Service quality and reliability assessment of mobile communication infrastructure

The service quality of any sector has two major aspects namely technical and functional. Technical quality can be attained by maintaining technical specification as decided by the organization. Functional quality refers to the manner which service is delivered to customer which can be assessed by the customer feed backs. A field survey was conducted based on the management tool SERVQUAL, by designing 28 constructs under 7 dimensions of service quality. Stratified sampling techniques were used to get 336 valid responses and the gap scores of expectations and perceptions are analyzed using statistical techniques to identify the weakest dimension. To assess the technical aspects of availability six months live outage data of base transceiver were collected. The statistical and exploratory techniques were used to model the network performance. The failure patterns have been modeled in competing risk models and probability distribution of service outage and restorations were parameterized. Since the availability of network is a function of the reliability and maintainability of the network elements, any service provider who wishes to keep up their service level agreements on availability should be aware of the variability of these elements and its effects on interactions. The availability variations were studied by designing a discrete time event simulation model with probabilistic input parameters. The probabilistic distribution parameters arrived from live data analysis was used to design experiments to define the availability domain of the network under consideration. The availability domain can be used as a reference for planning and implementing maintenance activities. A new metric is proposed which incorporates a consistency index along with key service parameters that can be used to compare the performance of different service providers. The developed tool can be used for reliability analysis of mobile communication systems and assumes greater significance in the wake of mobile portability facility. It is also possible to have a relative measure of the effectiveness of different service providers.

Fundamental interactions of molecules (Na_2, Na_3) with intense femtosecond laser pulses

The real-time dynamics of multiphoton ionization and fragmentation of molecules Na_2 and Na_3 has been studied in molecular beam experiments employing ion and electron spectroscopy together with femtosecond pump-probe techniques. Experiments with Na_2 and Na_3 reveal unexpected features of the dynamics of the absorption of several photons as seen in the one- and three-dimensional vibrational wave packet motion in different potential surfaces and in high laser fields: In Na_2 a second major resonance-enhanced multiphoton ionization (REMPI) process is observed, involving the excitation of two electrons and subsequent electronic autoionization. The possibility of controlling a reaction by controlling the duration of propagation of a wave packet on an electronically-excited surface is demonstrated. In high laser fields, the contributions from direct photoionization and from the second REMPI process to the total ion yield change, due to different populations in the electronic states participating in the multiphoton ionization (MPI) processes. In addition, a vibrational wave packet motion in the electronic ground state is induced through stimulated emission pumping by the pump laser. The 4^1 \summe^+_g shelf state of Na_2 is given as an example for performing frequency spectroscopy of highlying electronic states in the time domain. Pure wave packet effects, such as the spreading and the revival of a vibrational wave packet, are investigated. The three-dimensional wave packet motion in the Na_3 reflects the normal modes in the X and B states, and shows in addition the pseudorotational motion in the B state in real time.

Modeling of hybrid systems by piecewise decomposition

Piecewise linear models systems arise as mathematical models of systems in many practical applications, often from linearization for nonlinear systems. There are two main approaches of dealing with these systems according to their continuous or discrete-time aspects. We propose an approach which is based on the state transformation, more particularly the partition of the phase portrait in different regions where each subregion is modeled as a two-dimensional linear time invariant system. Then the Takagi-Sugeno model, which is a combination of local model is calculated. The simulation results show that the Alpha partition is well-suited for dealing with such a system

Determinantes de la deserción universitaria en la Facultad de Economía de la Universidad del Rosario

Este trabajo analiza el problema de la deserción estudiantil en la Facultad de Economía de la Universidad del Rosario, a través del estudio de los factores individuales, académicos y socioeconómicos que implican el riesgo de desertar. Con este objetivo, se utiliza el análisis de modelos de duración. Específi camente, se estima un modelo de riesgo proporcional de tiempo discreto con y sin heterogeneidad observada (Prentice- Gloeckler, 1978 y Meyer, 1980). Los resultados muestran que los estudiantes de sexo masculino, la vinculación de los estudiantes al mercado laboral y los estudiantes provenientes de otras regiones, tienen el mayor riesgo de deserción. Además, la edad del estudiante incrementa el riesgo, sin embargo, su efecto decrece marginalmente al aumentar la edad. Palabras clave: deserción estudiantil, modelos de duración, riesgo proporcional. Clasifi cación JEL: C41, C13, I21.

