Information Processing: Coordination and Control in Large Hotels

A number of factors influence the information processing needs of organizations, particularly with respect to the coordination and control mechanisms within a hotel. The authors use a theoretical framework to illustrate alternative mechanisms that can be used to coordinate and control hotel operations.

Heteronormativity and teaching: A phenomenological study of lesbian teachers

The purpose of this phenomenological study was to understand what impact “heteronormativity” has on a lesbian teacher's perception of her instructional style, content, and context of curriculum taught. Through taped interviews with lesbian educators, this research examined the lived experience of the lesbian teacher. The framework for this study included theories related to historical, sociocultural, and psychosocial development while the methodology included a qualitative design using primary elements of a phenomenological study outlined without ignoring the influence associated with contextualism. Due to the sensitive nature of the study nine women who were the focus of this research were volunteers with the first serving as a “gatekeeper” to assist in the pilot study. The subsequent group evolved as a result of “snowballing” to gain more participants. ^ The data in the form of narrative derived from the interviews was transcribed, color-coded, and organized into four themes and associated sub-themes, based upon the perceptions of these educators. These themes characterized the coming out process of a lesbian, which directly paralleled the personal and professional development of the lesbian educator, emerged as a result of the analysis. They included: (a) self-acknowledgement; (b) self-indentification; (c) coming out to other lesbians by overcoming fear and establishing relationships; (d) coming out to others by overcoming heteronormativity by using support groups in defining a lesbian's role as a teacher. ^ The results of this study showed that the acceptance of the lesbian culture, shared with the acknowledgement, rather than compliance or defiance, of cultural hegemony can allow the lesbian educator to develop a curriculum and a classroom climate that will foster understanding and even generate social change among colleagues, parents, and students, one person at a time. ^

A study on uncertain dynamic disaster management tasks, knowledge sharing, and task performance

Each disaster presents itself with a unique set of characteristics that are hard to determine a priori. Thus disaster management tasks are inherently uncertain, requiring knowledge sharing and quick decision making that involves coordination across different levels and collaborators. While there has been an increasing interest among both researchers and practitioners in utilizing knowledge management to improve disaster management, little research has been reported about how to assess the dynamic nature of disaster management tasks, and what kinds of knowledge sharing are appropriate for different dimensions of task uncertainty characteristics. ^ Using combinations of qualitative and quantitative methods, this research study developed the dimensions and their corresponding measures of the uncertain dynamic characteristics of disaster management tasks and tested the relationships between the various dimensions of uncertain dynamic disaster management tasks and task performance through the moderating and mediating effects of knowledge sharing. ^ Furthermore, this research work conceptualized and assessed task uncertainty along three dimensions: novelty, unanalyzability, and significance; knowledge sharing along two dimensions: knowledge sharing purposes and knowledge sharing mechanisms; and task performance along two dimensions: task effectiveness and task efficiency. Analysis results of survey data collected from Miami-Dade County emergency managers suggested that knowledge sharing purposes and knowledge sharing mechanisms moderate and mediate uncertain dynamic disaster management task and task performance. Implications for research and practice as well directions for future research are discussed.^

Geospatial Data Indexing Analysis and Visualization via Web Services with Autonomic Resource Management

With the exponential growth of the usage of web-based map services, the web GIS application has become more and more popular. Spatial data index, search, analysis, visualization and the resource management of such services are becoming increasingly important to deliver user-desired Quality of Service. First, spatial indexing is typically time-consuming and is not available to end-users. To address this, we introduce TerraFly sksOpen, an open-sourced an Online Indexing and Querying System for Big Geospatial Data. Integrated with the TerraFly Geospatial database [1-9], sksOpen is an efficient indexing and query engine for processing Top-k Spatial Boolean Queries. Further, we provide ergonomic visualization of query results on interactive maps to facilitate the user’s data analysis. Second, due to the highly complex and dynamic nature of GIS systems, it is quite challenging for the end users to quickly understand and analyze the spatial data, and to efficiently share their own data and analysis results with others. Built on the TerraFly Geo spatial database, TerraFly GeoCloud is an extra layer running upon the TerraFly map and can efficiently support many different visualization functions and spatial data analysis models. Furthermore, users can create unique URLs to visualize and share the analysis results. TerraFly GeoCloud also enables the MapQL technology to customize map visualization using SQL-like statements [10]. Third, map systems often serve dynamic web workloads and involve multiple CPU and I/O intensive tiers, which make it challenging to meet the response time targets of map requests while using the resources efficiently. Virtualization facilitates the deployment of web map services and improves their resource utilization through encapsulation and consolidation. Autonomic resource management allows resources to be automatically provisioned to a map service and its internal tiers on demand. v-TerraFly are techniques to predict the demand of map workloads online and optimize resource allocations, considering both response time and data freshness as the QoS target. The proposed v-TerraFly system is prototyped on TerraFly, a production web map service, and evaluated using real TerraFly workloads. The results show that v-TerraFly can accurately predict the workload demands: 18.91% more accurate; and efficiently allocate resources to meet the QoS target: improves the QoS by 26.19% and saves resource usages by 20.83% compared to traditional peak load-based resource allocation.

