3D TerraFly: Quality of service management for online interactive 3D geographic information system

3D geographic information system (GIS) is data and computation intensive in nature. Internet users are usually equipped with low-end personal computers and network connections of limited bandwidth. Data reduction and performance optimization techniques are of critical importance in quality of service (QoS) management for online 3D GIS. In this research, QoS management issues regarding distributed 3D GIS presentation were studied to develop 3D TerraFly, an interactive 3D GIS that supports high quality online terrain visualization and navigation. ^ To tackle the QoS management challenges, multi-resolution rendering model, adaptive level of detail (LOD) control and mesh simplification algorithms were proposed to effectively reduce the terrain model complexity. The rendering model is adaptively decomposed into sub-regions of up-to-three detail levels according to viewing distance and other dynamic quality measurements. The mesh simplification algorithm was designed as a hybrid algorithm that combines edge straightening and quad-tree compression to reduce the mesh complexity by removing geometrically redundant vertices. The main advantage of this mesh simplification algorithm is that grid mesh can be directly processed in parallel without triangulation overhead. Algorithms facilitating remote accessing and distributed processing of volumetric GIS data, such as data replication, directory service, request scheduling, predictive data retrieving and caching were also proposed. ^ A prototype of the proposed 3D TerraFly implemented in this research demonstrates the effectiveness of our proposed QoS management framework in handling interactive online 3D GIS. The system implementation details and future directions of this research are also addressed in this thesis. ^

Best practices in exemplary service delivery: A multiple case study of service quality

The purpose of this study was to explain how exemplary service providers in luxury hotels provide consistently excellent service. Using a case study framework, the study investigated the service provider's strategies and concepts of service delivery, the importance and implementation of organizational and individual controls, and the role of training and learning. The study identified barriers to service provision and characteristics of the exemplary individuals that affect their ability to deliver luxury service. This study sought to better understand how exemplary service providers learn, think about, and do their work. The sample population of three Five-Diamond-Award winning resorts was selected for their potential for learning about the phenomenon of interest. The results demonstrate that exemplary service providers possess individual characteristics that are enhanced by the organizations for which they work. Exemplary service providers are often exemplary communicators who are emotionally generous and genuinely enjoy helping and serving others. Exemplary service organizations treat their employees as they treat their customers, as suggested by the Service-Profit Chain (Heskett, Sasser & Schlesinger, 1997). Further, they have systems and standards to guarantee satisfactory service experiences for every guest. They also encourage their service providers to personalize their service delivery and to seek opportunities to delight their guests, using a combination of controls, traditions and cultural values. Several customer service theories are discussed in relationship to whether they were or were not supported by the data. The study concluded that the delivery of exemplary service is a complex phenomenon that requires successful interactions between guests, service providers and the organization. A Model of Exemplary Service Delivery is presented and discussed that demonstrates the components of service quality as shown in the data. The model can be used by practitioners seeking to create, enhance, or evaluate their service quality, and by researchers seeking insights into the complex concepts in service quality research. Implications for future research are discussed.

Effects of service-learning on student attitudes toward academic engagement and civic responsibility

