Investigating the performance of MIMO systems from an electromagnetic perspective

Multiple input multiple output (MIMO) wireless systems use multiple element antennas (MEAs) tit the transmitter (TX) and the receiver (RX) in order to offer improved information rates (capacity) over conventional single antenna systems in rich scattering environments. In this paper, an example of a simple MIMO system is considered in which both antennas and scattering objects is are formed by wire dipoles. Such it system can be analyzed in the strict electromagnetic (EM) sense and its capacity can be determined for varying array size, interelement spacing, and distributions of scatterers. The EM model of this MIMO system can be used to assess the validity of single- or double-bounce scattering models for mixed line of sight (LOS) and non-line of sight (NLOS) signal-propagation conditions. (c) 2006 Wiley Periodicals, Inc.

Understanding and analyzing the performance of MIMO systems from the microwave perspective

Multiple input multiple output (MIMO) wireless systems use multiple element antennas at the transmitter and receiver to offer improved capacity over conventional single antenna systems in a rich scattering environment. In this paper, the microwave perspective of operation of MIMO system is given. Following the new interpretation of operation, an electromagnetic model is introduced to assess the MIMO system transmission capacity. The proposed model is shown to provide good agreement with reported results in the literature.

Finitely coordinated models for low-temperature phases of amorphous systems

We introduce models of heterogeneous systems with finite connectivity defined on random graphs to capture finite-coordination effects on the low-temperature behaviour of finite-dimensional systems. Our models use a description in terms of small deviations of particle coordinates from a set of reference positions, particularly appropriate for the description of low-temperature phenomena. A Born-von Karman-type expansion with random coefficients is used to model effects of frozen heterogeneities. The key quantity appearing in the theoretical description is a full distribution of effective single-site potentials which needs to be determined self-consistently. If microscopic interactions are harmonic, the effective single-site potentials turn out to be harmonic as well, and the distribution of these single-site potentials is equivalent to a distribution of localization lengths used earlier in the description of chemical gels. For structural glasses characterized by frustration and anharmonicities in the microscopic interactions, the distribution of single-site potentials involves anharmonicities of all orders, and both single-well and double-well potentials are observed, the latter with a broad spectrum of barrier heights. The appearance of glassy phases at low temperatures is marked by the appearance of asymmetries in the distribution of single-site potentials, as previously observed for fully connected systems. Double-well potentials with a broad spectrum of barrier heights and asymmetries would give rise to the well-known universal glassy low-temperature anomalies when quantum effects are taken into account. © 2007 IOP Publishing Ltd.

Identification of nonlinear systems by correlation using pseudorandom signals

This thesis is concerned with the measurement of the characteristics of nonlinear systems by crosscorrelation, using pseudorandom input signals based on m sequences. The systems are characterised by Volterra series, and analytical expressions relating the rth order Volterra kernel to r-dimensional crosscorrelation measurements are derived. It is shown that the two-dimensional crosscorrelation measurements are related to the corresponding second order kernel values by a set of equations which may be structured into a number of independent subsets. The m sequence properties determine how the maximum order of the subsets for off-diagonal values is related to the upper bound of the arguments for nonzero kernel values. The upper bound of the arguments is used as a performance index, and the performance of antisymmetric pseudorandom binary, ternary and quinary signals is investigated. The performance indices obtained above are small in relation to the periods of the corresponding signals. To achieve higher performance with ternary signals, a method is proposed for combining the estimates of the second order kernel values so that the effects of some of the undesirable nonzero values in the fourth order autocorrelation function of the input signal are removed. The identification of the dynamics of two-input, single-output systems with multiplicative nonlinearity is investigated. It is shown that the characteristics of such a system may be determined by crosscorrelation experiments using phase-shifted versions of a common signal as inputs. The effects of nonlinearities on the estimates of system weighting functions obtained by crosscorrelation are also investigated. Results obtained by correlation testing of an industrial process are presented, and the differences between theoretical and experimental results discussed for this case;

Formulation of multiparticulate systems as lyophilised orally disintegrating tablets

The current study aimed to exploit the electrostatic associative interaction between carrageenan and gelatin to optimise a formulation of lyophilised orally disintegrating tablets (ODTs) suitable for multiparticulate delivery. A central composite face centred (CCF) design was applied to study the influence of formulation variables (gelatin, carrageenan and alanine concentrations) on the crucial responses of the formulation (disintegration time, hardness, viscosity and pH). The disintegration time and viscosity were controlled by the associative interaction between gelatin and carrageenan upon hydration which forms a strong complex that increases the viscosity of the stock solution and forms tablet with higher resistant to disintegration in aqueous medium. Therefore, the levels of carrageenan, gelatin and their interaction in the formulation were the significant factors. In terms of hardness, increasing gelatin and alanine concentration was the most effective way to improve tablet hardness. Accordingly, optimum concentrations of these excipients were needed to find the best balance that fulfilled all formulation requirements. The revised model showed high degree of predictability and optimisation reliability and therefore was successful in developing an ODT formulation with optimised properties that were able deliver enteric coated multiparticulates of omeprazole without compromising their functionality.

