Effective Reconfigurable Antenna Designs to Enhance Performance and Enable Wireless Powering

With the increase in traffic on the internet, there is a greater demand for wireless mobile and ubiquitous applications. These applications need antennas that are not only broadband, but can also work in different frequency spectrums. Even though there is a greater demand for such applications, it is still imperative to conserve power. Thus, there is a need to design multi-broadband antennas that do not use a lot of power. Reconfigurable antennas can work in different frequency spectrums as well as conserve power. The current designs of reconfigurable antennas work only in one band. There is a need to design reconfigurable antennas that work in different frequency spectrums. In this current era of high power consumption there is also a greater demand for wireless powering. This dissertation explores ideal designs of reconfigurable antennas that can improve performance and enable wireless powering. This dissertation also presents lab results of the multi-broadband reconfigurable antenna that was created. A detailed mathematical analyses, as well as extensive simulation results are also presented. The novel reconfigurable antenna designs can be extended to Multiple Input Multiple Output (MIMO) environments and military applications.

A Methodological Framework for Modeling Pavement Maintenance Costs for Projects with Performance-based Contracts

Performance-based maintenance contracts differ significantly from material and method-based contracts that have been traditionally used to maintain roads. Road agencies around the world have moved towards a performance-based contract approach because it offers several advantages like cost saving, better budgeting certainty, better customer satisfaction with better road services and conditions. Payments for the maintenance of road are explicitly linked to the contractor successfully meeting certain clearly defined minimum performance indicators in these contracts. Quantitative evaluation of the cost of performance-based contracts has several difficulties due to the complexity of the pavement deterioration process. Based on a probabilistic analysis of failures of achieving multiple performance criteria over the length of the contract period, an effort has been made to develop a model that is capable of estimating the cost of these performance-based contracts. One of the essential functions of such model is to predict performance of the pavement as accurately as possible. Prediction of future degradation of pavement is done using Markov Chain Process, which requires estimating transition probabilities from previous deterioration rate for similar pavements. Transition probabilities were derived using historical pavement condition rating data, both for predicting pavement deterioration when there is no maintenance, and for predicting pavement improvement when maintenance activities are performed. A methodological framework has been developed to estimate the cost of maintaining road based on multiple performance criteria such as crack, rut and, roughness. The application of the developed model has been demonstrated via a real case study of Miami Dade Expressways (MDX) using pavement condition rating data from Florida Department of Transportation (FDOT) for a typical performance-based asphalt pavement maintenance contract. Results indicated that the pavement performance model developed could predict the pavement deterioration quite accurately. Sensitivity analysis performed shows that the model is very responsive to even slight changes in pavement deterioration rate and performance constraints. It is expected that the use of this model will assist the highway agencies and contractors in arriving at a fair contract value for executing long term performance-based pavement maintenance works.

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.

The effects of semantic and syntactic instruction on user performance and satisfaction in search user interface design

The design of interfaces to facilitate user search has become critical for search engines, ecommercesites, and intranets. This study investigated the use of targeted instructional hints to improve search by measuring the quantitative effects of users' performance and satisfaction. The effects of syntactic, semantic and exemplar search hints on user behavior were evaluated in an empirical investigation using naturalistic scenarios. Combining the three search hint components, each with two levels of intensity, in a factorial design generated eight search engine interfaces. Eighty participants participated in the study and each completed six realistic search tasks. Results revealed that the inclusion of search hints improved user effectiveness, efficiency and confidence when using the search interfaces, but with complex interactions that require specific guidelines for search interface designers. These design guidelines will allow search designers to create more effective interfaces for a variety of searchapplications.

Analysis and comparison of network performance with different network parameters

The purpose of this study was to analyze the network performance by observing the effect of varying network size and data link rate on one of the most commonly found network configurations. Computer networks have been growing explosively. Networking is used in every aspect of business, including advertising, production, shipping, planning, billing, and accounting. Communication takes place through networks that form the basis of transfer of information. The number and type of components may vary from network to network depending on several factors such as requirement and actual physical placement of the networks. There is no fixed size of the networks and they can be very small consisting of say five to six nodes or very large consisting of over two thousand nodes. The varying network sizes make it very important to study the network performance so as to be able to predict the functioning and the suitability of the network. The findings demonstrated that the network performance parameters such as global delay, load, router processor utilization, router processor delay, etc. are affected. The findings demonstrated that the network performance parameters such as global delay, load, router processor utilization, router processor delay, etc. are affected significantly due to the increase in the size of the network and that there exists a correlation between the various parameters and the size of the network. These variations are not only dependent on the magnitude of the change in the actual physical area of the network but also on the data link rate used to connect the various components of the network.

Improving performance of a permeable reactive barrier in the degradation of trichloroethylene using ultrasound

The impact of ultrasound on improving the performance of a granular iron Permeable Reactive Barrier (PRB) in the degradation of Trichloroethylene (TCE) was evaluated. Two treatment columns made of clear Plexiglas with a height of 1ft and a diameter of 2 inches and filled with granular iron were used. One was fitted with 25Khz ultrasound probes. A solution of TCE was run through at constant flow rate. Samples obtained from the column at different residence times before and after sonication were analyzed for concentrations of TCE and used to generate concentration profiles to obtain rate constants, which were compared. An improvement of 23.4% in the reaction rate of TCE degradation was observed after sonication of the iron media suggesting that ultrasound may contribute to improving the performance of PRBs in the degradation of TCE in contaminated groundwater.

