O:N2 ratio, especially in alkaline and wetland soils. nirK was correlated to N2O production and became a stronger predictor of DEA in acidic soils, indicating that nirK and nirS are not ecologically redundant.

Energy Management of a Battery-Ultracapacitor Hybrid Energy Storage System in Electric Vehicles

Electric vehicle (EV) batteries tend to have accelerated degradation due to high peak power and harsh charging/discharging cycles during acceleration and deceleration periods, particularly in urban driving conditions. An oversized energy storage system (ESS) can meet the high power demands; however, it suffers from increased size, volume and cost. In order to reduce the overall ESS size and extend battery cycle life, a battery-ultracapacitor (UC) hybrid energy storage system (HESS) has been considered as an alternative solution. In this work, we investigate the optimized configuration, design, and energy management of a battery-UC HESS. One of the major challenges in a HESS is to design an energy management controller for real-time implementation that can yield good power split performance. We present the methodologies and solutions to this problem in a battery-UC HESS with a DC-DC converter interfacing with the UC and the battery. In particular, a multi-objective optimization problem is formulated to optimize the power split in order to prolong the battery lifetime and to reduce the HESS power losses. This optimization problem is numerically solved for standard drive cycle datasets using Dynamic Programming (DP). Trained using the DP optimal results, an effective real-time implementation of the optimal power split is realized based on Neural Network (NN). This proposed online energy management controller is applied to a midsize EV model with a 360V/34kWh battery pack and a 270V/203Wh UC pack. The proposed online energy management controller effectively splits the load demand with high power efficiency and also effectively reduces the battery peak current. More importantly, a 38V-385Wh battery and a 16V-2.06Wh UC HESS hardware prototype and a real-time experiment platform has been developed. The real-time experiment results have successfully validated the real-time implementation feasibility and effectiveness of the real-time controller design for the battery-UC HESS. A battery State-of-Health (SoH) estimation model is developed as a performance metric to evaluate the battery cycle life extension effect. It is estimated that the proposed online energy management controller can extend the battery cycle life by over 60%.

UNDERSTANDING CUSTOMER CHOICES IN SERVICE OUTSOURCING AND REVENUE MANAGEMENT

This dissertation investigates customer behavior modeling in service outsourcing and revenue management in the service sector (i.e., airline and hotel industries). In particular, it focuses on a common theme of improving firms’ strategic decisions through the understanding of customer preferences. Decisions concerning degrees of outsourcing, such as firms’ capacity choices, are important to performance outcomes. These choices are especially important in high-customer-contact services (e.g., airline industry) because of the characteristics of services: simultaneity of consumption and production, and intangibility and perishability of the offering. Essay 1 estimates how outsourcing affects customer choices and market share in the airline industry, and consequently the revenue implications from outsourcing. However, outsourcing decisions are typically endogenous. A firm may choose whether to outsource or not based on what a firm expects to be the best outcome. Essay 2 contributes to the literature by proposing a structural model which could capture a firm’s profit-maximizing decision-making behavior in a market. This makes possible the prediction of consequences (i.e., performance outcomes) of future strategic moves. Another emerging area in service operations management is revenue management. Choice-based revenue systems incorporate discrete choice models into traditional revenue management algorithms. To successfully implement a choice-based revenue system, it is necessary to estimate customer preferences as a valid input to optimization algorithms. The third essay investigates how to estimate customer preferences when part of the market is consistently unobserved. This issue is especially prominent in choice-based revenue management systems. Normally a firm only has its own observed purchases, while those customers who purchase from competitors or do not make purchases are unobserved. Most current estimation procedures depend on unrealistic assumptions about customer arriving. This study proposes a new estimation methodology, which does not require any prior knowledge about the customer arrival process and allows for arbitrary demand distributions. Compared with previous methods, this model performs superior when the true demand is highly variable.

The Issue with Issues Management: An Engagement Approach to Integrate Gender and Emotion into Issues Management

Using sexual assault on college campuses as a context for interrogating issues management, this study offers a normative model for inclusive issues management through an engagement approach that can better account for the gendered and emotional dimensions of issues. Because public relations literature and research have offered little theoretical or practical guidance for how issues managers can most effectively deal with issues such as sexual assault, this study represents a promising step forward. Results for this study were obtained through 32 in-depth interviews with university issues managers, six focus groups with student populations, and approximately 92 hours of participant observation. By focusing on inclusion, this revised model works to have utility for an array of issues that have previously fallen outside of the dominant masculine and rationale spheres that have worked to silence marginalized publics’ experiences. Through adapting previous issues management models to focus on inclusion at the heart of a strategic process, and engagement as the strategy for achieving this, this study offers a framework for ensuring more voices are heard—which enables organizations to more effectively communicate with their publics. Additionally, findings from this research may also help practitioners at different types of organizations develop better, and proactive, communication strategies for handling emotional and gendered issues as to avoid negative media attention and work to change organizational culture.