Drying processess in the United Kingdom:assessment of industrial energy utilisation and efficiency of drying systems and the modelling of drying characters using neural networks (BL)

Drying is an important unit operation in process industry. Results have suggested that the energy used for drying has increased from 12% in 1978 to 18% of the total energy used in 1990. A literature survey of previous studies regarding overall drying energy consumption has demonstrated that there is little continuity of methods and energy trends could not be established. In the ceramics, timber and paper industrial sectors specific energy consumption and energy trends have been investigated by auditing drying equipment. Ceramic products examined have included tableware, tiles, sanitaryware, electrical ceramics, plasterboard, refractories, bricks and abrasives. Data from industry has shown that drying energy has not varied significantly in the ceramics sector over the last decade, representing about 31% of the total energy consumed. Information from the timber industry has established that radical changes have occurred over the last 20 years, both in terms of equipment and energy utilisation. The energy efficiency of hardwood drying has improved by 15% since the 1970s, although no significant savings have been realised for softwood. A survey estimating the energy efficiency and operating characteristics of 192 paper dryer sections has been conducted. Drying energy was found to increase to nearly 60% of the total energy used in the early 1980s, but has fallen over the last decade, representing 23% of the total in 1993. These results have demonstrated that effective energy saving measures, such as improved pressing and heat recovery, have been successfully implemented since the 1970s. Artificial neural networks have successfully been applied to model process characteristics of microwave and convective drying of paper coated gypsum cove. Parameters modelled have included product moisture loss, core gypsum temperature and quality factors relating to paper burning and bubbling defects. Evaluation of thermal and dielectric properties have highlighted gypsum's heat sensitive characteristics in convective and electromagnetic regimes. Modelling experimental data has shown that the networks were capable of simulating drying process characteristics to a high degree of accuracy. Product weight and temperature were predicted to within 0.5% and 5C of the target data respectively. Furthermore, it was demonstrated that the underlying properties of the data could be predicted through a high level of input noise.

Design and implementation of production systems for high variety electronics assembly

Information technology companies are having to broaden their overall strategic view in deference to the premise that it is better to be market-driven than technology-led. Cost and technical performance are no longer the only considerations, as quality and service now demand equal recognition. The production of a high volume single item has given way to that of low volume multiple items, which in turn requires some modification of production systems and brings flexible manufacturing, Just-in-Time production and total quality control into sharper focus for the achievement of corporate objectives.

Bridging large and small scales of water models using hybrid Molecular Dynamics/Fluctuating Hydrodynamics framework

This thesis presents a two-dimensional water model investigation and development of a multiscale method for the modelling of large systems, such as virus in water or peptide immersed in the solvent. We have implemented a two-dimensional ‘Mercedes Benz’ (MB) or BN2D water model using Molecular Dynamics. We have studied its dynamical and structural properties dependence on the model’s parameters. For the first time we derived formulas to calculate thermodynamic properties of the MB model in the microcanonical (NVE) ensemble. We also derived equations of motion in the isothermal–isobaric (NPT) ensemble. We have analysed the rotational degree of freedom of the model in both ensembles. We have developed and implemented a self-consistent multiscale method, which is able to communicate micro- and macro- scales. This multiscale method assumes, that matter consists of the two phases. One phase is related to micro- and the other to macroscale. We simulate the macro scale using Landau Lifshitz-Fluctuating Hydrodynamics, while we describe the microscale using Molecular Dynamics. We have demonstrated that the communication between the disparate scales is possible without introduction of fictitious interface or approximations which reduce the accuracy of the information exchange between the scales. We have investigated control parameters, which were introduced to control the contribution of each phases to the matter behaviour. We have shown, that microscales inherit dynamical properties of the macroscales and vice versa, depending on the concentration of each phase. We have shown, that Radial Distribution Function is not altered and velocity autocorrelation functions are gradually transformed, from Molecular Dynamics to Fluctuating Hydrodynamics description, when phase balance is changed. In this work we test our multiscale method for the liquid argon, BN2D and SPC/E water models. For the SPC/E water model we investigate microscale fluctuations which are computed using advanced mapping technique of the small scales to the large scales, which was developed by Voulgarakisand et. al.

