Food Service Operations in the Cruise Industry

Food service on a cruise ship presents some unique challenges. A review of food service in the cruise industry is presented along with some ideas on the future. The case is made for a change in traditional operations with a move toward greater use of computer-driven management techniques.

Science behind management of Shark Bay and Florida Bay, two P-limited subtropical systems with different climatology and human pressures

This special issue on ‘Science for the management of subtropical embayments: examples from Shark Bay and Florida Bay’ is a valuable compilation of individual research outcomes from Florida Bay and Shark Bay from the past decade and addresses gaps in our scientific knowledge base in Shark Bay especially. Yet the compilation also demonstrates excellent research that is poorly integrated, and driven by interests and issues that do not necessarily lead to a more integrated stewardship of the marine natural values of either Shark Bay or Florida Bay. Here we describe the status of our current knowledge, introduce the valuable extension of the current knowledge through the papers in this issue and then suggest some future directions. For management, there is a need for a multidisciplinary international science program that focusses research on the ecological resilience of Shark Bay and Florida Bay, the effect of interactions between physical environmental drivers and biological control through behavioural and trophic interactions, and all under increased anthropogenic stressors. Shark Bay offers a ‘pristine template’ for this scale of study.

Relating precipitation and water management to nutrient concentrations in the oligotrophic ‘‘upside-down’’ estuaries of the Florida Everglades

We present 8 yr of long-term water quality, climatological, and water management data for 17 locations in Everglades National Park, Florida. Total phosphorus (P) concentration data from freshwater sites (typically ,0.25 mmol L21, or 8 mg L21) indicate the oligotrophic, P-limited nature of this large freshwater–estuarine landscape. Total P concentrations at estuarine sites near the Gulf of Mexico (average ø0.5 m mol L21) demonstrate the marine source for this limiting nutrient. This ‘‘upside down’’ phenomenon, with the limiting nutrient supplied by the ocean and not the land, is a defining characteristic of the Everglade landscape. We present a conceptual model of how the seasonality of precipitation and the management of canal water inputs control the marine P supply, and we hypothesize that seasonal variability in water residence time controls water quality through internal biogeochemical processing. Low freshwater inflows during the dry season increase estuarine residence times, enabling local processes to control nutrient availability and water quality. El Nin˜o–Southern Oscillation (ENSO) events tend to mute the seasonality of rainfall without altering total annual precipitation inputs. The Nin˜o3 ENSO index (which indicates an ENSO event when positive and a La Nin˜a event when negative) was positively correlated with both annual rainfall and the ratio of dry season to wet season precipitation. This ENSO-driven disruption in seasonal rainfall patterns affected salinity patterns and tended to reduce marine inputs of P to Everglades estuaries. ENSO events also decreased dry season residence times, reducing the importance of estuarine nutrient processing. The combination of variable water management activities and interannual differences in precipitation patterns has a strong influence on nutrient and salinity patterns in Everglades estuaries.

Vegetation:environment relationships and water management in Shark Slough, Everglades National Park

The hydrologic regime of Shark Slough, the most extensive long hydroperiod marsh in Everglades National Park, is largely controlled by the location, volume, and timing of water delivered to it through several control structures from Water Conservation Areas north of the Park. Where natural or anthropogenic barriers to water flow are present, water management practices in this highly regulated system may result in an uneven distribution of water in the marsh, which may impact regional vegetation patterns. In this paper, we use data from 569 sampling locations along five cross-Slough transects to examine regional vegetation distribution, and to test and describe the association of marsh vegetation with several hydrologic and edaphic parameters. Analysis of vegetation:environment relationships yielded estimates of both mean and variance in soil depth, as well as annual hydroperiod, mean water depth, and 30-day maximum water depth within each cover type during the 1990’s. We found that rank abundances of the three major marsh cover types (Tall Sawgrass, Sparse Sawgrass, and Spikerush Marsh) were identical in all portions of Shark Slough, but regional trends in the relative abundance of individual communities were present. Analysis also indicated clear and consistent differences in the hydrologic regime of three marsh cover types, with hydroperiod and water depths increasing in the order Tall Sawgrass , Sparse Sawgrass , Spikerush Marsh. In contrast, soil depth decreased in the same order. Locally, these differences were quite subtle; within a management unit of Shark Slough, mean annual values for the two water depth parameters varied less than 15 cm among types, and hydroperiods varied by 65 days or less. More significantly, regional variation in hydrology equaled or exceeded the variation attributable to cover type within a small area. For instance, estimated hydroperiods for Tall Sawgrass in Northern Shark Slough were longer than for Spikerush Marsh in any of the other regions. Although some of this regional variation may reflect a natural gradient within the Slough, a large proportion is the result of compartmentalization due to current water management practices within the marsh.We conclude that hydroperiod or water depth are the most important influences on vegetation within management units, and attribute larger scale differences in vegetation pattern to the interactions among soil development, hydrology and fire regime in this pivotal portion of Everglades.

