891 resultados para Linear and multilinear programming
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We describe the linear and nonlinear optical transfer characteristics of a multi-resonance device consisting of two optical ring resonators coupled one to the other and to an optical waveguide. The propagation effects displayed by the device are compared with those of a sequence of fundamental ring resonators coupled to a waveguide.
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We study existence, stability, and dynamics of linear and nonlinear stationary modes propagating in radially symmetric multicore waveguides with balanced gain and loss. We demonstrate that, in general, the system can be reduced to an effective PT-symmetric dimer with asymmetric coupling. In the linear case, we find that there exist two modes with real propagation constants before an onset of the PT-symmetry breaking while other modes have always the propagation constants with nonzero imaginary parts. This leads to a stable (unstable) propagation of the modes when gain is localized in the core (ring) of the waveguiding structure. In the case of nonlinear response, we show that an interplay between nonlinearity, gain, and loss induces a high degree of instability, with only small windows in the parameter space where quasistable propagation is observed. We propose a novel stabilization mechanism based on a periodic modulation of both gain and loss along the propagation direction that allows bounded light propagation in the multicore waveguiding structures.
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Main styles, or paradigms of programming – imperative, functional, logic, and object-oriented – are shortly described and compared, and corresponding programming techniques are outlined. Programming languages are classified in accordance with the main style and techniques supported. It is argued that profound education in computer science should include learning base programming techniques of all main programming paradigms.
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We report on a new vector model of an erbium-doped fibre laser mode locked with carbon nanotubes. This model goes beyond the limitations of the previously used models based on either coupled nonlinear Schrödinger or Ginzburg-Landau equations. Unlike the previous models, it accounts for the vector nature of the interaction between an optical field and an erbium-doped active medium, slow relaxation dynamics of erbium ions, linear birefringence in a fibre, linear and circular birefringence of a laser cavity caused by in-cavity polarization controller and light-induced anisotropy caused by elliptically polarized pump field. Interplay of aforementioned factors changes coherent coupling of two polarization modes at a long time scale and so results in a new family of vector solitons (VSs) with fast and slowly evolving states of polarization. The observed VSs can be of interest in secure communications, trapping and manipulation of atoms and nanoparticles, control of magnetization in data storage devices and many other areas.
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A novel approach of normal ECG recognition based on scale-space signal representation is proposed. The approach utilizes curvature scale-space signal representation used to match visual objects shapes previously and dynamic programming algorithm for matching CSS representations of ECG signals. Extraction and matching processes are fast and experimental results show that the approach is quite robust for preliminary normal ECG recognition.
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A concept of educational game for learning programming languages is presented. The idea of learning programming languages and improving programming skills through programming game characters’ behavior is described. The learning course description rules for using in games are suggested. The concept is implemented in a game for learning C# programming language. A common game architecture is modified for using in the educational game. The game engine is built on the base of the graphical engine Ogre3D and extended with game logic. The game has been developed as an industry level commercial product and is planned for sale to educational institutions.
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Some aspects of design of the discriminant functions that in the best way separate points of predefined final sets are considered. The concept is introduced of the nested discriminant functions which allow to separate correctly points of any of the final sets. It is proposed to apply some methods of non-smooth optimization to solve arising extremal problems efficiently.
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The goal of this study was to examine the longitudinal effects of five family factors on alcohol use among adolescent males. The family factors included familism (family pride, loyalty, and cohesion), parent derogation (being put down by parents), parent/child communication, family alcohol problems and family drug problems. The study focused on the effects of the family factors reported by a sample of 451 White-non-Hispanic and African American males during early and mid-adolescence on (1) the intensity of alcohol use in mid-adolescence, and (2) the number of problems associated with alcohol use during the transition to young adulthood. The study also explored racial differences in the effects of the family factors. The data for this study were derived from a two-phase longitudinal epidemiologic cohort study of male and female adolescents enrolled in middle schools in Miami, FL. Data were collected at four points between 1990 and 2001. Linear and logistical regressions were used to analyze the effects of the family variables on the dependent variables. ^ The results of the analyses indicated that all of the family variables except family drug problems were statistically significant predictors of the level of alcohol use and alcohol-related problems. Familism had a moderate influence on both of the dependent variables at all data points, while parent derogation, parent/child communication and family alcohol problems were weak predictors. While the family factors varied by race, their impact on the dependent variables did not vary substantially. ^ This study had methodological shortcomings related to measurement and design that may have contributed to the weak influence of the variables. Future studies should explore possible mediating effects of these variables, and should employ more sensitive measures that are culturally appropriate. The results suggest that, since early family factors have long-term effects on children's substance-using behaviors, the family environment should be addressed in prevention and intervention efforts. ^
