Application of a SPH depth-integrated model to landslide run-out analysis

Hazard and risk assessment of landslides with potentially long run-out is becoming more and more important. Numerical tools exploiting different constitutive models, initial data and numerical solution techniques are important for making the expert’s assessment more objective, even though they cannot substitute for the expert’s understanding of the site-specific conditions and the involved processes. This paper presents a depth-integrated model accounting for pore water pressure dissipation and applications both to real events and problems for which analytical solutions exist. The main ingredients are: (i) The mathematical model, which includes pore pressure dissipation as an additional equation. This makes possible to model flowslide problems with a high mobility at the beginning, the landslide mass coming to rest once pore water pressures dissipate. (ii) The rheological models describing basal friction: Bingham, frictional, Voellmy and cohesive-frictional viscous models. (iii) We have implemented simple erosion laws, providing a comparison between the approaches of Egashira, Hungr and Blanc. (iv) We propose a Lagrangian SPH model to discretize the equations, including pore water pressure information associated to the moving SPH nodes

Co-simulation Methodologies for Hybrid and Electric Vehicle Dynamics

In recent decades, full electric and hybrid electric vehicles have emerged as an alternative to conventional cars due to a range of factors, including environmental and economic aspects. These vehicles are the result of considerable efforts to seek ways of reducing the use of fossil fuel for vehicle propulsion. Sophisticated technologies such as hybrid and electric powertrains require careful study and optimization. Mathematical models play a key role at this point. Currently, many advanced mathematical analysis tools, as well as computer applications have been built for vehicle simulation purposes. Given the great interest of hybrid and electric powertrains, along with the increasing importance of reliable computer-based models, the author decided to integrate both aspects in the research purpose of this work. Furthermore, this is one of the first final degree projects held at the ETSII (Higher Technical School of Industrial Engineers) that covers the study of hybrid and electric propulsion systems. The present project is based on MBS3D 2.0, a specialized software for the dynamic simulation of multibody systems developed at the UPM Institute of Automobile Research (INSIA). Automobiles are a clear example of complex multibody systems, which are present in nearly every field of engineering. The work presented here benefits from the availability of MBS3D software. This program has proven to be a very efficient tool, with a highly developed underlying mathematical formulation. On this basis, the focus of this project is the extension of MBS3D features in order to be able to perform dynamic simulations of hybrid and electric vehicle models. This requires the joint simulation of the mechanical model of the vehicle, together with the model of the hybrid or electric powertrain. These sub-models belong to completely different physical domains. In fact the powertrain consists of energy storage systems, electrical machines and power electronics, connected to purely mechanical components (wheels, suspension, transmission, clutch…). The challenge today is to create a global vehicle model that is valid for computer simulation. Therefore, the main goal of this project is to apply co-simulation methodologies to a comprehensive model of an electric vehicle, where sub-models from different areas of engineering are coupled. The created electric vehicle (EV) model consists of a separately excited DC electric motor, a Li-ion battery pack, a DC/DC chopper converter and a multibody vehicle model. Co-simulation techniques allow car designers to simulate complex vehicle architectures and behaviors, which are usually difficult to implement in a real environment due to safety and/or economic reasons. In addition, multi-domain computational models help to detect the effects of different driving patterns and parameters and improve the models in a fast and effective way. Automotive designers can greatly benefit from a multidisciplinary approach of new hybrid and electric vehicles. In this case, the global electric vehicle model includes an electrical subsystem and a mechanical subsystem. The electrical subsystem consists of three basic components: electric motor, battery pack and power converter. A modular representation is used for building the dynamic model of the vehicle drivetrain. This means that every component of the drivetrain (submodule) is modeled separately and has its own general dynamic model, with clearly defined inputs and outputs. Then, all the particular submodules are assembled according to the drivetrain configuration and, in this way, the power flow across the components is completely determined. Dynamic models of electrical components are often based on equivalent circuits, where Kirchhoff’s voltage and current laws are applied to draw the algebraic and differential equations. Here, Randles circuit is used for dynamic modeling of the battery and the electric motor is modeled through the analysis of the equivalent circuit of a separately excited DC motor, where the power converter is included. The mechanical subsystem is defined by MBS3D equations. These equations consider the position, velocity and acceleration of all the bodies comprising the vehicle multibody system. MBS3D 2.0 is entirely written in MATLAB and the structure of the program has been thoroughly studied and understood by the author. MBS3D software is adapted according to the requirements of the applied co-simulation method. Some of the core functions are modified, such as integrator and graphics, and several auxiliary functions are added in order to compute the mathematical model of the electrical components. By coupling and co-simulating both subsystems, it is possible to evaluate the