THE EFFECT OF TALKER NATIVENESS ON THE PERCEPTION OF VOICING IN SYLLABLE-INITIAL PLOSIVES BY AMERICAN ENGLISH MONOLINGUALS

Ph.D

Context-Aware Generative Adversarial Privacy

Preserving the utility of published datasets while simultaneously providing provable privacy guarantees is a well-known challenge. On the one hand, context-free privacy solutions, such as differential privacy, provide strong privacy guarantees, but often lead to a significant reduction in utility. On the other hand, context-aware privacy solutions, such as information theoretic privacy, achieve an improved privacy-utility tradeoff, but assume that the data holder has access to dataset statistics. We circumvent these limitations by introducing a novel context-aware privacy framework called generative adversarial privacy (GAP). GAP leverages recent advancements in generative adversarial networks (GANs) to allow the data holder to learn privatization schemes from the dataset itself. Under GAP, learning the privacy mechanism is formulated as a constrained minimax game between two players: a privatizer that sanitizes the dataset in a way that limits the risk of inference attacks on the individuals' private variables, and an adversary that tries to infer the private variables from the sanitized dataset. To evaluate GAP's performance, we investigate two simple (yet canonical) statistical dataset models: (a) the binary data model, and (b) the binary Gaussian mixture model. For both models, we derive game-theoretically optimal minimax privacy mechanisms, and show that the privacy mechanisms learned from data (in a generative adversarial fashion) match the theoretically optimal ones. This demonstrates that our framework can be easily applied in practice, even in the absence of dataset statistics.Comment: Improved version of a paper accepted by Entropy Journal, Special Issue on Information Theory in Machine Learning and Data Scienc

An active interferometric method for extreme impedance on-wafer device measurements

Nano-scale devices and high-power transistors present extreme impedances, which are far removed from the 50-Ω reference impedance of conventional test equipment, resulting in a reduction in the measurement sensitivity as compared with impedances close to the reference impedance. This letter describes a novel method based on active interferometry to increase the measurement sensitivity of a vector network analyzer for measuring such extreme impedances, using only a single coupler. The theory of the method is explained with supporting simulation. An interferometry-based method is demonstrated for the first time with on-wafer measurements, resulting in an improved measurement sensitivity for extreme impedance device characterization of up to 9%

FOCUSING THE BALTIC AGRICULTURAL SECTOR TOWARDS THE NEW CONSUMER: ESTONIA'S CASE

This paper analyses some of the current problems emerging in the Baltic economies with special reference to Estonia and the agricultural sector. The prime objectives are to put forward suggestions for improving the agricultural investment, and to improve the marketing towards the modern international consumer. The major points covered are: 1.National changes following the break from USSR in 1991. 2.Re orientation towards the European Union (EU) and international markets. 3.Changes for long run growth in the Estonian agricultural sector.agricultural sector, Estonia