Compact dielectric-filled waveguide filters and diplexers

This paper presents electromagnetic simulations of dielectric-filled rectangular waveguide bandpass filter structures with microstrip to waveguide transitions as well as a diplexer based on such filters for modern wireless systems. The two bandpass filters have been designed and simulated at centre frequencies of 11.85 and 14.25 GHz, respectively. A significant size reduction is achieved through dielectric filling.

Compact high linearity switchable dual-mode microstrip bandpass filters

A compact highly linear microstrip dual-mode electronically switchable filter is presented. The key characteristics of the dual-mode switchable filter are investigated and described. A second order filter design procedure is outlined to facilitate the realisation of Butterworth and Chebyshev functions. The proposed filter was built and tested with NXP pin diode model BAP65-03. The measured and simulated results are in good agreement. The measured insertion loss in the ON state was 3.0 dB the isolation in the OFF state was 45 dB at the centre frequency. An evaluation of filter distortion is presented for digitally modulated 16 QAM and QPSK signals.

Compact filters using metal-dielectric inserts

A novel filter based on e-plane metal-dielectric insert in rectangular waveguide is proposed. Properties of the structure containing metallic septa, C- and I-shaped resonators placed in waveguide are investigated. Pseudo-elliptic cross-coupled filter with direct source-load coupling is designed, simulated and fabricated. Experimental results are presented to prove feasibility of the filter. Significant size reduction is achieved.

Ultra compact pseudo-elliptic inline waveguide bandpass filters using bypass coupling

This paper presents an ultra compact waveguide bandpass filter that exhibits a pseudo-elliptic response. The transmission zero created in the upper stopband to form a rapid roll off is produced through a bypass coupling with higher order modes. A 3rd order filter is designed at the centre frequency of 9.4 GHz with a 5.3% fractional bandwidth. The proposed structure's size is 38% smaller than one of a 3rd order E-plane extracted pole filter with comparable response. Additionally, this configuration allows larger span of different bandwidths. The filter has been fabricated and tested using E-plane waveguide technology, which has benefits of being inexpensive and having mass producible capabilities. Measurements of such a fabricated filter validate the simulated results.

Ultra compact inline E-plane waveguide extracted pole bandpass filters

This letter presents an ultra compact extracted pole E-plane filter. The proposed structure can achieve up to 65% size reduction in comparison with a standard extracted pole filter designed at 9.5 GHz centre frequency with a 3% fractional bandwidth. The filter has been fabricated and tested using E-plane waveguide technology. Measurements on a fabricated filter confirm the accuracy of the design method.

Compact tunable bandstop filters using defected microstrip structure for multi-standard wireless systems

A novel compact tunable bandstop filter using Defected Microstrip Structure (DMS) is presented in this paper. The structure utilizes a modified T shaped DMS which helps in miniaturization of the filter. To verify the concept, one such filter was simulated, designed, fabricated and tested. Measurements on a fabricated tunable filter confirm the accuracy of the design procedure. The tuning range of 20% is achieved, ranging from 2.26 GHz to 2.747 GHz. Tuning is achieved by using NXP BB179 varactor diode. A nonlinear distortion evaluation in a tunable filter was experimentally verified. Experimental verification shows the filter is highly linear.

Dynamic power- and failure-aware cloud resources allocation for Sets of independent tasks

Cloud computing is increasingly being adopted in different scenarios, like social networking, business applications, scientific experiments, etc. Relying in virtualization technology, the construction of these computing environments targets improvements in the infrastructure, such as power-efficiency and fulfillment of users’ SLA specifications. The methodology usually applied is packing all the virtual machines on the proper physical servers. However, failure occurrences in these networked computing systems can induce substantial negative impact on system performance, deviating the system from ours initial objectives. In this work, we propose adapted algorithms to dynamically map virtual machines to physical hosts, in order to improve cloud infrastructure power-efficiency, with low impact on users’ required performance. Our decision making algorithms leverage proactive fault-tolerance techniques to deal with systems failures, allied with virtual machine technology to share nodes resources in an accurately and controlled manner. The results indicate that our algorithms perform better targeting power-efficiency and SLA fulfillment, in face of cloud infrastructure failures.

