7 resultados para MULTIPLICITY
em Digital Commons at Florida International University
Resumo:
This study examines the congruency of planning between organizational structure and process, through an evaluation and planning model known as the Micro/Macro Dynamic Planning Grid. The model compares day-to-day planning within an organization to planning imposed by organizational administration and accrediting agencies. A survey instrument was developed to assess the micro and macro sociological analysis elements utilized by an organization.^ The Micro/Macro Dynamic Planning Grid consists of four quadrants. Each quadrant contains characteristics that reflect the interaction between the micro and macro elements of planning, objectives and goals within an organization. The Over Macro/Over Micro, Quadrant 1, contains attributes that reflect a tremendous amount of action and ongoing adjustments, typical of an organization undergoing significant changes in either leadership, program and/or structure. Over Macro/Under Micro, Quadrant 2, reflects planning characteristics found in large, bureaucratic systems with little regard given to the workings of their component parts. Under Macro/Under Micro, Quadrant 3, reflects the uncooperative, uncoordinated organization, one that contains a multiplicity of viewpoints, language, objectives and goals. Under Macro/Under Micro, Quadrant 4 represents the worst case scenario for any organization. The attributes of this quadrant are very reactive, chaotic, non-productive and redundant.^ There were three phases to the study: development of the initial instrument, pilot testing the initial instrument and item revision, and administration and assessment of the refined instrument. The survey instrument was found to be valid and reliable for the purposes and audiences herein described.^ In order to expand the applicability of the instrument to other organizational settings, the survey was administered to three professional colleges within a university.^ The first three specific research questions collectively answered, in the affirmative, the basic research question: Can the Micro/Macro Dynamic Planning Grid be applied to an organization through an organizational development tool? The first specific question: Can an instrument be constructed that applies the Micro/Macro Dynamic Planning Grid? The second specific research question: Is the constructed instrument valid and reliable? The third specific research question: Does an instrument that applies the Micro/Macro Dynamic Planning Grid assess congruency of micro and macro planning, goals and objectives within an organization? The fourth specific research question: What are the differences in the responses based on roles and responsibilities within an organization? involved statistical analysis of the response data and comparisons obtained with the demographic data. (Abstract shortened by UMI.) ^
Resumo:
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.^
Resumo:
Identity studies of immigrants are complex because of multiple influences affecting identity reconstruction during immigration and acculturation: nationality, socio-cultural differences, occupations, education, spatial and geographic locations, age, gender, and personal attributes. Most immigrant identity studies deal with lower-income immigrants, who do not have the resources of middle- and upper-middle-class immigrants. South Florida is “home” to many middle-class immigrants, including Dominican-Americans. This dissertation interviewed sixty-six Dominican immigrants in South Florida, in order to determine their reconstructed identities after immigration/resettlement and to discover what influences contributed to these changes in identities. ^ The research design of this dissertation utilized an inductive, qualitative model, with the “grounded theory” method of data collection, categorization, and analysis. Participants were selected by a snowball sampling and interviewed with an informal questionnaire. Results were transcribed, categorized, tabulated, and analyzed for conclusions and theorization on immigrant identity. ^ The dissertation addressed numerous influences relating to identity reconstruction: the differing circumstances of immigration, the unique resources of middle- and higher-class immigrants, the nurturing environment of South Florida for immigrants with education and professional skills, and the boundary protection offered by suburban spaces. The interviewees displayed a wide range of age, length of residence in the United States, reasons for immigration, entry ports, settlement, relocations, occupations, and claimed identities. Identity was cross-tabulated with the various influences, as a means of invalidating certain influences and indicating possible trends. ^ The dissertation concluded that middle-class immigrant identities are diverse and multiple, as are the related influences. None of these immigrants had become totally assimilated, nor have they retained dual, non-overlapping attachments or frames of reference. Instead, many of the immigrants seemed to have developed or negotiated two or more identities, according to need, context, and personal interest. A cosmopolitan community such as South Florida seems to have encouraged such multiplicity of identity. However, rather than forming free-flowing identities, most of these immigrants eventually developed diverse and hybrid identities that have bounded attachments to various networks, groups, and places in South Florida. ^
Resumo:
With the introduction of new input devices, such as multi-touch surface displays, the Nintendo WiiMote, the Microsoft Kinect, and the Leap Motion sensor, among others, the field of Human-Computer Interaction (HCI) finds itself at an important crossroads that requires solving new challenges. Given the amount of three-dimensional (3D) data available today, 3D navigation plays an important role in 3D User Interfaces (3DUI). This dissertation deals with multi-touch, 3D navigation, and how users can explore 3D virtual worlds using a multi-touch, non-stereo, desktop display. ^ The contributions of this dissertation include a feature-extraction algorithm for multi-touch displays (FETOUCH), a multi-touch and gyroscope interaction technique (GyroTouch), a theoretical model for multi-touch interaction using high-level Petri Nets (PeNTa), an algorithm to resolve ambiguities in the multi-touch gesture classification process (Yield), a proposed technique for navigational experiments (FaNS), a proposed gesture (Hold-and-Roll), and an experiment prototype for 3D navigation (3DNav). The verification experiment for 3DNav was conducted with 30 human-subjects of both genders. The experiment used the 3DNav prototype to present a pseudo-universe, where each user was required to find five objects using the multi-touch display and five objects using a game controller (GamePad). For the multi-touch display, 3DNav used a commercial library called GestureWorks in conjunction with Yield to resolve the ambiguity posed by the multiplicity of gestures reported by the initial classification. The experiment compared both devices. The task completion time with multi-touch was slightly shorter, but the difference was not statistically significant. The design of experiment also included an equation that determined the level of video game console expertise of the subjects, which was used to break down users into two groups: casual users and experienced users. The study found that experienced gamers performed significantly faster with the GamePad than casual users. When looking at the groups separately, casual gamers performed significantly better using the multi-touch display, compared to the GamePad. Additional results are found in this dissertation.^
Resumo:
With the introduction of new input devices, such as multi-touch surface displays, the Nintendo WiiMote, the Microsoft Kinect, and the Leap Motion sensor, among others, the field of Human-Computer Interaction (HCI) finds itself at an important crossroads that requires solving new challenges. Given the amount of three-dimensional (3D) data available today, 3D navigation plays an important role in 3D User Interfaces (3DUI). This dissertation deals with multi-touch, 3D navigation, and how users can explore 3D virtual worlds using a multi-touch, non-stereo, desktop display. The contributions of this dissertation include a feature-extraction algorithm for multi-touch displays (FETOUCH), a multi-touch and gyroscope interaction technique (GyroTouch), a theoretical model for multi-touch interaction using high-level Petri Nets (PeNTa), an algorithm to resolve ambiguities in the multi-touch gesture classification process (Yield), a proposed technique for navigational experiments (FaNS), a proposed gesture (Hold-and-Roll), and an experiment prototype for 3D navigation (3DNav). The verification experiment for 3DNav was conducted with 30 human-subjects of both genders. The experiment used the 3DNav prototype to present a pseudo-universe, where each user was required to find five objects using the multi-touch display and five objects using a game controller (GamePad). For the multi-touch display, 3DNav used a commercial library called GestureWorks in conjunction with Yield to resolve the ambiguity posed by the multiplicity of gestures reported by the initial classification. The experiment compared both devices. The task completion time with multi-touch was slightly shorter, but the difference was not statistically significant. The design of experiment also included an equation that determined the level of video game console expertise of the subjects, which was used to break down users into two groups: casual users and experienced users. The study found that experienced gamers performed significantly faster with the GamePad than casual users. When looking at the groups separately, casual gamers performed significantly better using the multi-touch display, compared to the GamePad. Additional results are found in this dissertation.
Resumo:
This study was conducted to gain a more comprehensive understanding of HIV risk among Haitian women. The variables measured were: knowledge of HIV transmission, sexual risk behaviors, and perceptions of risk among Haitian women. The sociocultural aspect of the Haitian women's lives with regard to their risky behaviors was also examined. A total of 101 Haitian women (aged 25-53) who attended two comprehensive health clinics were interviewed. A combined questionnaire derived from both the ARM-Q and the RBA was used. In general, the women had good knowledge of the sexual transmission of HIV I AIDS and indicated that they were susceptible to HIV infection. However, knowledge and perceptions of risk were not translated into sexual risk-reduction behaviors with their partners. Multiplicity of partners and low incidence of condom use were the two major sexual risk factors isolated in this study. Results indicate Haitian women were more likely to use condoms if they possessed greater HIV knowledge and their sexual partners held more positive attitudes toward using condoms. Also, Haitian women may have failed to protect themselves because behavior changes could have involved threats to their social and economic survival, relationships and culturally sanctioned roles. This suggests the need to include male partners in HIV prevention interventions with Haitian women. Future research should focus on preventing high-risk behavior by improving knowledge, altering the male partners' attitudes toward condoms, and enhancing communication and negotiation skills. Nursing implications and recommendations for culturally sensitive and relevant AIDS prevention efforts are discussed.
Resumo:
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.