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.

TRAFFIC IMPACT ANALYSIS OF SEVERAL DYNAMIC LANE MANAGEMENT STRATEGIES FOR CONGESTION MITIGATION BASED ON DTA MODEL

Persistent daily congestion has been increasing in recent years, particularly along major corridors during selected periods in the mornings and evenings. On certain segments, these roadways are often at or near capacity. However, a conventional Predefined control strategy did not fit the demands that changed over time, making it necessary to implement the various dynamical lane management strategies discussed in this thesis. Those strategies include hard shoulder running, reversible HOV lanes, dynamic tolls and variable speed limit. A mesoscopic agent-based DTA model is used to simulate different strategies and scenarios. From the analyses, all strategies aim to mitigate congestion in terms of the average speed and average density. The largest improvement can be found in hard shoulder running and reversible HOV lanes while the other two provide more stable traffic. In terms of average speed and travel time, hard shoulder running is the most congested strategy for I-270 to help relieve the traffic pressure.

Mycobacteriosis in Chesapeake Bay Striped Bass (Morone saxatilis): The Interaction of Nutrition and Disease

Field and laboratory studies were conducted from 1998 - 2005 to examine the relationship between nutritional status and mycobacteriosis in Chesapeake Bay striped bass (Morone saxatilis). A review of DNA from archived tissue blocks indicated that the disease has been present since at least 1984. Field surveys and feeding trials were conducted from 1998-1999 to determine the nutritional condition of striped bass and the association with disease state. Proximate composition revealed elevated moisture (~ 80%) and low storage lipids (< 0.5% ww), characteristic of a poorly nourished population. These findings were not consistent with data collected in 1990-1991, or with experimentally fed fish. Mycobacteriosis explained little of the variance in chemical composition (p > 0.2); however elevated moisture and low lipid concentration were associated with fish with ulcerative lesions (p < 0.05). This suggests that age 3 and 4 striped bass were in poor nutritional health in 1998-1999, which may be independent from the disease process. Challenge studies were performed to address the hypothesis that disease progression and severity may be altered by nutritional status of the host. Intraperitoneal inoculation of 104 CFU M. marinum resulted in high mortality, elevated bacterial density, and poor granuloma formation in low ration (0.15% bw/d) groups while adequately fed fish (1% bw/d) followed a normal course of granulomatous inflammation with low mortality to a steady, equilibrium state. Further, we demonstrated that an active inflammatory state could be reactivated in fish through reductions in total diet. The energetic demand of mycobacteriosis, was insignificant in comparison to sham inoculated controls in adequately fed fish (p > 0.05). Declines in total body energy were only apparent during active, inflammatory stages of disease. Overall, these findings suggest that: 1) mycobacteriosis is not a new disease of Chesapeake Bay striped bass, 2) the disease has little energetic demand in the normal, chronic progression, and 3) poor nutritional health can greatly enhance the progression and severity, and reactivation of disease. The implications of this research are that management strategies focused on enhancing the nutritional state of striped bass could potentially alter the disease dynamics in Chesapeake Bay.

Nutrient enrichment effects on mangrove sediments from differing tree height zones in Bocas del Toro, Panama

Red mangrove (Rhizophora mangle L.) forests have distinct tree-height zones, with tall trees fringing the ocean and shorter trees in interior stands. A long-term nitrogen (N) and phosphorus (P) fertilization experiment in Almirante Bay, Bocas del Toro Province, Panama has shown that tree-height zonation is primarily related to nutrient limitation. This experiment was used to test the effects of in-situ nutrient additions and tree zonation on mangrove sediments. The sediments underlying the experimental R. mangle trees were sampled and N₂ fixation, ¹⁵N, chlorophyll a, percent N and P, and percent organic biomass were quantified. Both N and P additions significantly affected almost every parameter measured in both zones within this experiment. These results are likely to have implications for management since N and P inputs are predicted to increase throughout the tropics and subtropics worldwide.