Digital test signal generation: An accurate SNR calibration approach for the DSN

A new method of generating analog test signals with accurate signal to noise ratios (SNRs) is described. High accuracy will be obtained by simultaneous generation of digital noise and signal spectra at a given baseband or bandpass limited bandwidth. The digital synthesis will provide a test signal embedded in noise with the statistical properties of a stationary random process. Accuracy will only be dependent on test integration time with a limit imposed by the system quantization noise (expected to be 0.02 dB). Setability will be approximately 0.1 dB. The first digital SNR generator to provide baseband test signals is being built and will be available in early 1991

F-measure Maximization in Multi-Label Classification with Conditionally Independent Label Subsets

We discuss a method to improve the exact F-measure maximization algorithm called GFM, proposed in (Dembczynski et al. 2011) for multi-label classification, assuming the label set can be can partitioned into conditionally independent subsets given the input features. If the labels were all independent, the estimation of only $m$ parameters ($m$ denoting the number of labels) would suffice to derive Bayes-optimal predictions in $O(m^2)$ operations. In the general case, $m^2+1$ parameters are required by GFM, to solve the problem in $O(m^3)$ operations. In this work, we show that the number of parameters can be reduced further to $m^2/n$, in the best case, assuming the label set can be partitioned into $n$ conditionally independent subsets. As this label partition needs to be estimated from the data beforehand, we use first the procedure proposed in (Gasse et al. 2015) that finds such partition and then infer the required parameters locally in each label subset. The latter are aggregated and serve as input to GFM to form the Bayes-optimal prediction. We show on a synthetic experiment that the reduction in the number of parameters brings about significant benefits in terms of performance

Improvement of anterior and posterior segment ocular drug delivery: application in ocular cystinosis and age-related macular degeneration

In this doctoral thesis, hydrogel-based formulations containing cysteamine of great potential for the treatment of ocular cystinosis have been developed. The hydrogel based on hyaluronic acid polymer has been extensively characterised and its preparation has been translated to Hospital Pharmacy Departments. On the other hand, regarding the study of intravitreal injections in AMD, this thesis has demonstrated the usefulness of the PET methodology for the study of intravitreal pharmacokinetics in rats, which has been subsequently used for the evaluation of the ocular pharmacokinetics after intravitreal administration of aflibercept and bevacizumab. Moreover, intravitreal chitosan-based implants containing aflibercept which permit its extended delivery have been developed