This empirical study explored the impact of service-learning participation on high school students' attitudes toward academic engagement and civic responsibility. This study focused whether a group of high school students who participated in a service-learning project had more positive attitudes toward academic engagement and civic responsibility than their high school peers who did not participate in a service learning project. ^ Data were collected from 67 volunteer students as participants in grades 9–12. A service-learning treatment group of 34 high school students was examined relative to a comparison group of 33 high school students with similar demographic and academic characteristics. The investigator used questionnaires, an oral history/service-learning project, and interviews with the teacher-coordinators of the project to collect the data. The two surveys, one investigating high school students' attitudes about academic engagement, the other investigating high school students' attitudes toward civic responsibility, were administered in a pre-treatment/post-treatment design. There were 90 days between the pre-treatment and post-treatment administrations. A factor analysis of the civic responsibility instrument and multivariate analysis of gain scores were used to compare the means of the total aggregate scores of the treatment and comparison groups. Factor analysis was performed on the academic engagement instrument but it was determined that only the total scores could be used in subsequent analyses. Results were used to determine the efficacy of service-learning as interpreted in student attitudes toward academic engagement and student attitudes toward civic responsibility. ^ The study found no significant difference between the academic engagement and the civic responsibility attitudes of a high school service-learning project group and a high school comparison group with comparable school and similar demographic characteristics. One of the implications for educational practice and policy from the study results is a need to design and implement more powerful studies, studies implemented at many sites rather than just at two sites that were the basis of this study, and studies that investigate the research questions over longer time periods. Although it was not a focus of the study, the investigator concluded that service learning projects such as this might be more effective if they were better aligned with Dewey's principles. ^

Realization of Differentiated Quality of Service for Wideband Code Division Multiple Access Core Network

The development of 3G (the 3rd generation telecommunication) value-added services brings higher requirements of Quality of Service (QoS). Wideband Code Division Multiple Access (WCDMA) is one of three 3G standards, and enhancement of QoS for WCDMA Core Network (CN) becomes more and more important for users and carriers. The dissertation focuses on enhancement of QoS for WCDMA CN. The purpose is to realize the DiffServ (Differentiated Services) model of QoS for WCDMA CN. Based on the parallelism characteristic of Network Processors (NPs), the NP programming model is classified as Pool of Threads (POTs) and Hyper Task Chaining (HTC). In this study, an integrated programming model that combines both of the two models was designed. This model has highly efficient and flexible features, and also solves the problems of sharing conflicts and packet ordering. We used this model as the programming model to realize DiffServ QoS for WCDMA CN. ^ The realization mechanism of the DiffServ model mainly consists of buffer management, packet scheduling and packet classification algorithms based on NPs. First, we proposed an adaptive buffer management algorithm called Packet Adaptive Fair Dropping (PAFD), which takes into consideration of both fairness and throughput, and has smooth service curves. Then, an improved packet scheduling algorithm called Priority-based Weighted Fair Queuing (PWFQ) was introduced to ensure the fairness of packet scheduling and reduce queue time of data packets. At the same time, the delay and jitter are also maintained in a small range. Thirdly, a multi-dimensional packet classification algorithm called Classification Based on Network Processors (CBNPs) was designed. It effectively reduces the memory access and storage space, and provides less time and space complexity. ^ Lastly, an integrated hardware and software system of the DiffServ model of QoS for WCDMA CN was proposed. It was implemented on the NP IXP2400. According to the corresponding experiment results, the proposed system significantly enhanced QoS for WCDMA CN. It extensively improves consistent response time, display distortion and sound image synchronization, and thus increases network efficiency and saves network resource.^

Creating Memories: The Interactive Process of Service Delivery

A model is presented that captures the complex nature of the service experience in an attempt to aid in the design, development and evaluation of service delivery personnel and systems.

Model of Service Quality: Customer Loyalty for Hotels

The authors investigate the relationship between loyalty and perceived service quality of hotel customers and discus managerial implications to develop strategies to enhance loyalty of hotel customers. A survey was conducted among customers in the San Francisco Bay Area. Results indicate that customer loyalty is dependent on perceived service quality which is observed in terms of timelines, facilities, and ambience.

Examining the Impact of Service Times on Overall Guest Satisfaction Perception in the Casual Dining Environment

A mystery shopper study was used to examine the influence of service times on customer satisfaction. The impact of management emphasis on service quality was also examined. In the restaurants studied, service time influenced customer satisfaction. Management attention to service time improved performance in direct relationship to the level of emphasis.