Best Management Practices in Green Lodging Defined and Explained

Best management practices in green lodging are sustainable or “green” business strategies designed to enhance the lodging product from the perspective of owners, operators and guests. For guests, these practices should enhance their experience while for owners and operators, generate positive returns on investments. Best management practices in green lodging typically starts with a clear understanding of each lodging firm’s role in society, its impact on the environment and strategies developed to mitigate negative environmental externalities generated from the production of lodging goods and services. Negative externalities of hotel operations manifest themselves in energy and water usage, waste generation and air pollution. Hence, best management practices in green lodging are dynamic, cost effective, innovative, stakeholder driven and environmentally sound technical and behavioral solutions that attempt to ameliorate or eliminate the negative environmental externalities associated with lodging operations, while simultaneously generate positive returns on green investments. Thus, best management practices in green lodging should reduce lodging firms’ operating costs, increase guest satisfaction, reduce or eliminate the negative environmental impacts associated with hotel operations while simultaneously enhance business operations.

Ethics, Value Systems And The Professionalization Of Hoteliers

In the discussion - Ethics, Value Systems And The Professionalization Of Hoteliers by K. Michael Haywood, Associate Professor, School of Hotel and Food Administration, University of Guelph, Haywood initially presents: “Hoteliers and executives in other service industries should realize that the foundation of success in their businesses is based upon personal and corporate value systems and steady commitment to excellence. The author illustrates how ethical issues and manager morality are linked to, and shaped by the values of executives and the organization, and how improved professionalism can only be achieved through the adoption of a value system that rewards contributions rather than the mere attainment of results.” The bottom line of this discussion is, how does the hotel industry reconcile its behavior with that of public perception? “The time has come for hoteliers to examine their own standards of ethics, value systems, and professionalism,” Haywood says. And it is ethics that are at the center of this issue; Haywood holds that component in an estimable position. “Hoteliers must become value-driven,” advises Haywood. “They must be committed to excellence both in actualizing their best potentialities and in excelling in all they do. In other words, the professionalization of the hotelier can be achieved through a high degree of self-control, internalized values, codes of ethics, and related socialization processes,” he expands. “Serious ethical issues exist for hoteliers as well as for many business people and professionals in positions of responsibility,” Haywood alludes in defining some inter-industry problems. “The acceptance of kickbacks and gifts from suppliers, the hiding of income from taxation authorities, the lack of interest in installing and maintaining proper safety and security systems, and the raiding of competitors' staffs are common practices,” he offers, with the reasoning that if these problems can occur within ranks, then there is going to be a negative backlash in the public/client arena as well. Haywood divides the key principles of his thesis statement - ethics, value systems, and professionalism – into specific elements, and then continues to broaden the scope of each element. Promotion, product/service, and pricing are additional key components in Haywood’s discussion, and he addresses each with verve and vitality. Haywood references the four character types - craftsmen, jungle fighters, company men, and gamesmen – via a citation to Michael Maccoby, in the portion of the discussion dedicated to morality and success. Haywood closes with a series of questions derived from Lawrence Miller's American Spirit, Visions of a New Corporate Culture, each question designed to focus, shape, and organize management's attention to the values that Miller sets forth in his piece.

Market-Driven Hotel Brands: Linking Market Orientation, Innovation, and Performance

"Market orientation" is a term popularized by marketing practitioners to indicate the extent to which a firm is market driven. This presumed linkage between market orientation and profitability has caught the attention of scholars, but, surprisingly, only two prior studies have reported a positive association between the two. Given the special relevance to the hotel industry of being market driven, we believe this industry provides the ideal setting for demonstrating the link between market orientation and performance. This research examines this linkage in the hotel industry. The results of our study suggest that market orientation is positively and significantly related to innovation, subjective performance, and objective performance. This result yields a number of useful ideas about how to harness the power of the marketing concept.