dynamic interaction among all the components of the drivetrain. ‘Tight-coupling’ method is used to cosimulate the sub-models. This approach integrates all subsystems simultaneously and the results of the integration are exchanged by function-call. This means that the integration is done jointly for the mechanical and the electrical subsystem, under a single integrator and then, the speed of integration is determined by the slower subsystem. Simulations are then used to show the performance of the developed EV model. However, this project focuses more on the validation of the computational and mathematical tool for electric and hybrid vehicle simulation. For this purpose, a detailed study and comparison of different integrators within the MATLAB environment is done. Consequently, the main efforts are directed towards the implementation of co-simulation techniques in MBS3D software. In this regard, it is not intended to create an extremely precise EV model in terms of real vehicle performance, although an acceptable level of accuracy is achieved. The gap between the EV model and the real system is filled, in a way, by introducing the gas and brake pedals input, which reflects the actual driver behavior. This input is included directly in the differential equations of the model, and determines the amount of current provided to the electric motor. For a separately excited DC motor, the rotor current is proportional to the traction torque delivered to the car wheels. Therefore, as it occurs in the case of real vehicle models, the propulsion torque in the mathematical model is controlled through acceleration and brake pedal commands. The designed transmission system also includes a reduction gear that adapts the torque coming for the motor drive and transfers it. The main contribution of this project is, therefore, the implementation of a new calculation path for the wheel torques, based on performance characteristics and outputs of the electric powertrain model. Originally, the wheel traction and braking torques were input to MBS3D through a vector directly computed by the user in a MATLAB script. Now, they are calculated as a function of the motor current which, in turn, depends on the current provided by the battery pack across the DC/DC chopper converter. The motor and battery currents and voltages are the solutions of the electrical ODE (Ordinary Differential Equation) system coupled to the multibody system. Simultaneously, the outputs of MBS3D model are the position, velocity and acceleration of the vehicle at all times. The motor shaft speed is computed from the output vehicle speed considering the wheel radius, the gear reduction ratio and the transmission efficiency. This motor shaft speed, somehow available from MBS3D model, is then introduced in the differential equations corresponding to the electrical subsystem. In this way, MBS3D and the electrical powertrain model are interconnected and both subsystems exchange values resulting as expected with tight-coupling approach.When programming mathematical models of complex systems, code optimization is a key step in the process. A way to improve the overall performance of the integration, making use of C/C++ as an alternative programming language, is described and implemented. Although this entails a higher computational burden, it leads to important advantages regarding cosimulation speed and stability. In order to do this, it is necessary to integrate MATLAB with another integrated development environment (IDE), where C/C++ code can be generated and executed. In this project, C/C++ files are programmed in Microsoft Visual Studio and the interface between both IDEs is created by building C/C++ MEX file functions. These programs contain functions or subroutines that can be dynamically linked and executed from MATLAB. This process achieves reductions in simulation time up to two orders of magnitude. The tests performed with different integrators, also reveal the stiff character of the differential equations corresponding to the electrical subsystem, and allow the improvement of the cosimulation process. When varying the parameters of the integration and/or the initial conditions of the problem, the solutions of the system of equations show better dynamic response and stability, depending on the integrator used. Several integrators, with variable and non-variable step-size, and for stiff and non-stiff problems are applied to the coupled ODE system. Then, the results are analyzed, compared and discussed. From all the above, the project can be divided into four main parts: 1. Creation of the equation-based electric vehicle model; 2. Programming, simulation and adjustment of the electric vehicle model; 3. Application of co-simulation methodologies to MBS3D and the electric powertrain subsystem; and 4. Code optimization and study of different integrators. Additionally, in order to deeply understand the context of the project, the first chapters include an introduction to basic vehicle dynamics, current classification of hybrid and electric vehicles and an explanation of the involved technologies such as brake energy regeneration, electric and non-electric propulsion systems for EVs and HEVs (hybrid electric vehicles) and their control strategies. Later, the problem of dynamic modeling of hybrid and electric vehicles is discussed. The integrated development environment and the simulation tool are also briefly described. The core chapters include an explanation of the major co-simulation methodologies and how they have been programmed and applied to the electric powertrain model together with the multibody system dynamic model. Finally, the last chapters summarize the main results and conclusions of the project and propose further research topics. In conclusion, co-simulation methodologies are applicable within the integrated development environments MATLAB and Visual Studio, and the simulation tool MBS3D 2.0, where equation-based models of multidisciplinary subsystems, consisting of mechanical and electrical components, are coupled and integrated in a very efficient way.