The Influence of Selected Antecedents of Frontline Employee's Perceptions of Service Recovery Performance

The purpose of this study is to determine the potential impact of selected organizational factors on boundary-spanning-role employees’ perceptions of service recovery performance. This study also aims to assess the impact of service recovery performance on the intention to leave the job and extrinsic job satisfaction. This study uses a sample of frontline employees in Belek, Antalya, Turkey. The empirical findings revealed that education, team work and role ambiguity as frontline job perceptions were found to exert positive influences on the service recovery performance, but, empowerment, reward, and organizational commitment were found to have negative effects on the service recovery performance.

Implementation of service -learning in higher education courses: Perceptions of faculty

This study examined the motivation of college and university faculty to implement service-learning into their traditional courses. The benefits derived by faculty, as well as those issues of maintenance, including supports and/or obstacles, were also investigated in relation to their impact on motivation. The focus was on generating theory from the emerging data. ^ Data were collected from interviews with 17 faculty teaching courses that included a component of service-learning. A maximum variation sampling of participants from six South Florida colleges and universities was utilized. Faculty participants represented a wide range of academic disciplines, faculty ranks, years of experience in teaching and using service-learning as well as gender and ethnic diversity. For data triangulation, a focus group with eight additional college faculty was conducted and documents, including course syllabi and institutional service-learning handbooks, collected during the interviews were examined. The interviews were transcribed and coded using traditional methods as well as with the assistance of the computerized assisted qualitative data analysis software, Atlas.ti. The data were organized into five major categories with themes and sub-themes emerging for each. ^ While intrinsic or personal factors along with extrinsic factors all serve to influence faculty motivation, the study's findings revealed that the primary factors influencing faculty motivation to adopt service-learning were those that were intrinsic or personal in nature. These factors included: (a) past experiences, (b) personal characteristics including the value of serving, (c) involvement with community service, (d) interactions and relationships with peers, (e) benefits to students, (f) benefits to teaching, and (g) perceived career benefits. Implications and recommendations from the study encompass suggestions for administrators in higher education institutions for supporting and encouraging faculty adoption of service-learning including a well developed infrastructure as well as incentives, particularly during the initial implementation period, rewards providing recognition for the academic nature of service-learning and support for the development of peer relationships among service-learning faculty. ^

Ensemble fuzzy belief intrusion detection design

With the rapid growth of the Internet, computer attacks are increasing at a fast pace and can easily cause millions of dollar in damage to an organization. Detecting these attacks is an important issue of computer security. There are many types of attacks and they fall into four main categories, Denial of Service (DoS) attacks, Probe, User to Root (U2R) attacks, and Remote to Local (R2L) attacks. Within these categories, DoS and Probe attacks continuously show up with greater frequency in a short period of time when they attack systems. They are different from the normal traffic data and can be easily separated from normal activities. On the contrary, U2R and R2L attacks are embedded in the data portions of the packets and normally involve only a single connection. It becomes difficult to achieve satisfactory detection accuracy for detecting these two attacks. Therefore, we focus on studying the ambiguity problem between normal activities and U2R/R2L attacks. The goal is to build a detection system that can accurately and quickly detect these two attacks. In this dissertation, we design a two-phase intrusion detection approach. In the first phase, a correlation-based feature selection algorithm is proposed to advance the speed of detection. Features with poor prediction ability for the signatures of attacks and features inter-correlated with one or more other features are considered redundant. Such features are removed and only indispensable information about the original feature space remains. In the second phase, we develop an ensemble intrusion detection system to achieve accurate detection performance. The proposed method includes multiple feature selecting intrusion detectors and a data mining intrusion detector. The former ones consist of a set of detectors, and each of them uses a fuzzy clustering technique and belief theory to solve the ambiguity problem. The latter one applies data mining technique to automatically extract computer users’ normal behavior from training network traffic data. The final decision is a combination of the outputs of feature selecting and data mining detectors. The experimental results indicate that our ensemble approach not only significantly reduces the detection time but also effectively detect U2R and R2L attacks that contain degrees of ambiguous information.