Improving resource management in virtualized data centers using application performance models

The rapid growth of virtualized data centers and cloud hosting services is making the management of physical resources such as CPU, memory, and I/O bandwidth in data center servers increasingly important. Server management now involves dealing with multiple dissimilar applications with varying Service-Level-Agreements (SLAs) and multiple resource dimensions. The multiplicity and diversity of resources and applications are rendering administrative tasks more complex and challenging. This thesis aimed to develop a framework and techniques that would help substantially reduce data center management complexity.^ We specifically addressed two crucial data center operations. First, we precisely estimated capacity requirements of client virtual machines (VMs) while renting server space in cloud environment. Second, we proposed a systematic process to efficiently allocate physical resources to hosted VMs in a data center. To realize these dual objectives, accurately capturing the effects of resource allocations on application performance is vital. The benefits of accurate application performance modeling are multifold. Cloud users can size their VMs appropriately and pay only for the resources that they need; service providers can also offer a new charging model based on the VMs performance instead of their configured sizes. As a result, clients will pay exactly for the performance they are actually experiencing; on the other hand, administrators will be able to maximize their total revenue by utilizing application performance models and SLAs. ^ This thesis made the following contributions. First, we identified resource control parameters crucial for distributing physical resources and characterizing contention for virtualized applications in a shared hosting environment. Second, we explored several modeling techniques and confirmed the suitability of two machine learning tools, Artificial Neural Network and Support Vector Machine, to accurately model the performance of virtualized applications. Moreover, we suggested and evaluated modeling optimizations necessary to improve prediction accuracy when using these modeling tools. Third, we presented an approach to optimal VM sizing by employing the performance models we created. Finally, we proposed a revenue-driven resource allocation algorithm which maximizes the SLA-generated revenue for a data center.^

A retrospective-longitudinal examination of the relationship between apportionment of seat time in community-college algebra courses and student academic performance

During the past decade, there has been a dramatic increase by postsecondary institutions in providing academic programs and course offerings in a multitude of formats and venues (Biemiller, 2009; Kucsera & Zimmaro, 2010; Lang, 2009; Mangan, 2008). Strategies pertaining to reapportionment of course-delivery seat time have been a major facet of these institutional initiatives; most notably, within many open-door 2-year colleges. Often, these enrollment-management decisions are driven by the desire to increase market-share, optimize the usage of finite facility capacity, and contain costs, especially during these economically turbulent times. So, while enrollments have surged to the point where nearly one in three 18-to-24 year-old U.S. undergraduates are community college students (Pew Research Center, 2009), graduation rates, on average, still remain distressingly low (Complete College America, 2011). Among the learning-theory constructs related to seat-time reapportionment efforts is the cognitive phenomenon commonly referred to as the spacing effect, the degree to which learning is enhanced by a series of shorter, separated sessions as opposed to fewer, more massed episodes. This ex post facto study explored whether seat time in a postsecondary developmental-level algebra course is significantly related to: course success; course-enrollment persistence; and, longitudinally, the time to successfully complete a general-education-level mathematics course. Hierarchical logistic regression and discrete-time survival analysis were used to perform a multi-level, multivariable analysis of a student cohort (N = 3,284) enrolled at a large, multi-campus, urban community college. The subjects were retrospectively tracked over a 2-year longitudinal period. The study found that students in long seat-time classes tended to withdraw earlier and more often than did their peers in short seat-time classes (p < .05). Additionally, a model comprised of nine statistically significant covariates (all with p-values less than .01) was constructed. However, no longitudinal seat-time group differences were detected nor was there sufficient statistical evidence to conclude that seat time was predictive of developmental-level course success. A principal aim of this study was to demonstrate—to educational leaders, researchers, and institutional-research/business-intelligence professionals—the advantages and computational practicability of survival analysis, an underused but more powerful way to investigate changes in students over time.

Quality of life and application of the transtheoretical model to diabetes self -management behaviors in older adults with type 2 diabetes