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Online learning systems (OLS) have become center stage for corporations and educational institutions as a competitive tool in the knowledge economy. The satisfaction construct has received extensive coverage in information systems literature as an indicator of effectiveness but has been criticized for lack of validity; yet, the value construct has been largely ignored, although it has a long history in psychology, sociology, and behavioral science. The purpose of this dissertation is to investigate the value and satisfaction constructs in the context of OLS, and their perceived by learners relationship for implied effectiveness of OLS. ^ First, a qualitative phase is employed to gather OLS values from learners' focus groups, followed by a pilot phase to refine a proposed instrument, and a main phase to validate the survey. Responses were received from 75 students in four focus groups, 141 in the pilot, and 207 the main survey. Extensive data cleaning and exploratory factor analysis were done to identify factors of learners' perceived value and satisfaction of OLS. Then, Value-Satisfaction grids and the Learners' Value Index of Satisfaction (LeVIS) were developed as benchmarking tools of OLS. Moreover, Multicriteria Decision Analysis (MCDA) techniques were employed to impute value from satisfaction scores in order to reduce survey response time. ^ The results provided four satisfaction and four value factors with high reliability (Cronbach's α). Moreover, value and satisfaction were found to have low linear and nonlinear correlations, indicating that they are two distinct uncorrelated constructs. This is consistent with the literature. Value-Satisfaction grids and the LeVIS index indicated relatively high effectiveness for technology and support characteristics, relatively low effectiveness for professor's characteristics, while course and learner characteristics indicated average effectiveness. ^ The main contributions of this study include identifying, defining, and articulating the relationship between value and satisfaction constructs as assessment of users' implied IS effectiveness, as well as assessing the accuracy of MCDA procedures to predict value scores, thus reducing by half the survey questionnaire size. ^
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This dissertation addressed two broad problems in international macroeconomics and conflict analysis. The first problem in the first chapter looked at the behavior of exchange rate and its interaction with industry-level tradable goods prices for three countries, USA, UK and Japan. This question has important monetary policy implications. Here, I computed to what extent changes in exchange rate affected prices of consumer, producer, and export goods. I also studied the timing of these changes in these prices. My results, based on thirty-four industrial prices for USA, UK and Japan, supported the view that changes in exchange rates significantly affect prices of industrial and consumer goods. It also provided an insight to the underlying economic process that led to changes in relative prices. ^ In the second chapter, I explored the predictability of future inflation by incorporating shocks to exchange rates and clearly specified the transmission mechanisms that link exchange rates to industry-level consumer and producer prices. Employing a variety of linear and state-of-the-art nonlinear models, I also predicted growth rates of future prices. Comparing levels of inflation obtained from the above approaches showed superiority of the structural model incorporating the exchange rate pass-through effect. ^ The second broad issue addressed in the third chapter of the dissertation investigated the economic motives for conflict, manifested by rebellion and civil war for seventeen Latin American countries. Based on the analytical framework of Garfinkel, Skaperdas and Syropoulos (2004), I employed ordinal regressions and Markov switching for a panel of seventeen countries to identify trade and openness factors responsible for conflict occurrence and intensity. The results suggested that increased trade openness reduced high intensity domestic conflicts but overdependence on agricultural exports, along with a lack of income earning opportunities lead to more conflicts. Thereafter, using the Cox Proportional Hazard model I studied “conflict duration” and found that over-reliance on agricultural exports explained a major part of the length of conflicts in addition to various socio-political factors. ^
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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.
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Dropout rates impacting students with high-incidence disabilities in American schools remain staggering (Bost, 2006; Hehir, 2005). Of this group, students with Emotional Behavioral Disorders (EBD) are at greatest risk. Despite the mandated national propagation of inclusion, students with EBD remain the least included and the least successful when included (Bost). Accordingly, this study investigated the potential significance of inclusive settings and other school-related variables within the context of promoting the graduation potential of students with Specific Learning Disabilities (SLD) or EBD. This mixed-methods study investigated specified school-related variables as likely dropout predictors, as well as the existence of first-order interactions among some of the variables. In addition, it portrayed the perspectives of students with SLD or EBD on the school-related variables that promote graduation. Accordingly, the sample was limited to students with SLD or EBD who had graduated or were close to graduation. For the quantitative component the numerical data were analyzed using linear and logistic regressions. For the qualitative component guided student interviews were conducted. Both strands were subsequently analyzed using Ridenour and Newman’s (2008) model where the quantitative hypotheses are tested and are later built-upon by the related qualitative meta-themes. Results indicated that a successful academic history, or obtaining passing grades was the only significant predictor of graduation potential when statistically controlling all the other variables. While at a marginal significance, results also yielded that students with SLD or EBD in inclusive settings experienced better academic results and behavioral outcomes than those in self-contained settings. Specifically, students with SLD or EBD in inclusive settings were found to be more likely to obtain passing grades and less likely to be suspended from school. Generally, the meta-themes yielded during the student interviews corroborated these findings as well as provided extensive insights on how students with disabilities view school within the context of promoting graduation. Based on the results yielded, provided the necessary academic accommodations and adaptations are in place, along with an effective behavioral program, inclusive settings can be utilized as drop-out prevention tools in special education.
