Machine learning -- based diffractive imaging with subwavelength resolution

Far-field characterization of small objects is severely constrained by the diffraction limit. Existing tools achieving sub-diffraction resolution often utilize point-by-point image reconstruction via scanning or labelling. Here, we present a new imaging technique capable of fast and accurate characterization of two-dimensional structures with at least wavelength/25 resolution, based on a single far-field intensity measurement. Experimentally, we realized this technique resolving the smallest-available to us 180-nm-scale features with 532-nm laser light. A comprehensive analysis of machine learning algorithms was performed to gain insight into the learning process and to understand the flow of subwavelength information through the system. Image parameterization, suitable for diffractive configurations and highly tolerant to random noise was developed. The proposed technique can be applied to new characterization tools with high spatial resolution, fast data acquisition, and artificial intelligence, such as high-speed nanoscale metrology and quality control, and can be further developed to high-resolution spectroscop

Configurable 3D-integrated focal-plane sensor-processor array architecture

A mixed-signal Cellular Visual Microprocessor architecture with digital processors is described. An ASIC implementation is also demonstrated. The architecture is composed of a regular sensor readout circuit array, prepared for 3D face-to-face type integration, and one or several cascaded array of mainly identical (SIMD) processing elements. The individual array elements derived from the same general HDL description and could be of different in size, aspect ratio, and computing resources

An Open-Domain Dialog Act Taxonomy

This document defines the taxonomy of dialog acts that are necessary to encode domain-independent dialog moves in the context of a task-oriented, open-domain dialog. Such taxonomy is formulated to satisfy two complementary requirements: on the one hand, domain independence, i.e. the power to cover all the range of possible interactions in any type of conversation (particularly conversation oriented to the performance of tasks). On the other hand, the ability to instantiate a concrete set of tasks as defined by a specific knowledge base (such as an ontology of domain concepts and actions) and within a particular language. For the modeling of dialog acts, inspiration is taken from several well-known dialog annotation schemes, such as DAMSL (Core & Allen, 1997), TRAINS (Traum, 1996) and VERBMOBIL (Alexandersson et al., 1997)

Convergence of adaptive morphological filters in the context of Markov chains

A typical parameterized r-opening *r is a filter defined as a union of openings by a collection of compact, convex structuring elements, each of which is governed by a parameter vector r. It reduces to a single parameter r-opening filter by a set of structuring elements when r is a scalar sizing parameter. The parameter vector is adjusted by a set of adaptation rules according to whether the re construction Ar derived from r correctly or incorrectly passes the signal and noise grains sampled from the image. Applied to the signal-union-noise model, the optimization problem is to find the vector of r that minimizes the Mean-Absolute-Error between the filtered and ideal image processes. The adaptive r-opening filter fits into the framework of Markov processes, the adaptive parameter being the state of the process. For a single parameter r-opening filter, we proved that there exists a stationary distribution governing the parameter in the steady state and convergence is characterized in terms of the steady-state distribution. Key filter properties such as parameter mean, parameter variance, and expected error in the steady state are characterized via the stationary distribution. Steady-state behavior is compared to the optimal solution for the uniform model, for which it is possible to derive a closed-form solution for the optimal filter. We also developed the Markov adaptation system for multiparameter opening filters and provided numerical solutions to some special cases. For multiparameter r-opening filters, various adaptive models derived from various assumptions on the form of the filter have been studied. Although the state-probability increment equations can be derived from the appropriate Chapman-Kolmogorov equations, the closed-form representation of steady-state distributions is mathematically problematic due to the support geometry of the boundary states and their transitions. Therefore, numerical methods are employed to approximate for steady state probability distributions. The technique developed for conventional opening filters is also applied to bandpass opening filters. In present thesis study, the concept of signal and noise pass sets plays a central role throughout the adaptive filter analysis. The pass set reduces to the granulometric measure (or {&r}-measure) of the signal and noise grain. Optimization and adaptation are characterized in terms of the distribution of the granulometric measures for single parameter filters, or in terms of the multivariate distribution of the signal and noise pass sets. By introducing these concepts, this thesis study also provides some optimal opening filter error equations. It has been shown in the case of the uniform distribution of single sizing parameter that there is a strong agreement between the adaptive filter and optimal filter based on analytic error minimization. This agreement has been also demonstrated in various r-opening filters. Furthermore, the probabilistic interpretation has a close connection to traditional linear adaptive filter theory. The method has been applied to the classical grain separation (clutter removal) problem. *See content for correct numerical representation