One in five adults 65 years and older has diabetes. Coping with diabetes is a lifelong task, and much of the responsibility for managing the disease falls upon the individual. Reports of non-adherence to recommended treatments are high. Understanding the additive impact of diabetes on quality of life issues is important. The purpose of this study was to investigate the quality of life and diabetes self-management behaviors in ethnically diverse older adults with type 2 diabetes. The SF-12v2 was used to measure physical and mental health quality of life. Scores were compared to general, age sub-groups, and diabetes-specific norms. The Transtheoretical Model (TTM) was applied to assess perceived versus actual behavior for three diabetes self-management tasks: dietary management, medication management, and blood glucose self-monitoring. Dietary intake and hemoglobin A1c values were measured as outcome variables. Utilizing a cross-sectional research design, participants were recruited from Elderly Nutrition Program congregate meal sites (n = 148, mean age 75). ^ Results showed that mean scores of the SF-12v2 were significantly lower in the study sample than the general norms for physical health (p < .001), mental health (p < .01), age sub-group norms (p < .05), and diabetes-specific norms for physical health (p < .001). A multiple regression analysis found that adherence to an exercise plan was significantly associated with better physical health (p < .001). Transtheoretical Model multiple regression analyses explained 68% of the variance for % Kcal from fat, 41% for fiber, 70% for % Kcal from carbohydrate, and 7% for hemoglobin A 1c values. Significant associations were found between TTM stage of change and dietary fiber intake (p < .01). Other significant associations related to diet included gender (p < .01), ethnicity (p < .05), employment (p < .05), type of insurance (p < .05), adherence to an exercise plan (p < .05), number of doctor visits/year ( p < .01), and physical health (p < .05). Significant associations were found between hemoglobin A1c values and age ( p < .05), being non-Hispanic Black (p < .01), income (p < .01), and eye problems (p < .05). ^ The study highlights the importance of the beneficial effects of exercise on quality of life issues. Furthermore, application of the Transtheoretical Model in conjunction with an assessment of dietary intake may be valuable in helping individuals make lifestyle changes. ^

Best Management Practices in Green Lodging Defined and Explained

Best management practices in green lodging are sustainable or “green” business strategies designed to enhance the lodging product from the perspective of owners, operators and guests. For guests, these practices should enhance their experience while for owners and operators, generate positive returns on investments. Best management practices in green lodging typically starts with a clear understanding of each lodging firm’s role in society, its impact on the environment and strategies developed to mitigate negative environmental externalities generated from the production of lodging goods and services. Negative externalities of hotel operations manifest themselves in energy and water usage, waste generation and air pollution. Hence, best management practices in green lodging are dynamic, cost effective, innovative, stakeholder driven and environmentally sound technical and behavioral solutions that attempt to ameliorate or eliminate the negative environmental externalities associated with lodging operations, while simultaneously generate positive returns on green investments. Thus, best management practices in green lodging should reduce lodging firms’ operating costs, increase guest satisfaction, reduce or eliminate the negative environmental impacts associated with hotel operations while simultaneously enhance business operations.

Developing a Data-Driven Classification of South Florida Plant Communities

A comprehensive, broadly accepted vegetation classification is important for ecosystem management, particularly for planning and monitoring. South Florida vegetation classification systems that are currently in use were largely arrived at subjectively and intuitively with the involvement of experienced botanical observers and ecologists, but with little support in terms of quantitative field data. The need to develop a field data-driven classification of South Florida vegetation that builds on the ecological organization has been recognized by the National Park Service and vegetation practitioners in the region. The present work, funded by the National Park Service Inventory and Monitoring Program - South Florida/Caribbean Network (SFCN), covers the first stage of a larger project whose goal is to apply extant vegetation data to test, and revise as necessary, an existing, widely used classification (Rutchey et al. 2006). The objectives of the first phase of the project were (1) to identify useful existing datasets, (2) to collect these data and compile them into a geodatabase, (3) to conduct an initial classification analysis of marsh sites, and (4) to design a strategy for augmenting existing information from poorly represented landscapes in order to develop a more comprehensive south Florida classification.

Human-driven benthic jellyfish blooms: Causes and consequences for coastal marine ecosystems

Coastal marine ecosystems are among the most impacted globally, attributable to individual and cumulative effects of human disturbance. Anthropogenic nutrient loading is one stressor that commonly affects nearshore ecosystems, including seagrass beds, and has positive and negative effects on the structure and function of coastal systems. An additional, previously unexplored mechanistic pathway through which nutrients may indirectly influence nearshore systems is by driving blooms of benthic jellyfish. My dissertation research, conducted on Abaco Island, Bahamas, focused on elucidating the role that benthic jellyfish have in structuring systems in which they are common (i.e., seagrass beds), and explored mechanistic processes that may drive blooms of this taxa. ^ To establish that human disturbances (e.g., elevated nutrient availability) may drive increased abundance and size of benthic jellyfish, Cassiopea spp., I conducted surveys in human-impacted and unimpacted coastal sites. Jellyfish were more abundant (and larger) from human-impacted areas, positively correlated to elevated nutrient availability. In order to elucidate mechanisms linking Cassiopea spp. with elevated nutrients, I evaluated whether zooxanthellae from Cassiopea were higher from human-disturbed systems, and whether Cassiopea exhibited increased size following nutrient input. I demonstrated that zooxanthellae population densities were elevated in human-impacted sites, and that nutrients led to positive jellyfish growth. ^ As heightened densities of Cassiopea jellyfish may exert top-down and bottom-up controls on flora and fauna in impacted seagrass beds, I sought to examine ecological responses to Cassiopea. I evaluated whether there was a relationship between high Cassiopea densities and lower benthic fauna abundance and diversity in shallow seagrass beds. I found that Cassiopea have subtle effects on benthic fauna. However, through an experiment conducted in a seagrass bed in which nutrients and Cassiopea were added, I demonstrated that Cassiopea can result in seagrass habitat modification, with negative consequences for benthic fauna. ^ My dissertation research demonstrates that increased human-driven benthic jellyfish densities may have indirect and direct effects on flora and fauna of coastal marine systems. This knowledge will advance our understanding of how human disturbances shift species interactions in coastal ecosystems, and will be critical for effective management of jellyfish blooms.^