Hybrid wind-diesel power plant valuation and optimization using real option theory and dynamic programming

El sistema de energía eólica-diesel híbrido tiene un gran potencial en la prestación de suministro de energía a comunidades remotas. En comparación con los sistemas tradicionales de diesel, las plantas de energía híbridas ofrecen grandes ventajas tales como el suministro de capacidad de energía extra para "microgrids", reducción de los contaminantes y emisiones de gases de efecto invernadero, y la cobertura del riesgo de aumento inesperado del precio del combustible. El principal objetivo de la presente tesis es proporcionar nuevos conocimientos para la evaluación y optimización de los sistemas de energía híbrido eólico-diesel considerando las incertidumbres. Dado que la energía eólica es una variable estocástica, ésta no puede ser controlada ni predecirse con exactitud. La naturaleza incierta del viento como fuente de energía produce serios problemas tanto para la operación como para la evaluación del valor del sistema de energía eólica-diesel híbrido. Por un lado, la regulación de la potencia inyectada desde las turbinas de viento es una difícil tarea cuando opera el sistema híbrido. Por otro lado, el bene.cio económico de un sistema eólico-diesel híbrido se logra directamente a través de la energía entregada a la red de alimentación de la energía eólica. Consecuentemente, la incertidumbre de los recursos eólicos incrementa la dificultad de estimar los beneficios globales en la etapa de planificación. La principal preocupación del modelo tradicional determinista es no tener en cuenta la incertidumbre futura a la hora de tomar la decisión de operación. Con lo cual, no se prevé las acciones operativas flexibles en respuesta a los escenarios futuros. El análisis del rendimiento y simulación por ordenador en el Proyecto Eólico San Cristóbal demuestra que la incertidumbre sobre la energía eólica, las estrategias de control, almacenamiento de energía, y la curva de potencia de aerogeneradores tienen un impacto significativo sobre el rendimiento del sistema. En la presente tesis, se analiza la relación entre la teoría de valoración de opciones y el proceso de toma de decisiones. La opción real se desarrolla con un modelo y se presenta a través de ejemplos prácticos para evaluar el valor de los sistemas de energía eólica-diesel híbridos. Los resultados muestran que las opciones operacionales pueden aportar un valor adicional para el sistema de energía híbrida, cuando esta flexibilidad operativa se utiliza correctamente. Este marco se puede aplicar en la optimización de la operación a corto plazo teniendo en cuenta la naturaleza dependiente de la trayectoria de la política óptima de despacho, dadas las plausibles futuras realizaciones de la producción de energía eólica. En comparación con los métodos de valoración y optimización existentes, el resultado del caso de estudio numérico muestra que la política de operación resultante del modelo de optimización propuesto presenta una notable actuación en la reducción del con- sumo total de combustible del sistema eólico-diesel. Con el .n de tomar decisiones óptimas, los operadores de plantas de energía y los gestores de éstas no deben centrarse sólo en el resultado directo de cada acción operativa, tampoco deberían tomar decisiones deterministas. La forma correcta es gestionar dinámicamente el sistema de energía teniendo en cuenta el valor futuro condicionado en cada opción frente a la incertidumbre. ABSTRACT Hybrid wind-diesel power systems have a great potential in providing energy supply to remote communities. Compared with the traditional diesel systems, hybrid power plants are providing many advantages such as providing extra energy capacity to the micro-grid, reducing pollution and greenhouse-gas emissions, and hedging the risk of unexpected fuel price increases. This dissertation aims at providing novel insights for assessing and optimizing hybrid wind-diesel power systems considering the related uncertainties. Since wind power can neither be controlled nor accurately predicted, the energy harvested from a wind turbine may be considered a stochastic variable. This uncertain nature of wind energy source results in serious problems for both the operation and value assessment of the hybrid wind-diesel power system. On the one hand, regulating the uncertain power injected from wind turbines is a difficult task when operating the hybrid system. On the other hand, the economic profit of a hybrid wind-diesel system is achieved directly through the energy delivered to the power grid from the wind energy. Therefore, the uncertainty of wind resources has increased the difficulty in estimating the total benefits in the planning stage. The main concern of the traditional deterministic model is that it does not consider the future uncertainty when making the dispatch decision. Thus, it does not provide flexible operational actions in response to the uncertain future scenarios. Performance analysis and computer simulation on the San Cristobal Wind Project demonstrate that the wind power uncertainty, control strategies, energy storage, and the wind turbine power curve have a significant impact on the performance of the system. In this dissertation, the relationship between option pricing theory and decision making process is discussed. A real option model is developed and presented through practical examples for assessing the value of hybrid wind-diesel power systems. Results show that operational options can provide additional value to the hybrid power system when this operational flexibility is correctly utilized. This framework can be applied in optimizing short term dispatch decisions considering the path-dependent nature of the optimal dispatch policy, given the plausible future realizations of the wind power production. Comparing with the existing valuation and optimization methods, result from numerical example shows that the dispatch policy resulting from the proposed optimization model exhibits a remarkable performance in minimizing the total fuel consumption of the wind-diesel system. In order to make optimal decisions, power plant operators and managers should not just focus on the direct outcome of each operational action; neither should they make deterministic decisions. The correct way is to dynamically manage the power system by taking into consideration the conditional future value in each option in response to the uncertainty.

