9 resultados para non-parametric background modeling
em Digital Commons at Florida International University
Resumo:
Recent studies have reported alarmingly high rates of HIV infection and risky sexual behaviors among gay men in Miami, Florida. Previous research has suggested that the risky sexual behaviors of many gay men reflect the pursuit of intimacy and love, and that barriers to intimate relationships among gay men may stem from traditional masculinity norms. This dissertation examines the meanings which gay men ascribe to their sexual behaviors, as well as the intersections of those meanings with both traditional masculinity constructions and Miami's gay male sexual culture. ^ The study is based upon participant observation, print media content analysis, surveys and ethnographic interviews of a purposive snowball sample of 30 Cuban American, Puerto Rican, African American and Anglo gay men who reside in Miami-Dade County, Florida. Analysis of research questions was accomplished through grounded theory methods and descriptive and non-parametric statistics, including Pearson chi-square, Fisher's Exact and Mann-Whitney U tests. ^ The study shows that culturally-specified masculinity norms vary in the relative importance ascribed to heterosexual prowess, economic providership and competitiveness. These cultural differences appear important not only to the timing of sexual awareness and to the strength of homosexual stereotyping as effeminacy, but also to men's strategies in coming out as gay. The meanings men attributed to their sexual behaviors were, however, constructed in response to both inherited masculinity norms and the hypermasculine structure of Miami's gay male sexual culture. In addition to providing an ethnographic account of this subculture, the study elaborates men's issues relative to casual sex and committed relationships. Unprotected anal intercourse with casual partners during the previous twelve months was associated with growing up without one's father in the home, having been teased for effeminacy during childhood, being defensive about one's masculinity, not trusting men, having been cheated on by boyfriends, and believing that long-term gay male relationships are problematic. ^ It is concluded that the continuing epidemic of HIV infections among local gay men, as well as the hypermasculine form of the gay sexual subculture itself, are nihilistic symptoms embedded in the masculinist gender structure of the larger society. ^
Resumo:
This dissertation is one of the earliest to systematically apply and empirically test the resource-based view (RBV) in the context of nascent social ventures in a large scale study. Social ventures are entrepreneurial ventures organized as nonprofit, for-profit, or hybrid organizations whose primary purpose is to address unmet social needs and create social value. Nascent social ventures face resource gaps and engage in partnerships or alliances as one means to access external resources. These partnerships with different sectors facilitate social venture innovative and earned income strategies, and assist in the development of adequate heterogeneous resource conditions that impact competitive advantage. Competitive advantage in the context of nascent social ventures is achieved through the creation of value and the achievement of venture development activities and launching. The relationships between partnerships, heterogeneous resource conditions, strategies, and competitive advantage are analyzed in the context of nascent social ventures that participated in business plan competitions. A content analysis of 179 social venture business plans and an exploratory follow-up survey of 72 of these ventures are used to analyze these relationships using regression, ANOVA, correlations, t-tests, and non-parametric statistics. The findings suggest a significant positive relationship between competitive advantage and partnership diversity, heterogeneous resource conditions, social innovation, and earned income. Social capital is the type of resource most significantly related to competitive advantage. Founder previous start-up experience, client location, and business plan completeness are also found to be significant in the relationship between partnership diversity and competitive advantage. Finally the findings suggest that hybrid social ventures create a greater competitive advantage than nonprofit or for-profit social ventures. Consequently, this dissertation not only provides academics further insight into the factors that impact nascent social value creation, venture development, and ability to launch, but also offers practitioners guidance on how best to organize certain processes to create a competitive advantage. As a result more insight is gained into the nascent social venture creation process and how these ventures can have a greater impact on society.
Resumo:
This is a mixed methods study conducted in Guerrero, Mexico, at the end of the academic year 2005-2006. The purpose of this study was to capture the perceptions held by high school students, of both indigenous and non-indigenous background, regarding the intercultural university, as well as their conceptualization of multiculturalism.
Resumo:
Corporate executives closely monitor the accuracy of their hotels' occupancy fore- casts since important decisions are based upon these predictions. This study lists the criteria for selecting an appropriate error measure. It discusses several evaluation methods focusing on statistical significance tests and demonstrates the use of two adequate evaluation methods: Mincer- Zamowitz's efficiency test and Wilcoxon's Non-Parametric Matched-Pairs Signed- Ranks test.