Event mining for system and service management

Modern IT infrastructures are constructed by large scale computing systems and administered by IT service providers. Manually maintaining such large computing systems is costly and inefficient. Service providers often seek automatic or semi-automatic methodologies of detecting and resolving system issues to improve their service quality and efficiency. This dissertation investigates several data-driven approaches for assisting service providers in achieving this goal. The detailed problems studied by these approaches can be categorized into the three aspects in the service workflow: 1) preprocessing raw textual system logs to structural events; 2) refining monitoring configurations for eliminating false positives and false negatives; 3) improving the efficiency of system diagnosis on detected alerts. Solving these problems usually requires a huge amount of domain knowledge about the particular computing systems. The approaches investigated by this dissertation are developed based on event mining algorithms, which are able to automatically derive part of that knowledge from the historical system logs, events and tickets. ^ In particular, two textual clustering algorithms are developed for converting raw textual logs into system events. For refining the monitoring configuration, a rule based alert prediction algorithm is proposed for eliminating false alerts (false positives) without losing any real alert and a textual classification method is applied to identify the missing alerts (false negatives) from manual incident tickets. For system diagnosis, this dissertation presents an efficient algorithm for discovering the temporal dependencies between system events with corresponding time lags, which can help the administrators to determine the redundancies of deployed monitoring situations and dependencies of system components. To improve the efficiency of incident ticket resolving, several KNN-based algorithms that recommend relevant historical tickets with resolutions for incoming tickets are investigated. Finally, this dissertation offers a novel algorithm for searching similar textual event segments over large system logs that assists administrators to locate similar system behaviors in the logs. Extensive empirical evaluation on system logs, events and tickets from real IT infrastructures demonstrates the effectiveness and efficiency of the proposed approaches.^

Statistical dialog management for health interventions

Research endeavors on spoken dialogue systems in the 1990s and 2000s have led to the deployment of commercial spoken dialogue systems (SDS) in microdomains such as customer service automation, reservation/booking and question answering systems. Recent research in SDS has been focused on the development of applications in different domains (e.g. virtual counseling, personal coaches, social companions) which requires more sophistication than the previous generation of commercial SDS. The focus of this research project is the delivery of behavior change interventions based on the brief intervention counseling style via spoken dialogue systems. ^ Brief interventions (BI) are evidence-based, short, well structured, one-on-one counseling sessions. Many challenges are involved in delivering BIs to people in need, such as finding the time to administer them in busy doctors' offices, obtaining the extra training that helps staff become comfortable providing these interventions, and managing the cost of delivering the interventions. Fortunately, recent developments in spoken dialogue systems make the development of systems that can deliver brief interventions possible. ^ The overall objective of this research is to develop a data-driven, adaptable dialogue system for brief interventions for problematic drinking behavior, based on reinforcement learning methods. The implications of this research project includes, but are not limited to, assessing the feasibility of delivering structured brief health interventions with a data-driven spoken dialogue system. Furthermore, while the experimental system focuses on harmful alcohol drinking as a target behavior in this project, the produced knowledge and experience may also lead to implementation of similarly structured health interventions and assessments other than the alcohol domain (e.g. obesity, drug use, lack of exercise), using statistical machine learning approaches. ^ In addition to designing a dialog system, the semantic and emotional meanings of user utterances have high impact on interaction. To perform domain specific reasoning and recognize concepts in user utterances, a named-entity recognizer and an ontology are designed and evaluated. To understand affective information conveyed through text, lexicons and sentiment analysis module are developed and tested.^