Ensemble Fuzzy Belief Intrusion Detection Design

With the rapid growth of the Internet, computer attacks are increasing at a fast pace and can easily cause millions of dollar in damage to an organization. Detecting these attacks is an important issue of computer security. There are many types of attacks and they fall into four main categories, Denial of Service (DoS) attacks, Probe, User to Root (U2R) attacks, and Remote to Local (R2L) attacks. Within these categories, DoS and Probe attacks continuously show up with greater frequency in a short period of time when they attack systems. They are different from the normal traffic data and can be easily separated from normal activities. On the contrary, U2R and R2L attacks are embedded in the data portions of the packets and normally involve only a single connection. It becomes difficult to achieve satisfactory detection accuracy for detecting these two attacks. Therefore, we focus on studying the ambiguity problem between normal activities and U2R/R2L attacks. The goal is to build a detection system that can accurately and quickly detect these two attacks. In this dissertation, we design a two-phase intrusion detection approach. In the first phase, a correlation-based feature selection algorithm is proposed to advance the speed of detection. Features with poor prediction ability for the signatures of attacks and features inter-correlated with one or more other features are considered redundant. Such features are removed and only indispensable information about the original feature space remains. In the second phase, we develop an ensemble intrusion detection system to achieve accurate detection performance. The proposed method includes multiple feature selecting intrusion detectors and a data mining intrusion detector. The former ones consist of a set of detectors, and each of them uses a fuzzy clustering technique and belief theory to solve the ambiguity problem. The latter one applies data mining technique to automatically extract computer users’ normal behavior from training network traffic data. The final decision is a combination of the outputs of feature selecting and data mining detectors. The experimental results indicate that our ensemble approach not only significantly reduces the detection time but also effectively detect U2R and R2L attacks that contain degrees of ambiguous information.

Semantic distributed database management with applications to the Internet dissemination of environmental data

The research presented in this dissertation is comprised of several parts which jointly attain the goal of Semantic Distributed Database Management with Applications to Internet Dissemination of Environmental Data. ^ Part of the research into more effective and efficient data management has been pursued through enhancements to the Semantic Binary Object-Oriented database (Sem-ODB) such as more effective load balancing techniques for the database engine, and the use of Sem-ODB as a tool for integrating structured and unstructured heterogeneous data sources. Another part of the research in data management has pursued methods for optimizing queries in distributed databases through the intelligent use of network bandwidth; this has applications in networks that provide varying levels of Quality of Service or throughput. ^ The application of the Semantic Binary database model as a tool for relational database modeling has also been pursued. This has resulted in database applications that are used by researchers at the Everglades National Park to store environmental data and to remotely-sensed imagery. ^ The areas of research described above have contributed to the creation TerraFly, which provides for the dissemination of geospatial data via the Internet. TerraFly research presented herein ranges from the development of TerraFly's back-end database and interfaces, through the features that are presented to the public (such as the ability to provide autopilot scripts and on-demand data about a point), to applications of TerraFly in the areas of hazard mitigation, recreation, and aviation. ^

A study of the effects of a service-learning experience on student success at an urban community college

The purpose of this study was to explore the effects of a service-learning experience on student success as measured by class attendance, course completion, final course grades, and end-of-term evaluation data.^ Though many outcomes of service-learning experiences have been studied, including ethical values, self-esteem, student personal development, and career preparation, relatively few studies have been conducted on the effects of such experiences on academic achievement, and the studies that have been done have primarily studied students at traditional, four-year, residential universities.^ The study consisted of 286 students enrolled in six paired courses taught by five instructors at a community college in the Fall term 1996. One section of each pair (the control group) was taught using traditional subject matter and course materials and the other section of each pair (the treatment group) participated in a 20-hour required service-learning activity in addition to the regular course curriculum. The courses in the study included American History, Sociology, College Preparatory English, and Introduction to English Composition.^ The results of this study indicate that, overall, students who participated in a class in which service-learning was a requirement, achieved higher final course grades and reported greater satisfaction with the course, the instructor, the reading assignments, and the grading system, and the treatment section of one course pair had fewer absences. In addition, the faculty members reported that, in the treatment sections, class discussions were more stimulating, the sections seemed more vital in terms of student involvement, the students seemed more challenged academically, more motivated to learn, and seemed to exert more effort in the course. ^