Hybrid thermionic-photovoltaic converter

A conceptual device for the direct conversion of heat into electricity is presented. This concept hybridizes thermionic (TI) and thermophotovoltaic (TPV) energy conversion in a single thermionic-photovoltaic (TIPV) solid-state device. This device transforms into electricity both the electron and photon fluxes emitted by an incandescent surface. This letter presents an idealized analysis of this device in order to determine its theoretical potential. According to this analysis, the key advantage of this converter, with respect to either TPV or TI, is the higher power density in an extended temperature range. For low temperatures, TIPV performs like TPV due to the negligible electron flux. On the contrary, for high temperatures, TIPV performs like TI due to the great enhancement of the electron flux, which overshadows the photon flux contribution. At the intermediate temperatures, 1650K in the case of this particular study, I show that the power density potential of TIPV converter is twice as great as that of TPV and TI. The greatest impact concerns applications in which the temperature varies in a relatively wide range, for which averaged power density enhancement above 500% is attainable. (C) 2016 AIP Publishing LLC.

Equipo de medición de estrés portable con conectividad a plataforma a través del SmartPhone

Durante este trabajo fin de grado (TFG), se ha hecho uso del módulo GSR (o módulo Stress) de la empresa RGB Medical Devices, para crear una aplicación Android que recoja la información enviada por dicho módulo a través del Bluetooth del SmartPhone y la muestre en pantalla en tiempo real.