Recreational Foodservice management: A Delphi study of needed competencies

The purpose of this study was to identify the needed competencies of a Recreational Foodservice manager. A three round Delphi method of iteration was used. Delphi is a research method that utilizes iterating rounds to elicit the opinion of a panel of experts regarding a specific subject.^ A nominating committee of 22 industry leaders was consulted to establish a panel of 40 management experts, of which 35 (87.5%) completed all three rounds of the Delphi study.^ Round One of the study identified 17 specific job functions of a Recreational Foodservice manager. The researcher prepared an instrument detailing 60 competencies derived from an analysis of Round One results and distributed it as a Round Two instrument requesting the panel opinion regarding the relative importance of each listed competency on a five point Likert scale.^ The results of Round Two were tabulated and analyzed to ascertain areas of consensus. A Round Three instrument was prepared advising panelists of all areas of consensus, their dissenting opinions, if any, and a request for a revised opinion.^ A final report was prepared listing the 60 competencies and the panel opinion that eight were of highest priority, 29 of above average priority, and 23 of average priority. No item received two other available ratings, below average priority and lowest priority.^ The implications of these findings suggest necessary areas of curriculum development and industry management development to implement professionalism for Recreational Foodservice managers. ^

Large scale data processing using MapReduce

As massive data sets become increasingly available, people are facing the problem of how to effectively process and understand these data. Traditional sequential computing models are giving way to parallel and distributed computing models, such as MapReduce, both due to the large size of the data sets and their high dimensionality. This dissertation, as in the same direction of other researches that are based on MapReduce, tries to develop effective techniques and applications using MapReduce that can help people solve large-scale problems. Three different problems are tackled in the dissertation. The first one deals with processing terabytes of raster data in a spatial data management system. Aerial imagery files are broken into tiles to enable data parallel computation. The second and third problems deal with dimension reduction techniques that can be used to handle data sets of high dimensionality. Three variants of the nonnegative matrix factorization technique are scaled up to factorize matrices of dimensions in the order of millions in MapReduce based on different matrix multiplication implementations. Two algorithms, which compute CANDECOMP/PARAFAC and Tucker tensor decompositions respectively, are parallelized in MapReduce based on carefully partitioning the data and arranging the computation to maximize data locality and parallelism.

The influence of study and travel abroad on the personal and professional development of students in architecture design programs

International travel has significant implications on the study of architecture. This study analyzed ways in which undergraduate and graduate students benefited from the experience of international travel and study abroad. Taken from the perspective of 15 individuals who were currently or had been architecture students at the University of Miami and Florida International University or who were alumni of the University of Florida and Syracuse University, the research explored how international travel and study abroad enhanced their awareness and understanding of architecture, and how it complemented their architecture curricula. This study also addressed a more personal aspect of international travel in order to learn how the experience and exposure to foreign cultures had positively influenced the personal and professional development of the participants.^ Participants’ individual and two-person semi-structured interviews about study abroad experiences were electronically recorded and transcribed for analysis. A second interview was conducted with five of the participants to obtain feedback concerning the accuracy of the transcripts and the interpretation of the data. Sketch journals and design projects were also analyzed from five participants and used as data for the purposes of better understanding what these individuals learned and experienced as part of their study abroad.^ Findings indicated that study abroad experiences helped to broaden student understanding about architecture and urban development. These experiences also opened the possibilities of creative and professional expression. For many, this was the most important aspect of their education as architects because it heightened their interest in architecture. These individuals talked about how they had the opportunity to experience contemporary and ancient buildings that they had learned about in their history and design classes on their home campuses. In terms of personal and professional development, many of the participants remarked that they became more independent and self-reliant because of their study abroad experiences. They also displayed a sense of global awareness and were interested in the cultures of their host nations. The study abroad experiences also had a lasting influence on their professional development.^

Effects of Management-Development Practices on Hospitality Management Graduates' Job Satisfaction and Intention to Stay