Sensitivity of night cooling performance to room/system design: surrogate models based on CFD

Night cooling, especially in offices, attracts growing interest. Unfortunately, building designers face considerable problems with the case-specific convective heat transfer by night. The BES programs they use actually need extra input, from either costly experiments or CFD simulations. Alternatively, up-front research on how to engineer best a generic night cooled office – as in this work – can thrust the application of night cooling. A fully automated configuration of data sampling, geometry/grid generation, CFD solving and surrogate modelling, generates several surrogate models. These models relate the convective heat flow in a night cooled landscape office to the ventilation concept, mass distribution, geometry and driving force for convective heat transfer. The results indicate that cases with a thermally massive floor have the highest night cooling performance

To Review or Not to Review? Limited Strategic Thinking at the Movie Box Office

Film distributors occasionally withhold movies from critics before their release. Cold openings provide a natural field setting to test models of limited strategic thinking. In a set of 856 widely released movies, cold opening produces a significant 15% increase in domestic box office revenue (though not in foreign markets and DVD sales), consistent with the hypothesis that some moviegoers do not infer low quality from cold opening. Structural parameter estimates indicate 1–2 steps of strategic thinking by moviegoers (comparable to experimental estimates). However, movie studios appear to think moviegoers are sophisticated since only 7% of movies are opened cold

Unlinkable Updatable Databases and Oblivious Transfer with Access Control

An oblivious transfer with access control protocol (OTAC) allows us to protect privacy of accesses to a database while enforcing access control policies. Existing OTAC have several shortcomings. First, their design is not modular. Typically, to create an OTAC, an adaptive oblivious transfer protocol (OT) is extended ad-hoc. Consequently, the security of the OT is reanalyzed when proving security of the OTAC, and it is not possible to instantiate the OTAC with any secure OT. Second, existing OTAC do not allow for policy updates. Finally, in practical applications, many messages share the same policy. However, existing OTAC cannot take advantage of that to improve storage efficiency. We propose an UC-secure OTAC that addresses the aforementioned shortcomings. Our OTAC uses as building blocks the ideal functionalities for OT, for zero-knowledge (ZK) and for an \emph{unlinkable updatable database} (\UUD), which we define and construct. \UUD is a protocol between an updater \fuudUpdater and multiple readers \fuudReader_k. \fuudUpdater sets up a database and updates it. \fuudReader_k can read the database by computing UC ZK proofs of an entry in the database, without disclosing what entry is read. In our OTAC, \UUD is used to store and read the policies. We construct an \UUD based on subvector commitments (SVC). We extend the definition of SVC with update algorithms for commitments and openings, and we provide an UC ZK proof of a subvector. Our efficiency analysis shows that our \UUD is practical

Behavioral, Parameterized, and Broadband Modeling of Wired Interconnects with Internal Discontinuities

We present a complete workflow for the extraction of behavioral reduced-order models of wired interconnect links, including an explicit dependence on geometrical or material parameters describing internal discontinuities that may affect the quality of signal transmission. Thanks to the adopted structure, the models are easily identified from sampled frequency responses at discrete points in the parameter space. Such responses are obtained from off-the-shelf full-wave solvers. A novel algorithm is used for checking and enforcing model stability and passivity, two fundamental requirements for reliably running stable transient simulations. Finally, an ad hoc procedure is devised to synthesize the models as parameterized circuit equivalents, compatible with any SPICE solver. Several examples illustrate and validate the workflow, confirming the suitability of the proposed approach for what-if, parameter sweep, design centering, and optimization through time-domain simulations, possibly including nonlinear devices and terminations