Study of Queuing Systems with a Generalized Departure Process

This work was supported by the Bulgarian National Science Fund under grant BY-TH-105/2005.

General Aspects of Constructing an Autonomous Adaptive Agent

There are a great deal of approaches in artificial intelligence, some of them also coming from biology and neirophysiology. In this paper we are making a review, discussing many of them, and arranging our discussion around the autonomous agent research. We highlight three aspect in our classification: type of abstraction applied for representing agent knowledge, the implementation of hypothesis processing mechanism, allowed degree of freedom in behaviour and self-organizing. Using this classification many approaches in artificial intelligence are evaluated. Then we summarize all discussed ideas and propose a series of general principles for building an autonomous adaptive agent.

Analytical approximations to predict performance measures of manufacturing systems with job failures and parallel processing

Parallel processing is prevalent in many manufacturing and service systems. Many manufactured products are built and assembled from several components fabricated in parallel lines. An example of this manufacturing system configuration is observed at a manufacturing facility equipped to assemble and test web servers. Characteristics of a typical web server assembly line are: multiple products, job circulation, and paralleling processing. The primary objective of this research was to develop analytical approximations to predict performance measures of manufacturing systems with job failures and parallel processing. The analytical formulations extend previous queueing models used in assembly manufacturing systems in that they can handle serial and different configurations of paralleling processing with multiple product classes, and job circulation due to random part failures. In addition, appropriate correction terms via regression analysis were added to the approximations in order to minimize the gap in the error between the analytical approximation and the simulation models. Markovian and general type manufacturing systems, with multiple product classes, job circulation due to failures, and fork and join systems to model parallel processing were studied. In the Markovian and general case, the approximations without correction terms performed quite well for one and two product problem instances. However, it was observed that the flow time error increased as the number of products and net traffic intensity increased. Therefore, correction terms for single and fork-join stations were developed via regression analysis to deal with more than two products. The numerical comparisons showed that the approximations perform remarkably well when the corrections factors were used in the approximations. In general, the average flow time error was reduced from 38.19% to 5.59% in the Markovian case, and from 26.39% to 7.23% in the general case. All the equations stated in the analytical formulations were implemented as a set of Matlab scripts. By using this set, operations managers of web server assembly lines, manufacturing or other service systems with similar characteristics can estimate different system performance measures, and make judicious decisions - especially setting delivery due dates, capacity planning, and bottleneck mitigation, among others.

Vaclav Havel's Legacy of Freedom

Vaclav Havel changed history as an advocate of freedom and universal human rights. A playwright, essayist, poet, dissident, and politician, Havel became a symbol of the civic opposition to the communist government in Czechoslovakia. After the Prague “Velvet Revolution” that toppled the communist regime, Havel became president of Czechoslovakia, and later the first president of the Czech Republic. Ten years ago, on September 21, 2002, President Vaclav Havel came to FIU and delivered memorable remarks about freedom and in support of a peaceful transition to democracy in Cuba. Madeleine K. Albright is Chair of Albright Stonebridge Group, a global strategy firm, and Chair of Albright Capital Management LLC, an investment advisory firm focused on emerging markets. She was the 64th Secretary of State of the United States. On May 29, 2012, Dr. Albright received the Presidential Medal of Freedom, the nation’s highest civilian honor, from President Obama. She received an honorary degree from FIU in 1996. Dr. Albright is a Professor in the Practice of Diplomacy at the Georgetown University School of Foreign Service. The panel discussion includes: Thomas Dine, President of the American Friends of the Czech Republic The Honorable Petr Gandalovic, Ambassador of the Czech Republic to the U.S. Carl Gershman, President of the National Endowment for Democracy Martin Palous, Director, Vaclav Havel Library, SIPA Senior Fellow Marifeli Perez-Stable, Interim Director, Latin American and Caribbean Center

Analytical Approximations to Predict Performance Measures of Manufacturing Systems with Job Failures and Parallel Processing