Resumo:
In finance literature many economic theories and models have been proposed to explain and estimate the relationship between risk and return. Assuming risk averseness and rational behavior on part of the investor, the models are developed which are supposed to help in forming efficient portfolios that either maximize (minimize) the expected rate of return (risk) for a given level of risk (rates of return). One of the most used models to form these efficient portfolios is the Sharpe's Capital Asset Pricing Model (CAPM). In the development of this model it is assumed that the investors have homogeneous expectations about the future probability distribution of the rates of return. That is, every investor assumes the same values of the parameters of the probability distribution. Likewise financial volatility homogeneity is commonly assumed, where volatility is taken as investment risk which is usually measured by the variance of the rates of return. Typically the square root of the variance is used to define financial volatility, furthermore it is also often assumed that the data generating process is made of independent and identically distributed random variables. This again implies that financial volatility is measured from homogeneous time series with stationary parameters. In this dissertation, we investigate the assumptions of homogeneity of market agents and provide evidence for the case of heterogeneity in market participants' information, objectives, and expectations about the parameters of the probability distribution of prices as given by the differences in the empirical distributions corresponding to different time scales, which in this study are associated with different classes of investors, as well as demonstrate that statistical properties of the underlying data generating processes including the volatility in the rates of return are quite heterogeneous. In other words, we provide empirical evidence against the traditional views about homogeneity using non-parametric wavelet analysis on trading data, The results show heterogeneity of financial volatility at different time scales, and time-scale is one of the most important aspects in which trading behavior differs. In fact we conclude that heterogeneity as posited by the Heterogeneous Markets Hypothesis is the norm and not the exception.
Resumo:
This study computed trends in extreme precipitation events of Florida for 1950-2010. Hourly aggregated rainfall data from 24 stations of the National Climatic Data Centre were analyzed to derive time-series of extreme rainfalls for 12 durations, ranging from 1 hour to 7 day. Non-parametric Mann-Kendall test and Theil-Sen Approach were applied to detect the significance of trends in annual maximum rainfalls, number of above threshold events and average magnitude of above threshold events for four common analysis periods. Trend Free Pre-Whitening (TFPW) approach was applied to remove the serial correlations and bootstrap resampling approach was used to detect the field significance of trends. The results for annual maximum rainfall revealed dominant increasing trends at the statistical significance level of 0.10, especially for hourly events in longer period and daily events in recent period. The number of above threshold events exhibited strong decreasing trends for hourly durations in all time periods.
Resumo:
Clusters are aggregations of atoms or molecules, generally intermediate in size between individual atoms and aggregates that are large enough to be called bulk matter. Clusters can also be called nanoparticles, because their size is on the order of nanometers or tens of nanometers. A new field has begun to take shape called nanostructured materials which takes advantage of these atom clusters. The ultra-small size of building blocks leads to dramatically different properties and it is anticipated that such atomically engineered materials will be able to be tailored to perform as no previous material could.^ The idea of ionized cluster beam (ICB) thin film deposition technique was first proposed by Takagi in 1972. It was based upon using a supersonic jet source to produce, ionize and accelerate beams of atomic clusters onto substrates in a vacuum environment. Conditions for formation of cluster beams suitable for thin film deposition have only recently been established following twenty years of effort. Zinc clusters over 1,000 atoms in average size have been synthesized both in our lab and that of Gspann. More recently, other methods of synthesizing clusters and nanoparticles, using different types of cluster sources, have come under development.^ In this work, we studied different aspects of nanoparticle beams. The work includes refinement of a model of the cluster formation mechanism, development of a new real-time, in situ cluster size measurement method, and study of the use of ICB in the fabrication of semiconductor devices.^ The formation process of the vaporized-metal cluster beam was simulated and investigated using classical nucleation theory and one dimensional gas flow equations. Zinc cluster sizes predicted at the nozzle exit are in good quantitative agreement with experimental results in our laboratory.^ A novel in situ real-time mass, energy and velocity measurement apparatus has been designed, built and tested. This small size time-of-flight mass spectrometer is suitable to be used in our cluster deposition systems and does not suffer from problems related to other methods of cluster size measurement like: requirement for specialized ionizing lasers, inductive electrical or electromagnetic coupling, dependency on the assumption of homogeneous nucleation, limits on the size measurement and non real-time capability. Measured ion energies using the electrostatic energy analyzer are in good accordance with values obtained from computer simulation. The velocity (v) is measured by pulsing the cluster beam and measuring the time of delay between the pulse and analyzer output current. The mass of a particle is calculated from m = (2E/v$\sp2).$ The error in the measured value of background gas mass is on the order of 28% of the mass of one N$\sb2$ molecule which is negligible for the measurement of large size clusters. This resolution in cluster size measurement is very acceptable for our purposes.^ Selective area deposition onto conducting patterns overlying insulating substrates was demonstrated using intense, fully-ionized cluster beams. Parameters influencing the selectivity are ion energy, repelling voltage, the ratio of the conductor to insulator dimension, and substrate thickness. ^