Reformed county government structure and service delivery performance: An integrated study of Florida counties

The most fundamental and challenging function of government is the effective and efficient delivery of services to local taxpayers and businesses. Counties, once known as the “dark continent” of American government, have recently become a major player in the provision of services. Population growth and suburbanization have increased service demands while the counties' role as service provider to incorporated residents has also expanded due to additional federal and state mandates. County governments are under unprecedented pressure and scrutiny to meet citizens' and elected officials' demands for high quality, and equitable delivery of services at the lowest possible cost while contending with anti-tax sentiments, greatly decreased state and federal support, and exceptionally costly and complex health and public safety problems. ^ This study tested the reform government theory proposition that reformed structures of county government positively correlate with efficient service delivery. A county government reformed index was developed for this dissertation comprised of form of government, home-rule status, method of election, number of government jurisdictions, and number of elected officials. The county government reform index and a measure of relative structural fragmentation were used to assess their impact on two measures of service output: mean county road pavement condition and county road maintenance expenditures. The study's multi-level design triangulated results from different data sources and methods of analysis. Data were collected from semi-structured interviews of county officials, secondary archival sources, and a survey of 544 elected and appointed officials from Florida's 67 counties. The results of the three sources of data converged in finding that reformed Florida counties are more likely than unreformed counties to provide better road service and to spend less on road expenditures. The same results were found for unfragmented Florida counties. Because both the county government reform index and the fragmentation variables were specified acknowledging the reform theory as well as elements from the public-choice model, the results help explain contradicting findings in the urban service research. ^ Therefore, as suggested by the corroborated findings of this dissertation, reformed as well as unfragmented counties are better providers of road maintenance service and do so in a less costly manner. These findings hold although the variables were specified to capture theoretical arguments from the consolidated as well as the public-choice theories suggesting a way to advance the debate from the consolidated-fragmented dichotomy of urban governance. ^

Selected psychosocial and demographic factors affecting levels of pre-retirement planning

In September 2002, the State of Florida implemented a new retirement structure for those employed in the Florida Public School System. Teachers were given the option to maintain their existing defined benefit plan or choose the newly offered defined contribution plan. The variables that affect planning for retirement are innumerable. Identifying the most significant variables is essential to understanding how one plans for retirement. ^ This study examined the relationship between hypothesized psychosocial and demographic factors and an individual's level of pre-retirement planning. The criterion variable, the level of pre-retirement planning, comprised two concepts. First, the time spent thinking about retirement was determined by the score an individual received on a pre-retirement planning scale. This scale included the concepts of information gathering, goals, anticipated resources, and long-range planning. Second, implementation of retirement plan procedures was determined by the percentage an individual annually deferred to retirement. ^ The survey used for data collection contained 50 close-ended items. It was distributed to all full-time teachers in nine randomly selected elementary, middle, and senior high schools throughout Miami-Dade County Public Schools. Multiple regression and crosstabulation indicated that math anxiety, general risk, years of service, and total family income were significant predictors of the level of pre-retirement planning, as measured by the pre-retirement planning scale. In addition, the statistical analysis indicated that math anxiety, internal locus of control, years of service, and total family income were significant predictors of the level pre-retirement planning, as measured by the amount deferred to retirement. An individual's level of math anxiety and family income were the two factors that were the most significant predictors for both concepts on the level of pre-retirement planning. ^ Based on the findings of the study, recommendations focused on assessing an individual's level of math anxiety and educating teachers, particularly pre-service candidates, about the factors that affect pre-retirement planning. Further research should investigate the benefit of such educational programs. ^