Parallel processing is prevalent in many manufacturing and service systems. Many manufactured products are built and assembled from several components fabricated in parallel lines. An example of this manufacturing system configuration is observed at a manufacturing facility equipped to assemble and test web servers. Characteristics of a typical web server assembly line are: multiple products, job circulation, and paralleling processing. The primary objective of this research was to develop analytical approximations to predict performance measures of manufacturing systems with job failures and parallel processing. The analytical formulations extend previous queueing models used in assembly manufacturing systems in that they can handle serial and different configurations of paralleling processing with multiple product classes, and job circulation due to random part failures. In addition, appropriate correction terms via regression analysis were added to the approximations in order to minimize the gap in the error between the analytical approximation and the simulation models. Markovian and general type manufacturing systems, with multiple product classes, job circulation due to failures, and fork and join systems to model parallel processing were studied. In the Markovian and general case, the approximations without correction terms performed quite well for one and two product problem instances. However, it was observed that the flow time error increased as the number of products and net traffic intensity increased. Therefore, correction terms for single and fork-join stations were developed via regression analysis to deal with more than two products. The numerical comparisons showed that the approximations perform remarkably well when the corrections factors were used in the approximations. In general, the average flow time error was reduced from 38.19% to 5.59% in the Markovian case, and from 26.39% to 7.23% in the general case. All the equations stated in the analytical formulations were implemented as a set of Matlab scripts. By using this set, operations managers of web server assembly lines, manufacturing or other service systems with similar characteristics can estimate different system performance measures, and make judicious decisions - especially setting delivery due dates, capacity planning, and bottleneck mitigation, among others.

Hegel’s Non-Metaphysical Idea of Freedom

the article explores the putatively non-metaphysical – non-voluntarist, and even non-causal – concept of freedom outlined in Hegel’s work and discusses its influential interpretation by robert Pippin as an ‘essentially practical’ concept. I argue that Hegel’s affirmation of freedom must be distinguished from that of Kant and Fichte, since it does not rely on a prior understanding of self-consciousness as an originally teleological relation and it has not the nature of a claim ‘from a practical point of view’.

Spatially integrated erbium-doped fiber amplifiers enabling space-division multiplexing

L’augmentation exponentielle de la demande de bande passante pour les communications laisse présager une saturation prochaine de la capacité des réseaux de télécommunications qui devrait se matérialiser au cours de la prochaine décennie. En effet, la théorie de l’information prédit que les effets non linéaires dans les fibres monomodes limite la capacité de transmission de celles-ci et peu de gain à ce niveau peut être espéré des techniques traditionnelles de multiplexage développées et utilisées jusqu’à présent dans les systèmes à haut débit. La dimension spatiale du canal optique est proposée comme un nouveau degré de liberté qui peut être utilisé pour augmenter le nombre de canaux de transmission et, par conséquent, résoudre cette menace de «crise de capacité». Ainsi, inspirée par les techniques micro-ondes, la technique émergente appelée multiplexage spatial (SDM) est une technologie prometteuse pour la création de réseaux optiques de prochaine génération. Pour réaliser le SDM dans les liens de fibres optiques, il faut réexaminer tous les dispositifs intégrés, les équipements et les sous-systèmes. Parmi ces éléments, l’amplificateur optique SDM est critique, en particulier pour les systèmes de transmission pour les longues distances. En raison des excellentes caractéristiques de l’amplificateur à fibre dopée à l’erbium (EDFA) utilisé dans les systèmes actuels de pointe, l’EDFA est à nouveau un candidat de choix pour la mise en œuvre des amplificateurs SDM pratiques. Toutefois, étant donné que le SDM introduit une variation spatiale du champ dans le plan transversal de la fibre, les amplificateurs à fibre dopée à l’erbium spatialement intégrés (SIEDFA) nécessitent une conception soignée. Dans cette thèse, nous examinons tout d’abord les progrès récents du SDM, en particulier les amplificateurs optiques SDM. Ensuite, nous identifions et discutons les principaux enjeux des SIEDFA qui exigent un examen scientifique. Suite à cela, la théorie des EDFA est brièvement présentée et une modélisation numérique pouvant être utilisée pour simuler les SIEDFA est proposée. Sur la base d’un outil de simulation fait maison, nous proposons une nouvelle conception des profils de dopage annulaire des fibres à quelques-modes dopées à l’erbium (ED-FMF) et nous évaluons numériquement la performance d’un amplificateur à un étage, avec fibre à dopage annulaire, à ainsi qu’un amplificateur à double étage pour les communications sur des fibres ne comportant que quelques modes. Par la suite, nous concevons des fibres dopées à l’erbium avec une gaine annulaire et multi-cœurs (ED-MCF). Nous avons évalué numériquement le recouvrement de la pompe avec les multiples cœurs de ces amplificateurs. En plus de la conception, nous fabriquons et caractérisons une fibre multi-cœurs à quelques modes dopées à l’erbium. Nous réalisons la première démonstration des amplificateurs à fibre optique spatialement intégrés incorporant de telles fibres dopées. Enfin, nous présentons les conclusions ainsi que les perspectives de cette recherche. La recherche et le développement des SIEDFA offriront d’énormes avantages non seulement pour les systèmes de transmission future SDM, mais aussi pour les systèmes de transmission monomode sur des fibres standards à un cœur car ils permettent de remplacer plusieurs amplificateurs par un amplificateur intégré.