Companies have long recognized the importance of training and developing their managers to prepare them for their short- and long-term careers. Formal management-development programs and other less formal means of management development abound in the hospitality industry. Therefore, one may ask whether the entry-level managers for whom these programs are designed perceive them to be effective. The present study explores management-development practices, procedures, and techniques, and their effects on job satisfaction and organizational commitment

What Google Maps can do for Biomedical Data Dissemination: Examples and a Design Study

Background: Biologists often need to assess whether unfamiliar datasets warrant the time investment required for more detailed exploration. Basing such assessments on brief descriptions provided by data publishers is unwieldy for large datasets that contain insights dependent on specific scientific questions. Alternatively, using complex software systems for a preliminary analysis may be deemed as too time consuming in itself, especially for unfamiliar data types and formats. This may lead to wasted analysis time and discarding of potentially useful data. Results: We present an exploration of design opportunities that the Google Maps interface offers to biomedical data visualization. In particular, we focus on synergies between visualization techniques and Google Maps that facilitate the development of biological visualizations which have both low-overhead and sufficient expressivity to support the exploration of data at multiple scales. The methods we explore rely on displaying pre-rendered visualizations of biological data in browsers, with sparse yet powerful interactions, by using the Google Maps API. We structure our discussion around five visualizations: a gene co-regulation visualization, a heatmap viewer, a genome browser, a protein interaction network, and a planar visualization of white matter in the brain. Feedback from collaborative work with domain experts suggests that our Google Maps visualizations offer multiple, scale-dependent perspectives and can be particularly helpful for unfamiliar datasets due to their accessibility. We also find that users, particularly those less experienced with computer use, are attracted by the familiarity of the Google Maps API. Our five implementations introduce design elements that can benefit visualization developers. Conclusions: We describe a low-overhead approach that lets biologists access readily analyzed views of unfamiliar scientific datasets. We rely on pre-computed visualizations prepared by data experts, accompanied by sparse and intuitive interactions, and distributed via the familiar Google Maps framework. Our contributions are an evaluation demonstrating the validity and opportunities of this approach, a set of design guidelines benefiting those wanting to create such visualizations, and five concrete example visualizations.

Mitigating Inconsistencies by Coupling Data Cleaning, Filtering, and Contextual Data Validation in Wireless Sensor Networks

With the advent of peer to peer networks, and more importantly sensor networks, the desire to extract useful information from continuous and unbounded streams of data has become more prominent. For example, in tele-health applications, sensor based data streaming systems are used to continuously and accurately monitor Alzheimer's patients and their surrounding environment. Typically, the requirements of such applications necessitate the cleaning and filtering of continuous, corrupted and incomplete data streams gathered wirelessly in dynamically varying conditions. Yet, existing data stream cleaning and filtering schemes are incapable of capturing the dynamics of the environment while simultaneously suppressing the losses and corruption introduced by uncertain environmental, hardware, and network conditions. Consequently, existing data cleaning and filtering paradigms are being challenged. This dissertation develops novel schemes for cleaning data streams received from a wireless sensor network operating under non-linear and dynamically varying conditions. The study establishes a paradigm for validating spatio-temporal associations among data sources to enhance data cleaning. To simplify the complexity of the validation process, the developed solution maps the requirements of the application on a geometrical space and identifies the potential sensor nodes of interest. Additionally, this dissertation models a wireless sensor network data reduction system by ascertaining that segregating data adaptation and prediction processes will augment the data reduction rates. The schemes presented in this study are evaluated using simulation and information theory concepts. The results demonstrate that dynamic conditions of the environment are better managed when validation is used for data cleaning. They also show that when a fast convergent adaptation process is deployed, data reduction rates are significantly improved. Targeted applications of the developed methodology include machine health monitoring, tele-health, environment and habitat monitoring, intermodal transportation and homeland security.

Food and beverage management

Abstract and faculty adviser information are not available for this thesis.

Initial placement methods for Haitian adult ESOL students : the NYS place test plus profile data compared to subjective assessment