API REST con MEAN para contenidos multimedia

Memoria de Proyecto Fin de Grado API REST con MEAN para Contenidos Multimedia. En ella se especifica todo el proceso de elaboración del proyecto, desde la confección de la idea, pasando por el análisis y la definición de requisitos de elaboración, hasta la entrega definitiva del producto final. El proyecto consta de dos bloques claramente diferenciados: Una documentación extensa de la línea de trabajo, con apoyo de diagramas, imágenes, descripciones y metodologías. Implementación de la línea de trabajo. Elaboración de una aplicación SW que presente una correspondencia con la temática del proyecto, la intención del mismo y los requisitos que se espera que la solución software satisfaga. Al ser un proyecto software, se ha seguido estándares de elaboración con la mayor fidelidad. Estos estándares de elaboración son tanto de documentación como de metodologías. La evolución del proyecto ha pasado por diferentes etapas. Las principales son las de análisis y recopilación de requisitos, diseño de la arquitectura, implementación de la solución software y validación de la misma.

Comparison of push-in and push-out tests for measuring interfacial shear strength in nano-reinforced composite materials

The influence of the carbon nanotubes (CNTs) content on the fiber/matrix interfacial shear strength (IFSS) in glass/fiber epoxy composites was measured by means of push-in and push-out tests. Both experimental methodologies provided equivalent values of the IFSS for each material. It was found that the dispersion of CNTs increased in IFSS by 19% in average with respect to the composite without CNTs. This improvement was reached with 0.3 wt.% of CNTs and increasing the CNT content up to 0.8 wt.% did not improve the interface strength.

Human activity recognition by inertial signals obtained from a smartphone

Human Activity Recognition (HAR) is an emerging research field with the aim to identify the actions carried out by a person given a set of observations and the surrounding environment. The wide growth in this research field inside the scientific community is mainly explained by the high number of applications that are arising in the last years. A great part of the most promising applications are related to the healthcare field, where it is possible to track the mobility of patients with motor dysfunction as also the physical activity in patients with cardiovascular risk. Until a few years ago, by using distinct kind of sensors, a patient follow-up was possible. However, far from being a long-term solution and with the smartphone irruption, that monitoring can be achieved in a non-invasive way by using the embedded smartphone’s sensors. For these reasons this Final Degree Project arises with the main target to evaluate new feature extraction techniques in order to carry out an activity and user recognition, and also an activity segmentation. The recognition is done thanks to the inertial signals integration obtained by two widespread sensors in the greater part of smartphones: accelerometer and gyroscope. In particular, six different activities are evaluated walking, walking-upstairs, walking-downstairs, sitting, standing and lying. Furthermore, a segmentation task is carried out taking into account the activities performed by thirty users. This can be done by using Hidden Markov Models and also a set of tools tested satisfactory in speech recognition: HTK (Hidden Markov Model Toolkit).

Human activity recognition by inertial signals obtained from a smartphone

El Reconocimiento de Actividades Humanas es un área de investigación emergente, cuyo objetivo principal es identificar las acciones realizadas por un sujeto analizando las señales obtenidas a partir de unos sensores. El rápido crecimiento de este área de investigación dentro de la comunidad científica se explica, en parte, por el elevado número de aplicaciones que están surgiendo en los últimos años. Gran parte de las aplicaciones más prometedoras se encuentran en el campo de la salud, donde se puede hacer un seguimiento del nivel de movilidad de pacientes con trastornos motores, así como monitorizar el nivel de actividad física en pacientes con riesgo cardiovascular. Hasta hace unos años, mediante el uso de distintos tipos de sensores se podía hacer un seguimiento del paciente. Sin embargo, lejos de ser una solución a largo plazo y gracias a la irrupción del teléfono inteligente, este seguimiento se puede hacer de una manera menos invasiva, haciendo uso de la gran variedad de sensores integrados en este tipo de dispositivos. En este contexto nace este Trabajo de Fin de Grado, cuyo principal objetivo es evaluar nuevas técnicas de extracción de características para llevar a cabo un reconocimiento de actividades y usuarios así como una segmentación de aquellas. Este reconocimiento se hace posible mediante la integración de señales inerciales obtenidas por dos sensores presentes en la gran mayoría de teléfonos inteligentes: acelerómetro y giróscopo. Concretamente, se evalúan seis tipos de actividades realizadas por treinta usuarios: andar, subir escaleras, bajar escaleras, estar sentado, estar de pie y estar tumbado. Además y de forma paralela, se realiza una segmentación temporal de los distintos tipos de actividades realizadas por dichos usuarios. Todo ello se llevará a cabo haciendo uso de los Modelos Ocultos de Markov, así como de un conjunto de herramientas probadas satisfactoriamente en reconocimiento del habla: HTK (Hidden Markov Model Toolkit).