An automated approach for performance deviation analysis of evolving software systems

A manutenção e evolução de sistemas de software tornou-se uma tarefa bastante crítica ao longo dos últimos anos devido à diversidade e alta demanda de funcionalidades, dispositivos e usuários. Entender e analisar como novas mudanças impactam os atributos de qualidade da arquitetura de tais sistemas é um pré-requisito essencial para evitar a deterioração de sua qualidade durante sua evolução. Esta tese propõe uma abordagem automatizada para a análise de variação do atributo de qualidade de desempenho em termos de tempo de execução (tempo de resposta). Ela é implementada por um framework que adota técnicas de análise dinâmica e mineração de repositório de software para fornecer uma forma automatizada de revelar fontes potenciais – commits e issues – de variação de desempenho em cenários durante a evolução de sistemas de software. A abordagem define quatro fases: (i) preparação – escolher os cenários e preparar os releases alvos; (ii) análise dinâmica – determinar o desempenho de cenários e métodos calculando seus tempos de execução; (iii) análise de variação – processar e comparar os resultados da análise dinâmica para releases diferentes; e (iv) mineração de repositório – identificar issues e commits associados com a variação de desempenho detectada. Estudos empíricos foram realizados para avaliar a abordagem de diferentes perspectivas. Um estudo exploratório analisou a viabilidade de se aplicar a abordagem em sistemas de diferentes domínios para identificar automaticamente elementos de código fonte com variação de desempenho e as mudanças que afetaram tais elementos durante uma evolução. Esse estudo analisou três sistemas: (i) SIGAA – um sistema web para gerência acadêmica; (ii) ArgoUML – uma ferramenta de modelagem UML; e (iii) Netty – um framework para aplicações de rede. Outro estudo realizou uma análise evolucionária ao aplicar a abordagem em múltiplos releases do Netty, e dos frameworks web Wicket e Jetty. Nesse estudo foram analisados 21 releases (sete de cada sistema), totalizando 57 cenários. Em resumo, foram encontrados 14 cenários com variação significante de desempenho para Netty, 13 para Wicket e 9 para Jetty. Adicionalmente, foi obtido feedback de oito desenvolvedores desses sistemas através de um formulário online. Finalmente, no último estudo, um modelo de regressão para desempenho foi desenvolvido visando indicar propriedades de commits que são mais prováveis a causar degradação de desempenho. No geral, 997 commits foram minerados, sendo 103 recuperados de elementos de código fonte degradados e 19 de otimizados, enquanto 875 não tiveram impacto no tempo de execução. O número de dias antes de disponibilizar o release e o dia da semana se mostraram como as variáveis mais relevantes dos commits que degradam desempenho no nosso modelo. A área de característica de operação do receptor (ROC – Receiver Operating Characteristic) do modelo de regressão é 60%, o que significa que usar o modelo para decidir se um commit causará degradação ou não é 10% melhor do que uma decisão aleatória.

An automated approach for performance deviation analysis of evolving software systems

A manutenção e evolução de sistemas de software tornou-se uma tarefa bastante crítica ao longo dos últimos anos devido à diversidade e alta demanda de funcionalidades, dispositivos e usuários. Entender e analisar como novas mudanças impactam os atributos de qualidade da arquitetura de tais sistemas é um pré-requisito essencial para evitar a deterioração de sua qualidade durante sua evolução. Esta tese propõe uma abordagem automatizada para a análise de variação do atributo de qualidade de desempenho em termos de tempo de execução (tempo de resposta). Ela é implementada por um framework que adota técnicas de análise dinâmica e mineração de repositório de software para fornecer uma forma automatizada de revelar fontes potenciais – commits e issues – de variação de desempenho em cenários durante a evolução de sistemas de software. A abordagem define quatro fases: (i) preparação – escolher os cenários e preparar os releases alvos; (ii) análise dinâmica – determinar o desempenho de cenários e métodos calculando seus tempos de execução; (iii) análise de variação – processar e comparar os resultados da análise dinâmica para releases diferentes; e (iv) mineração de repositório – identificar issues e commits associados com a variação de desempenho detectada. Estudos empíricos foram realizados para avaliar a abordagem de diferentes perspectivas. Um estudo exploratório analisou a viabilidade de se aplicar a abordagem em sistemas de diferentes domínios para identificar automaticamente elementos de código fonte com variação de desempenho e as mudanças que afetaram tais elementos durante uma evolução. Esse estudo analisou três sistemas: (i) SIGAA – um sistema web para gerência acadêmica; (ii) ArgoUML – uma ferramenta de modelagem UML; e (iii) Netty – um framework para aplicações de rede. Outro estudo realizou uma análise evolucionária ao aplicar a abordagem em múltiplos releases do Netty, e dos frameworks web Wicket e Jetty. Nesse estudo foram analisados 21 releases (sete de cada sistema), totalizando 57 cenários. Em resumo, foram encontrados 14 cenários com variação significante de desempenho para Netty, 13 para Wicket e 9 para Jetty. Adicionalmente, foi obtido feedback de oito desenvolvedores desses sistemas através de um formulário online. Finalmente, no último estudo, um modelo de regressão para desempenho foi desenvolvido visando indicar propriedades de commits que são mais prováveis a causar degradação de desempenho. No geral, 997 commits foram minerados, sendo 103 recuperados de elementos de código fonte degradados e 19 de otimizados, enquanto 875 não tiveram impacto no tempo de execução. O número de dias antes de disponibilizar o release e o dia da semana se mostraram como as variáveis mais relevantes dos commits que degradam desempenho no nosso modelo. A área de característica de operação do receptor (ROC – Receiver Operating Characteristic) do modelo de regressão é 60%, o que significa que usar o modelo para decidir se um commit causará degradação ou não é 10% melhor do que uma decisão aleatória.

