Autonomy of the Student: Maintaining Ballet\u27s Relevance as an Art Form Through Pedagogy

In response to the negative critique that denounces ballet as an irrelevant art form,\ud I was interested in analyzing alternative methods of teaching classical ballet. Comprised\ud of a brief history of classical ballet, a literature review of writings within the fields of\ud modern educational theory and dance pedagogy, and interviews of students and teachers,\ud my inquiry argues that the autonomy of the student needs to be maintained within the\ud classroom for classical ballet to maintain its relevance through pedagogy

Estimating Target Vessel Location on Robot-Assisted CABG using Feature-based CT to US Registration

Although robot-assisted coronary artery bypass grafting (RA-CABG) has gained more acceptance worldwide, its success still depends on the surgeon’s experience and expertise, and the conversion rate to full sternotomy is in the order of 15%—25%. One of the reasons for conversion is poor pre-operative planning, which is based solely on pre-operative computed tomography (CT) images. This thesis proposes a technique to estimate the global peri-operative displacement of the heart and to predict the intra-operative target vessel location. The technique has been validated via both an in vitro and a clinical study, and predicted the position of the peri-operative target vessel location with ~ 3.5 mm RMS accuracy in the in vitro study while it yielded ~ 5.0 mm accuracy for the clinical validation. As the desired clinical accuracy imposed by this procedure is on the order of one intercostal space (10 - 15 mm), our technique suits the clinical requirements. It is therefore believed that this technique has the potential to improve the pre-operative planning by updating peri-operative migration patterns of the heart and, consequently, will lead to reduced conversion to conventional open thoracic procedures

Monotheism and its Vicissitudes

Challenging the claim that monotheism is intolerant, the author presents an original interpretation of Sigmund Freud’s last book Moses and Monotheism. Freud is shown offering a theory of monotheism in which monotheism is not seen as exclusive, but rather as inherently equivocal

Generation of graph-state streams

We propose a protocol to generate a stream of mobile qubits in a graph state through a single stationary parent qubit and discuss two types of its physical implementation, namely, the generation of photonic graph states through an atom-like qubit and those of flying atoms through a cavity-mode photonic qubit. The generated graph states fall into an important class that can hugely reduce the resource requirement of fault-tolerant linear optics quantum computation, which was previously known to be far from realistic. In regard to the flying atoms, we also propose a heralded generation scheme, which allows for high-fidelity graph states even under the photon loss.Comment: Accepted for publication at PRA Rapid Communication

On scaled hyperbolic numbers induced by scaled hyperbolic rings

In this paper, we generalize the well-known hyperbolic numbers to certain numeric structures scaled by the real numbers. Under our scaling of $\mathbb{R}$, the usual hyperbolic numbers are understood to be our 1-scaled hyperbolic numbers. If a scale $t$ is not positive in $\mathbb{R}$, then our $t$-scaled hyperbolic numbers have similar numerical structures with those of the complex numbers, however, if a scale is positive in $\mathbb{R}$, then their numerical properties are similar to those of the classical hyperbolic numbers. We here understand scaled-hyperbolic numbers as elements of the scaled-hypercomplex rings $\{\mathbb{H}_t\}_{t\in \mathbb{R}}$, introduced in [1]. This scaled-hyperbolic analysis is done by algebra, analysis, operator theory, operator-algebra theory and free probability on scaled-hypercomplex number

Efficient Neural Network Robustness Certification with General Activation Functions

Finding minimum distortion of adversarial examples and thus certifying robustness in neural network classifiers for given data points is known to be a challenging problem. Nevertheless, recently it has been shown to be possible to give a non-trivial certified lower bound of minimum adversarial distortion, and some recent progress has been made towards this direction by exploiting the piece-wise linear nature of ReLU activations. However, a generic robustness certification for general activation functions still remains largely unexplored. To address this issue, in this paper we introduce CROWN, a general framework to certify robustness of neural networks with general activation functions for given input data points. The novelty in our algorithm consists of bounding a given activation function with linear and quadratic functions, hence allowing it to tackle general activation functions including but not limited to four popular choices: ReLU, tanh, sigmoid and arctan. In addition, we facilitate the search for a tighter certified lower bound by adaptively selecting appropriate surrogates for each neuron activation. Experimental results show that CROWN on ReLU networks can notably improve the certified lower bounds compared to the current state-of-the-art algorithm Fast-Lin, while having comparable computational efficiency. Furthermore, CROWN also demonstrates its effectiveness and flexibility on networks with general activation functions, including tanh, sigmoid and arctan.Comment: Accepted by NIPS 2018. Huan Zhang and Tsui-Wei Weng contributed equall

Schur analysis over the unit spectral ball

We define the corresponding Hardy space, Schur multipliers and their realizations, and interpolation. Possible applications of the present work include matrices of quaternions, matrices of split quaternions, and other algebras of hypercomplex numbers