A three-hybrid system to detect RNA-protein interactions in vivo.

RNA-protein interactions are pivotal in fundamental cellular processes such as translation, mRNA processing, early development, and infection by RNA viruses. However, in spite of the central importance of these interactions, few approaches are available to analyze them rapidly in vivo. We describe a yeast genetic method to detect and analyze RNA-protein interactions in which the binding of a bifunctional RNA to each of two hybrid proteins activates transcription of a reporter gene in vivo. We demonstrate that this three-hybrid system enables the rapid, phenotypic detection of specific RNA-protein interactions. As examples, we use the binding of the iron regulatory protein 1 (IRP1) to the iron response element (IRE), and of HIV trans-activator protein (Tat) to the HIV trans-activation response element (TAR) RNA sequence. The three-hybrid assay we describe relies only on the physical properties of the RNA and protein, and not on their natural biological activities; as a result, it may have broad application in the identification of RNA-binding proteins and RNAs, as well as in the detailed analysis of their interactions.

Locust adipokinetic hormones: carrier-independent transport and differential inactivation at physiological concentrations during rest and flight.

Since concomitant release of structurally related peptide hormones with apparently similar functions seems to be a general concept in endocrinology, we have studied the dynamics of the lifetime of the three known adipokinetic hormones (AKHs) of the migratory locust, which control flight-directed mobilization of carbohydrate and lipid from fat body stores. Although the structure of the first member of the AKHs has been known for 20 years, until now, reliable data on their inactivation and removal from the hemolymph are lacking, because measurement requires AKHs with high specific radioactivity. Employing tritiated AKHs with high specific radioactivity, obtained by catalytic reduction with tritium gas of the dehydroLeu2 analogues of the AKHs synthesized by the solid-phase procedure, studies with physiological doses of as low as 1.0 pmol per locust could be conducted. The AKHs appear to be transported in the hemolymph in their free forms and not associated with a carrier protein, despite their strong hydrophobicity. Application of AKHs in their free form in in vivo and in vitro studies therefore now has been justified. We have studied the degradation of the three AKHs during rest and flight. The first cleavage step by an endopeptidase is crucial, since the resulting degradation products lack any adipokinetic activity. Half-lives for AKH-I, -II and -III were 51, 40, and 5 min, respectively, for rest conditions and 35, 37, and 3 min, respectively, during flight. The rapid and differential degradation of structurally related hormones leads to changes in the ratio in which they are released and therefore will have important consequences for concerted hormone action at the level of the target organ or organs, suggesting that each of the known AKHs may play its own biological role in the overall syndrome of insect flight.

An interspecies hybrid RNA virus is significantly more virulent than either parental virus.

Cucumber mosaic cucumovirus (CMV) infects a very wide range of plant species (>1000 species). We recently demonstrated that a previously undescribed gene (2b) encoded by RNA 2 of the tripartite RNA genome of CMV is required for systemic virus spread and disease induction in its hosts. Herein we report that when this CMV gene is replaced by its homologue from tomato aspermy cucumovirus (TAV), the resultant hybrid virus is significantly more virulent, induces earlier onset of systemic symptoms, and accumulates to a higher level in seven host species from three families than either of the parents. Our results indicate that CMV and the TAV 2b protein interact synergistically despite the fact that no synergism occurs in double infections with the two parental viruses. To our knowledge, this is the first example of an interspecific hybrid made from plant or animal RNA viruses that is more efficient in systemic infection of a number of hosts than the naturally occurring parents. As CMV and the hybrid virus accumulated to a similar level in the infected tobacco protoplasts, the observed synergistic responses most likely resulted from an increased efficacy of the hybrid virus in systemic spread in host plants provided by the TAV 2b protein. The relevance of our finding to the application of pathogen-derived resistance is discussed.