De la subjetividad y sujetos posibles. Un abordaje desde la metodología Foucaultiana.

En el marco teórico foucaultiano la subjetividad se entiende como un elemento que da cuenta de la experiencia de los sujetos, respondiendo a particularidades que se presentan en cada momento histórico. Se identifican tres ejes de análisis para el estudio de la subjetividad, los cuales son el saber, el poder y la verdad. Cada uno de ellos usa metodologías particulares para el abordaje de la subjetividad, así entonces se usa la arqueología, la genealogía y la ontología respectivamente. En este texto se realiza una exploración del concepto de subjetividad desde la obra de M. Foucault, con el fin de encontrar una metodología para el estudio e investigación de la subjetividad como concepto de vital importancia para el abordaje de fenómenos sociales y culturales. En un primer momento se describen dinámicas correspondientes al saber y los juegos de veridicción, en un segundo momento se describen dinámicas correspondientes al poder, donde se describen las fuerzas que intervienen en la disposición de un ordenamiento particular de la experiencia. Por último en un tercer lugar, se da paso al concepto de la verdad en relación con la constitución subjetiva, la relación entre los juegos de poder y saber, como sistemas de ordenamiento y la verdad como efecto de los mismos, de esta manera se habla del foco de experiencia como unidad y elemento objeto de análisis.

Grado de predicción del valor de las acciones ante nuevas emisiones en el sector de extracción de petróleo crudo y gas natural en Colombia, mediante modelos de caos y análisis recurrente

El presente trabajo se enfoca en el análisis de las acciones de Ecopetrol, empresa representativa del mercado de Extracción de Petróleo y Gas natural en Colombia (SP&G), durante el periodo, del 22 de mayo de 2012 al 30 de agosto de 2013. Durante este espacio de tiempo la acción sufrió una serie de variaciones en su precio las cuales se relacionaban a la nueva emisión de acciones que realizo la Compañía. Debido a este cambio en el comportamiento del activo se generaron una serie de interrogantes sobre, (i) la reacción del mercado ante diferentes sucesos ocurridos dentro de las firmas y en su entorno (ii) la capacidad de los modelos financieros de predecir y entender las posibles reacciones observadas de los activos (entendidos como deuda). Durante el desarrollo del presente trabajo se estudiará la pertinencia del mismo, en línea con los objetivos y desarrollos de la Escuela de Administración de la Universidad del Rosario. Puntualmente en temas de Perdurabilidad direccionados a la línea de Gerencia. Donde el entendimiento de la deuda como parte del funcionamiento actual y como variable determinante para el comportamiento futuro de las organizaciones tiene especial importancia. Una vez se clarifica la relación entre el presente trabajo y la Universidad, se desarrollan diferentes conceptos y teorías financieras que han permitido conocer y estudiar de manera más específica el mercado, con el objetivo de reducir los riesgos de las inversiones realizadas. Éste análisis se desarrolla en dos partes: (i) modelos de tiempo discreto y (ii) modelos de tiempo continúo. Una vez se tiene mayor claridad sobre los modelos estudiados hasta el momento se realiza el respectivo análisis de los datos mediante modelos de caos y análisis recurrente los cuales nos permiten entender que las acciones se comportan de manera caótica pero que establecen ciertas relaciones entre los precios actuales y los históricos, desarrollando comportamientos definidos entre los precios, las cantidades, el entorno macroeconómico y la organización. De otra parte, se realiza una descripción del mercado de petróleo en Colombia y se estudia a Ecopetrol como empresa y eje principal del mercado descrito en el país. La compañía Ecopetrol es representativa debido a que es uno de los mayores aportantes fiscales del país, pues sus ingresos se desprenden de bienes que se encuentran en el subsuelo por lo que la renta petrolera incluye impuestos a la producción transformación y consumo (Ecopetrol, 2003). Por último, se presentan los resultados del trabajo, así como el análisis que da lugar para presentar ciertas recomendaciones a partir de lo observado.

Relationship between åström control and the kalman linear regulator — Caines revisited

The relationship between minimum variance and minimum expected quadratic loss feedback controllers for linear univariate discrete-time stochastic systems is reviewed by taking the approach used by Caines. It is shown how the two methods can be regarded as providing identical control actions as long as a noise-free measurement state-space model is employed.