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Renewable or sustainable energy (SE) sources have attracted the attention of many countries because the power generated is environmentally friendly, and the sources are not subject to the instability of price and availability. This dissertation presents new trends in the DC-AC converters (inverters) used in renewable energy sources, particularly for photovoltaic (PV) energy systems. A review of the existing technologies is performed for both single-phase and three-phase systems, and the pros and cons of the best candidates are investigated. In many modern energy conversion systems, a DC voltage, which is provided from a SE source or energy storage device, must be boosted and converted to an AC voltage with a fixed amplitude and frequency. A novel switching pattern based on the concept of the conventional space-vector pulse-width-modulated (SVPWM) technique is developed for single-stage, boost-inverters using the topology of current source inverters (CSI). The six main switching states, and two zeros, with three switches conducting at any given instant in conventional SVPWM techniques are modified herein into three charging states and six discharging states with only two switches conducting at any given instant. The charging states are necessary in order to boost the DC input voltage. It is demonstrated that the CSI topology in conjunction with the developed switching pattern is capable of providing the required residential AC voltage from a low DC voltage of one PV panel at its rated power for both linear and nonlinear loads. In a micro-grid, the active and reactive power control and consequently voltage regulation is one of the main requirements. Therefore, the capability of the single-stage boost-inverter in controlling the active power and providing the reactive power is investigated. It is demonstrated that the injected active and reactive power can be independently controlled through two modulation indices introduced in the proposed switching algorithm. The system is capable of injecting a desirable level of reactive power, while the maximum power point tracking (MPPT) dictates the desirable active power. The developed switching pattern is experimentally verified through a laboratory scaled three-phase 200W boost-inverter for both grid-connected and stand-alone cases and the results are presented.
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Background Low diet quality and depression symptoms are independently associated with poor glycemic control in subjects with type 2 diabetes (T2D); however, the relationship between them is unclear. The aim of this study was to determine the association between diet quality and symptoms of depression among Cuban-Americans with and without T2D living in South Florida. Methods Subjects (n = 356) were recruited from randomly selected mailing list. Diet quality was determined using the Healthy Eating Index-2005 (HEI-05) score. Symptoms of depression were assessed using the Beck Depression Inventory (BDI). Both linear and logistic regression analyses were run to determine whether or not these two variables were related. Symptoms of depression was the dependent variable and independent variables included HEI-05, gender, age, marital status, BMI, education level, A1C, employment status, depression medication, duration of diabetes, and diabetes status. Analysis of covariance was used to test for interactions among variables. Results An interaction between diabetes status, gender and HEI-05 was found (P = 0.011). Among males with a HEI-05 score ≤ 55.6, those with T2D had a higher mean BDI score than those without T2D (11.6 vs. 6.6 respectively, P = 0.028). Among males and females with a HEI-05 score ≤ 55.6, females without T2D had a higher mean BDI score compared to males without T2D (11.0 vs. 6.6 respectively, P = 0.012) Conclusions Differences in symptoms of depression according to diabetes status and gender are found in Cuban-Americans with low diet quality.
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The purpose of the study was to determine the degree of relationships among GRE scores, undergraduate GPA (UGPA), and success in graduate school, as measured by first year graduate GPA (FGPA), cumulative graduate GPA, and degree attainment status. A second aim of the study was to determine whether the relationships between the composite predictor (GRE scores and UGPA) and the three success measures differed by race/ethnicity and sex. A total of 7,367 graduate student records (masters, 5,990; doctoral: 1,377) from 2000 to 2010 were used to evaluate the relationships among GRE scores, UGPA and the three success measures. Pearson's correlation, multiple linear and logistic regression, and hierarchical multiple linear and logistic regression analyses were performed to answer the research questions. The results of the correlational analyses differed by degree level. For master's students, the ETS proposed prediction that GRE scores are valid predictors of first year graduate GPA was supported by the findings from the present study; however, for doctoral students, the proposed prediction was only partially supported. Regression and correlational analyses indicated that UGPA was the variable that consistently predicted all three success measures for both degree levels. The hierarchical multiple linear and logistic regression analyses indicated that at master's degree level, White students with higher GRE Quantitative Reasoning Test scores were more likely to attain a degree than Asian Americans, while International students with higher UGPA were more likely to attain a degree than White students. The relationships between the three predictors and the three success measures were not significantly different between men and women for either degree level. Findings have implications both for practice and research. They will provide graduate school administrators with institution-specific validity data for UGPA and the GRE scores, which can be referenced in making admission decisions, while they will provide empirical and professionally defensible evidence to support the current practice of using UGPA and GRE scores for admission considerations. In addition, new evidence relating to differential predictions will be useful as a resource reference for future GRE validation researchers.