Measurement of the cosmic ray energy spectrum using hybrid events of the Pierre Auger Observatory

The energy spectrum of ultra-high energy cosmic rays above 10(18)eV is measured using the hybrid events collected by the Pierre Auger Observatory between November 2005 and September 2010. The large exposure of the Observatory allows the measurement of the main features of the energy spectrum with high statistics. Full Monte Carlo simulations of the extensive air showers (based on the CORSIKA code) and of the hybrid detector response are adopted here as an independent cross check of the standard analysis (Phys. Lett. B 685, 239 (2010)). The dependence on mass composition and other systematic uncertainties are discussed in detail and, in the full Monte Carlo approach, a region of confidence for flux measurements is defined when all the uncertainties are taken into account. An update is also reported of the energy spectrum obtained by combining the hybrid spectrum and that measured using the surface detector array.

The Hybrid Spirit Animating Chinese Pentecostals in Malaysia

This dissertation interrogates the assertion in postcolonial scholarship, especially from the work of Homi Bhabha that the construction and performance of hybrid identities act as a form of resistance for marginalized communities against structures of oppression. While this study supports this assertion, it also critiques how hybridity fails to address issues of unequal power relations. This has led to an uncritical use of hybridity that reproduces the very idea of static identity which its proponents claim to transcend. Through qualitative study of Chinese members of a Pentecostal church in Malaysia, this study argues that church members engage in "unequal belonging" where they privilege certain elements of their identities over others. In concert with Pierre Bourdieu's conceptions of habitus, field, and capital, unequal belonging highlights how hybridity fails to capture the intersecting and competing loyalties, strategies, and complexities of identity formation on a contextual level. Unequal belonging challenges postcolonial scholars to locate the subtle workings of power and privilege that manifest even among marginalized communities. The study first situates the Chinese through an analysis of the historical legacy of British colonialism that has structured the country's current socio-political configuration along bounded categories of identification. The habitus constrains church members to accept certain Chinese ethnic markers as "givens." Although they face continuous marginalization, interviewee data demonstrates that church members negotiate their Chineseness and construct a "Modern Chinese" ethnic identity as a strategic move away from Chinese stereotypes. Moreover, conversion to Christianity affords church members access to cultural capital. Yet, it is limited and unequal capital. In particular, the "Chinese Chinese," who church members have demarcated as backward and traditional, are unable to gain access to this capital because they lack fluency in English and knowledge in modern, westernized worldviews. Unequal belonging nuances monolithic conceptions of hybridity. It demonstrates how church members' privilege of Christianity over Chineseness exposes the complex processes of power and privilege that makes westernized-English-speaking Chinese Christians culturally "higher" than non-English-speaking, non-Christian, Chinese. This study provides significant contribution to the complex aspect of hybridity where it is both a site of resistance and oppression.

Hybrid convex combinations for IIR system identification.

The low complexity of IIR adaptive filters (AFs) is specially appealing to realtime applications but some drawbacks have been preventing their widespread use so far. For gradient based IIR AFs, adverse operational conditions cause convergence problems in system identification scenarios: underdamped and clustered poles, undermodelling or non-white input signals lead to error surfaces where the adaptation nearly stops on large plateaus or get stuck at sub-optimal local minima that can not be identified as such a priori. Furthermore, the non-stationarity in the input regressor brought by the filter recursivity and the approximations made by the update rules of the stochastic gradient algorithms constrain the learning step size to small values, causing slow convergence. In this work, we propose IIR performance enhancement strategies based on hybrid combinations of AFs that achieve higher convergence rates than ordinary IIR AFs while keeping the stability.