The design of optical systems (OS) is a sequential process including stages of the analysis of a technical specification, structural synthesis, parametric optimization etc. Currently there exists a lot of computer-aided design systems (CAD) that can effectively solve the problem of an optical scheme optimization (also known as parametric synthesis), calculating the exact parameters of an optica...

Amines with remote stereocentres (stereocentres that are three or more bonds away from the C-N bond) are important structural elements in many pharmaceutical agents and natural products. However, previously reported methods to prepare these compounds in an enantioselective manner are indirect and require multistep synthesis. Here, we report a copper-hydride-catalysed, enantioselective synthesis...

Sequential optimization techniques fall in two broad categories: state-based and structure-based [4]. Structurebased techniques optimize a circuit netlist by interleaving retiming and combinational synthesis in different ways to improve design metrics such as delay, area, and power. Examples of such optimizations include among others: peripheral retiming [7], architectural retiming [6], and ite...

Allowing many processors to work in parallel offers no significant speedup when computing the rank of a finitely generated free group. Stallings’ folding process, an algorithm for simplifying a directed edgelabeled graph, when applied to those graphs that represent finitely generated free groups, provides a graph-theoretic method for computing the rank of that group. Does adding more processors...

Verification and Synthesis of Clock-Gated Circuits by Yu-Yun Dai Doctor of Philosophy in Engineering-Electrical Engineering and Computer Sciences University of California, Berkeley Professor Robert K. Brayton, Chair As system complexity and transistor density increase, the power consumed by digital integrated circuits has become a critical constraint for VLSI design and manufacturing. To reduce...

We introduce a new sequential algorithm for making robust predictions in the presence of changepoints. Unlike previous approaches, which focus on the problem of detecting and locating changepoints, our algorithm focuses on the problem of making predictions even when such changes might be present. We introduce nonstationary covariance functions to be used in Gaussian process prediction that mode...