Few valid and reliable placement procedures are available to assess the English language proficiency of adults who enroll in English for Speakers of Other Languages (ESOL) programs. Whereas placement material exists for children and university ESOL students, the needs of students in adult community education programs have not been adequately addressed. Furthermore, the research suggests that a number of variables, such as, native language, age, prior schooling, length of residence, and employment are related to second language acquisition. Numerous studies contribute to our understanding of the relationship of these factors to second language acquisition of Spanish-speaking students. Again, there is a void in the research investigating the factors affecting second language acquisition and consequently, appropriate placement of Haitian Creole-speaking students. This study compared a standardized instrument, the NYS Place Test, used alone and in combination with a writing sample in English, to subjective judgement of a department coordinator for initial placement of Haitian adult ESOL students in a community education program. The study also investigated whether or not consideration of student profile data improved the accuracy of the test. Finally, the study sought to determine if a relationship existed between student profile data and those who withdrew from the program or did not enter a class after registering. Analysis of the data by crosstabulation and chi-square revealed that the standardized NYS Place Test was at least as accurate as subjective department coordinator placement and that one procedure could be substituted for li other. Although the writing sample in English improved accuracy of placement by the NYS test, the results were not significant. Of the profile variables, only length of residence was found to be significantly related to accuracy of placement using the NYS Place Test. The number of incorrect placements was higher for those students who lived in the host country from twenty-five to one hundred ten months. A post hoc analysis of NYS test scores according to level showed that those learners who placed in level three also had a significantly higher incidence of incorrect placements. No significant relationship was observed between the profile variables and those who withdrew from the program or registered but did not enter a class.

Mitigating inconsistencies by coupling data cleaning, filtering, and contextual data validation in wireless sensor networks

With the advent of peer to peer networks, and more importantly sensor networks, the desire to extract useful information from continuous and unbounded streams of data has become more prominent. For example, in tele-health applications, sensor based data streaming systems are used to continuously and accurately monitor Alzheimer's patients and their surrounding environment. Typically, the requirements of such applications necessitate the cleaning and filtering of continuous, corrupted and incomplete data streams gathered wirelessly in dynamically varying conditions. Yet, existing data stream cleaning and filtering schemes are incapable of capturing the dynamics of the environment while simultaneously suppressing the losses and corruption introduced by uncertain environmental, hardware, and network conditions. Consequently, existing data cleaning and filtering paradigms are being challenged. This dissertation develops novel schemes for cleaning data streams received from a wireless sensor network operating under non-linear and dynamically varying conditions. The study establishes a paradigm for validating spatio-temporal associations among data sources to enhance data cleaning. To simplify the complexity of the validation process, the developed solution maps the requirements of the application on a geometrical space and identifies the potential sensor nodes of interest. Additionally, this dissertation models a wireless sensor network data reduction system by ascertaining that segregating data adaptation and prediction processes will augment the data reduction rates. The schemes presented in this study are evaluated using simulation and information theory concepts. The results demonstrate that dynamic conditions of the environment are better managed when validation is used for data cleaning. They also show that when a fast convergent adaptation process is deployed, data reduction rates are significantly improved. Targeted applications of the developed methodology include machine health monitoring, tele-health, environment and habitat monitoring, intermodal transportation and homeland security.

Minimizing makespan for hybrid flowshops with batch, discrete processing machines and arbitrary job sizes

This research aims at a study of the hybrid flow shop problem which has parallel batch-processing machines in one stage and discrete-processing machines in other stages to process jobs of arbitrary sizes. The objective is to minimize the makespan for a set of jobs. The problem is denoted as: FF: batch1,sj:Cmax. The problem is formulated as a mixed-integer linear program. The commercial solver, AMPL/CPLEX, is used to solve problem instances to their optimality. Experimental results show that AMPL/CPLEX requires considerable time to find the optimal solution for even a small size problem, i.e., a 6-job instance requires 2 hours in average. A bottleneck-first-decomposition heuristic (BFD) is proposed in this study to overcome the computational (time) problem encountered while using the commercial solver. The proposed BFD heuristic is inspired by the shifting bottleneck heuristic. It decomposes the entire problem into three sub-problems, and schedules the sub-problems one by one. The proposed BFD heuristic consists of four major steps: formulating sub-problems, prioritizing sub-problems, solving sub-problems and re-scheduling. For solving the sub-problems, two heuristic algorithms are proposed; one for scheduling a hybrid flow shop with discrete processing machines, and the other for scheduling parallel batching machines (single stage). Both consider job arrival and delivery times. An experiment design is conducted to evaluate the effectiveness of the proposed BFD, which is further evaluated against a set of common heuristics including a randomized greedy heuristic and five dispatching rules. The results show that the proposed BFD heuristic outperforms all these algorithms. To evaluate the quality of the heuristic solution, a procedure is developed to calculate a lower bound of makespan for the problem under study. The lower bound obtained is tighter than other bounds developed for related problems in literature. A meta-search approach based on the Genetic Algorithm concept is developed to evaluate the significance of further improving the solution obtained from the proposed BFD heuristic. The experiment indicates that it reduces the makespan by 1.93 % in average within a negligible time when problem size is less than 50 jobs.