Optimal observers for ARMA models

A polynomial-based ARMA model, when posed in a state-space framework can be regarded in many different ways. In this paper two particular state-space forms of the ARMA model are considered, and although both are canonical in structure they differ in respect of the mode in which disturbances are fed into the state and output equations. For both forms a solution is found to the optimal discrete-time observer problem and algebraic connections between the two optimal observers are shown. The purpose of the paper is to highlight the fact that the optimal observer obtained from the first state-space form, commonly known as the innovations form, is not that employed in an optimal controller, in the minimum-output variance sense, whereas the optimal observer obtained from the second form is. Hence the second form is a much more appropriate state-space description to use for controller design, particularly when employed in self-tuning control schemes.

Adaptive deadbeat control of stochastic systems

This paper considers the use of a discrete-time deadbeat control action on systems affected by noise. Variations on the standard controller form are discussed and comparisons are made with controllers in which noise rejection is a higher priority objective. Both load and random disturbances are considered in the system description, although the aim of the deadbeat design remains as a tailoring of reference input variations. Finally, the use of such a deadbeat action within a self-tuning control framework is shown to satisfy, under certain conditions, the self-tuning property, generally though only when an extended form of least-squares estimation is incorporated.

Auto-weighted minimum-variance self-tuning controller

A self-tuning controller which automatically assigns weightings to control and set-point following is introduced. This discrete-time single-input single-output controller is based on a generalized minimum-variance control strategy. The automatic on-line selection of weightings is very convenient, especially when the system parameters are unknown or slowly varying with respect to time, which is generally considered to be the type of systems for which self-tuning control is useful. This feature also enables the controller to overcome difficulties with non-minimum phase systems.

Weighted input predictive controller

A discrete-time algorithm is presented which is based on a predictive control scheme in the form of dynamic matrix control. A set of control inputs are calculated and made available at each time instant, the actual input applied being a weighted summation of the inputs within the set. The algorithm is directly applicable in a self-tuning format and is therefore suitable for slowly time-varying systems in a noisy environment.

Neural networks for linear control: an analysis

This paper considers the use of radial basis function and multi-layer perceptron networks for linear or linearizable, adaptive feedback control schemes in a discrete-time environment. A close look is taken at the model structure selected and the extent of the resulting parameterization. A comparison is made with standard, nonneural network algorithms, e.g. self-tuning control.

Application of a novel optimal control algorithm to a benchmark fed-batch fermentation process

A novel algorithm for solving nonlinear discrete time optimal control problems with model-reality differences is presented. The technique uses Dynamic Integrated System Optimisation and Parameter Estimation (DISOPE) which has been designed to achieve the correct optimal solution in spite of deficiencies in the mathematical model employed in the optimisation procedure. A method based on Broyden's ideas is used for approximating some derivative trajectories required. Ways for handling con straints on both manipulated and state variables are described. Further, a method for coping with batch-to- batch dynamic variations in the process, which are common in practice, is introduced. It is shown that the iterative procedure associated with the algorithm naturally suits applications to batch processes. The algorithm is success fully applied to a benchmark problem consisting of the input profile optimisation of a fed-batch fermentation process.

Model predictive control using dynamic integrated system optimisation and parameter estimation (DISOPE)

DISOPE is a technique for solving optimal control problems where there are differences in structure and parameter values between reality and the model employed in the computations. The model reality differences can also allow for deliberate simplification of model characteristics and performance indices in order to facilitate the solution of the optimal control problem. The technique was developed originally in continuous time and later extended to discrete time. The main property of the procedure is that by iterating on appropriately modified model based problems the correct optimal solution is achieved in spite of the model-reality differences. Algorithms have been developed in both continuous and discrete time for a general nonlinear optimal control problem with terminal weighting, bounded controls and terminal constraints. The aim of this paper is to show how the DISOPE technique can aid receding horizon optimal control computation in nonlinear model predictive control.

New developments in batch process input profile optimisation

A novel algorithm for solving nonlinear discrete time optimal control problems with model-reality differences is presented. The technique uses dynamic integrated system optimisation and parameter estimation (DISOPE) which achieves the correct optimal solution in spite of deficiencies in the mathematical model employed in the optimisation procedure. A new method for approximating some Jacobian trajectories required by the algorithm is introduced. It is shown that the iterative procedure associated with the algorithm naturally suits applications to batch chemical processes.