Resumo:
Network simulation is an indispensable tool for studying Internet-scale networks due to the heterogeneous structure, immense size and changing properties. It is crucial for network simulators to generate representative traffic, which is necessary for effectively evaluating next-generation network protocols and applications. With network simulation, we can make a distinction between foreground traffic, which is generated by the target applications the researchers intend to study and therefore must be simulated with high fidelity, and background traffic, which represents the network traffic that is generated by other applications and does not require significant accuracy. The background traffic has a significant impact on the foreground traffic, since it competes with the foreground traffic for network resources and therefore can drastically affect the behavior of the applications that produce the foreground traffic. This dissertation aims to provide a solution to meaningfully generate background traffic in three aspects. First is realism. Realistic traffic characterization plays an important role in determining the correct outcome of the simulation studies. This work starts from enhancing an existing fluid background traffic model by removing its two unrealistic assumptions. The improved model can correctly reflect the network conditions in the reverse direction of the data traffic and can reproduce the traffic burstiness observed from measurements. Second is scalability. The trade-off between accuracy and scalability is a constant theme in background traffic modeling. This work presents a fast rate-based TCP (RTCP) traffic model, which originally used analytical models to represent TCP congestion control behavior. This model outperforms other existing traffic models in that it can correctly capture the overall TCP behavior and achieve a speedup of more than two orders of magnitude over the corresponding packet-oriented simulation. Third is network-wide traffic generation. Regardless of how detailed or scalable the models are, they mainly focus on how to generate traffic on one single link, which cannot be extended easily to studies of more complicated network scenarios. This work presents a cluster-based spatio-temporal background traffic generation model that considers spatial and temporal traffic characteristics as well as their correlations. The resulting model can be used effectively for the evaluation work in network studies.
Resumo:
Network simulation is an indispensable tool for studying Internet-scale networks due to the heterogeneous structure, immense size and changing properties. It is crucial for network simulators to generate representative traffic, which is necessary for effectively evaluating next-generation network protocols and applications. With network simulation, we can make a distinction between foreground traffic, which is generated by the target applications the researchers intend to study and therefore must be simulated with high fidelity, and background traffic, which represents the network traffic that is generated by other applications and does not require significant accuracy. The background traffic has a significant impact on the foreground traffic, since it competes with the foreground traffic for network resources and therefore can drastically affect the behavior of the applications that produce the foreground traffic. This dissertation aims to provide a solution to meaningfully generate background traffic in three aspects. First is realism. Realistic traffic characterization plays an important role in determining the correct outcome of the simulation studies. This work starts from enhancing an existing fluid background traffic model by removing its two unrealistic assumptions. The improved model can correctly reflect the network conditions in the reverse direction of the data traffic and can reproduce the traffic burstiness observed from measurements. Second is scalability. The trade-off between accuracy and scalability is a constant theme in background traffic modeling. This work presents a fast rate-based TCP (RTCP) traffic model, which originally used analytical models to represent TCP congestion control behavior. This model outperforms other existing traffic models in that it can correctly capture the overall TCP behavior and achieve a speedup of more than two orders of magnitude over the corresponding packet-oriented simulation. Third is network-wide traffic generation. Regardless of how detailed or scalable the models are, they mainly focus on how to generate traffic on one single link, which cannot be extended easily to studies of more complicated network scenarios. This work presents a cluster-based spatio-temporal background traffic generation model that considers spatial and temporal traffic characteristics as well as their correlations. The resulting model can be used effectively for the evaluation work in network studies.