Compact, frequency reconfigurable, printed monopole antenna

This paper proposes a possible implementation of a compact printed monopole antenna, useful to operate in UMTS and WLAN bands. In order to accomplish that, a miniaturization technique based on the application of chip inductors is used in conjunction with frequency reconfiguration capability. The chip inductors change the impedance response of the monopole, allowing to reduce the resonant frequency. In order to be able to operate the antenna in these two different frequencies, an antenna reconfiguration technique based on PIN diodes is applied. This procedure allows the change of the active form of the antenna leading to a shift in the resonant frequency. The prototype measurements show good agreement with the simulation results.

Weakly spectrally complete pair of matrices

Let and be matrices over an algebraically closed field. Let be elements of such that and . We give necessary and sufficient condition for the existence of matrices and similar to and, respectively, such that has eigenvalues.

Compact simulated countercurrent chromatography for downstream processing of (bio)pharmaceuticals

Dissertação para obtenção do Grau de Doutor em Engenharia Química e Bioquímica

Improving the Scalability of Reduct Determination in Rough Sets

Rough Set Data Analysis (RSDA) is a non-invasive data analysis approach that solely relies on the data to find patterns and decision rules. Despite its noninvasive approach and ability to generate human readable rules, classical RSDA has not been successfully used in commercial data mining and rule generating engines. The reason is its scalability. Classical RSDA slows down a great deal with the larger data sets and takes much longer times to generate the rules. This research is aimed to address the issue of scalability in rough sets by improving the performance of the attribute reduction step of the classical RSDA - which is the root cause of its slow performance. We propose to move the entire attribute reduction process into the database. We defined a new schema to store the initial data set. We then defined SOL queries on this new schema to find the attribute reducts correctly and faster than the traditional RSDA approach. We tested our technique on two typical data sets and compared our results with the traditional RSDA approach for attribute reduction. In the end we also highlighted some of the issues with our proposed approach which could lead to future research.

Ranking Sets of Objects

We provide a survey of the literature on ranking sets of objects. The interpretations of those set rankings include those employed in the theory of choice under complete uncertainty, rankings of opportunity sets, set rankings that appear in matching theory, and the structure of assembly preferences. The survey is prepared for the Handbook of Utility Theory, vol. 2, edited by Salvador Barberà, Peter Hammond, and Christian Seidl, to be published by Kluwer Academic Publishers. The chapter number is provisional.

Identification, Weak Instruments and Statistical Inference in Econometrics

We discuss statistical inference problems associated with identification and testability in econometrics, and we emphasize the common nature of the two issues. After reviewing the relevant statistical notions, we consider in turn inference in nonparametric models and recent developments on weakly identified models (or weak instruments). We point out that many hypotheses, for which test procedures are commonly proposed, are not testable at all, while some frequently used econometric methods are fundamentally inappropriate for the models considered. Such situations lead to ill-defined statistical problems and are often associated with a misguided use of asymptotic distributional results. Concerning nonparametric hypotheses, we discuss three basic problems for which such difficulties occur: (1) testing a mean (or a moment) under (too) weak distributional assumptions; (2) inference under heteroskedasticity of unknown form; (3) inference in dynamic models with an unlimited number of parameters. Concerning weakly identified models, we stress that valid inference should be based on proper pivotal functions —a condition not satisfied by standard Wald-type methods based on standard errors — and we discuss recent developments in this field, mainly from the viewpoint of building valid tests and confidence sets. The techniques discussed include alternative proposed statistics, bounds, projection, split-sampling, conditioning, Monte Carlo tests. The possibility of deriving a finite-sample distributional theory, robustness to the presence of weak instruments, and robustness to the specification of a model for endogenous explanatory variables are stressed as important criteria assessing alternative procedures.