Investigation on performance characteristics of dense graded hot mix asphalt with RAP and crumb rubber

The objective of this study was to fundamentally characterize the laboratory performance of traditional hot mix asphalt (HMA) mixtures incorporating high RAP content and waste tire crumb rubber through their fundamental engineering properties. The nominal maximum aggregates size was chosen for this research was 12mm (considering the limitation of aggregate size for surface layer) and both coarse and fine aggregates are commonly used in Italy that were examined and analyzed in this study. On the other hand, the RAP plays an important role in reducing production costs and enhancing the environmentally sustainable pavements instead of using virgin materials in HMA. Particularly, this study has aimed to use 30% of RAP content (25% fine aggregate RAP and 5% coarse aggregate RAP) and 1% of CR additives by the total weight of aggregates for mix design. The mixture of aggregates, RAP and CR were blended with different amount of unmodified binder through dry processes. Generally, the main purposes of this study were investigating on capability of using RAP and CR in dense graded HMA and comparing the performance of rejuvenator in RAP with CR. In addition, based on the engineering analyses during the study, we were able compare the fundamental Indirect Tensile Strength (ITS) value of dense graded HMA and also mechanical characteristics in terms of Indirect Tensile Stiffness Modulus (ITSM). In order to get an extended comparable data, four groups of different mixtures such as conventional mixture with only virgin aggregates (DV), mixture with RAP (DR), mixture with RAP and rejuvenator (DRR), and mixture with RAP, rejuvenator, CR (DRRCr) were investigated in this research experimentally. Finally, the results of those tests indicated that the mixtures with RAP and CR had the high stiffness and less thermal sensitivity, while the mixture with virgin aggregates only had very low values in comparison.

Practical engineering of hard spin-glass instances

Recent technological developments in the field of experimental quantum annealing have made prototypical annealing optimizers with hundreds of qubits commercially available. The experimental demonstration of a quantum speedup for optimization problems has since then become a coveted, albeit elusive goal. Recent studies have shown that the so far inconclusive results, regarding a quantum enhancement, may have been partly due to the benchmark problems used being unsuitable. In particular, these problems had inherently too simple a structure, allowing for both traditional resources and quantum annealers to solve them with no special efforts. The need therefore has arisen for the generation of harder benchmarks which would hopefully possess the discriminative power to separate classical scaling of performance with size from quantum. We introduce here a practical technique for the engineering of extremely hard spin-glass Ising-type problem instances that does not require "cherry picking" from large ensembles of randomly generated instances. We accomplish this by treating the generation of hard optimization problems itself as an optimization problem, for which we offer a heuristic algorithm that solves it. We demonstrate the genuine thermal hardness of our generated instances by examining them thermodynamically and analyzing their energy landscapes, as well as by testing the performance of various state-of-the-art algorithms on them. We argue that a proper characterization of the generated instances offers a practical, efficient way to properly benchmark experimental quantum annealers, as well as any other optimization algorithm.

Lessons from monitoring the performance of highway bridges

Peer reviewed

Probing the Role of Thermally Reduced Graphene Oxide in Enhancing Performance of TiO2 in Photocatalytic Phenol Removal from Aqueous Environments

We thank the INSA-RSE bilateral exchange programme for financial assistance (PD) and the Petroleum Technology Development Fund (PTDF, Nigeria) for the award of PhD scholarship, as well as Abubakar Tafawa Balewa University, Bauchi-Nigeria for the granted fellowship (H.A).

Lessons from monitoring the performance of highway bridges

Peer reviewed

Probing the Role of Thermally Reduced Graphene Oxide in Enhancing Performance of TiO2 in Photocatalytic Phenol Removal from Aqueous Environments

We thank the INSA-RSE bilateral exchange programme for financial assistance (PD) and the Petroleum Technology Development Fund (PTDF, Nigeria) for the award of PhD scholarship, as well as Abubakar Tafawa Balewa University, Bauchi-Nigeria for the granted fellowship (H.A).

Detection of bridge anomalous behavior and assessment of their impact on structural performance

Peer reviewed