Putting holes in holey geometry: Topology change for arbitrary surfaces

This paper presents a method for computing topology changes for triangle meshes in an interactive geometric modeling environment. Most triangle meshes in practice do not exhibit desirable geometric properties, so we develop a solution that is independent of standard assumptions and robust to geometric errors. Specifically, we provide the first method for topology change applicable to arbitrary non-solid, non-manifold, non-closed, self-intersecting surfaces. We prove that this new method for topology change produces the expected conventional results when applied to solid (closed, manifold, non-self-intersecting) surfaces---that is, we prove a backwards-compatibility property relative to prior work. Beyond solid surfaces, we present empirical evidence that our method remains tolerant to a variety of surface aberrations through the incorporation of a novel error correction scheme. Finally, we demonstrate how topology change applied to non-solid objects enables wholly new and useful behaviors

Optimal Periodic Control: The pi Test Revisited

Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/57837/1/PeriodicControlTAC1980.pd

Opt: A Domain Specific Language for Non-linear Least Squares Optimization in Graphics and Imaging

Many graphics and vision problems can be expressed as non-linear least squares optimizations of objective functions over visual data, such as images and meshes. The mathematical descriptions of these functions are extremely concise, but their implementation in real code is tedious, especially when optimized for real-time performance on modern GPUs in interactive applications. In this work, we propose a new language, Opt (available under http://optlang.org), for writing these objective functions over image- or graph-structured unknowns concisely and at a high level. Our compiler automatically transforms these specifications into state-of-the-art GPU solvers based on Gauss-Newton or Levenberg-Marquardt methods. Opt can generate different variations of the solver, so users can easily explore tradeoffs in numerical precision, matrix-free methods, and solver approaches. In our results, we implement a variety of real-world graphics and vision applications. Their energy functions are expressible in tens of lines of code, and produce highly-optimized GPU solver implementations. These solver have performance competitive with the best published hand-tuned, application-specific GPU solvers, and orders of magnitude beyond a general-purpose auto-generated solver

Detecting brute-force attacks on cryptocurrency wallets

Blockchain is a distributed ledger, which is protected against malicious modifications by means of cryptographic tools, e.g. digital signatures and hash functions. One of the most prominent applications of blockchains is cryptocurrencies, such as Bitcoin. In this work, we consider a particular attack on wallets for collecting assets in a cryptocurrency network based on brute-force search attacks. Using Bitcoin as an example, we demonstrate that if the attack is implemented successfully, a legitimate user is able to prove that fact of this attack with a high probability. We also consider two options for modification of existing cryptocurrency protocols for dealing with this type of attacks. First, we discuss a modification that requires introducing changes in the Bitcoin protocol and allows diminishing the motivation to attack wallets. Second, an alternative option is the construction of special smart-contracts, which reward the users for providing evidence of the brute-force attack. The execution of this smart-contract can work as an automatic alarm that the employed cryptographic mechanisms, and (particularly) hash functions, have an evident vulnerability.Comment: 10 pages, 2 figures; published versio

Observations on COMET

This note presents two attacks against COMET, a second-round candidate in the NIST lightweight cryptography standardization process. The first attack uses a long message to detect the use of weak keys, whereas the second attack focuses on the resistance of COMET against slide attacks. These attacks do not invalidate the security claims of the designers

Level densities and γ\gamma-ray strength functions in 170,171,172^{170,171,172}Yb

Level densities and radiative strength functions in $^{171}$Yb and $^{170}$Yb nuclei have been measured using the $^{171}$Yb($^3$He,$^3$He$^\prime\gamma$)$^{171}$Yb and $^{171}$Yb($^3$He,$\alpha\gamma$)$^{170}$Yb reactions. New data on $^{171}$Yb are compared to a previous measurement for $^{171}$Yb from the $^{172}$Yb($^3$He,$\alpha\gamma$)$^{171}$Yb reaction. Systematics of level densities and radiative strength functions in $^{170,171,172}$Yb are established. The entropy excess in $^{171}$Yb relative to the even-even nuclei $^{170,172}$Yb due to the unpaired neutron quasiparticle is found to be approximately 2$k_B$. Results for the radiative strength function from the two reactions lead to consistent parameters characterizing the ``pygmy'' resonances. Pygmy resonances in the $^{170,172}$Yb populated by the ($^3$He,$\alpha$) reaction appear to be split into two components for both of which a complete set of resonance parameters are obtained.Comment: 8 pages, 7 figure

Context and perceptual salience influence the formation of novel stereotypes via cumulative cultural evolution

We use a transmission chain method to establish how context and category salience influence the formation of novel stereotypes through cumulative cultural evolution. We created novel alien targets by combining features from three category dimensions—color, movement, and shape—thereby creating social targets that were individually unique but that also shared category membership with other aliens (e.g., two aliens might be the same color and shape but move differently). At the start of the transmission chains each alien was randomly assigned attributes that described it (e.g., arrogant, caring, confident). Participants were given training on the alien-attribute assignments and were then tested on their memory for these. The alien-attribute assignments participants produced during test were used as the training materials for the next participant in the transmission chain. As information was repeatedly transmitted an increasingly simplified, learnable stereotype-like structure emerged for targets who shared the same color, such that by the end of the chains targets who shared the same color were more likely to share the same attributes (a reanalysis of data from Martin et al., 2014 which we term Experiment 1). The apparent bias toward the formation of novel stereotypes around the color category dimension was also found for objects (Experiment 2). However, when the category dimension of color was made less salient, it no longer dominated the formation of novel stereotypes (Experiment 3). The current findings suggest that context and category salience influence category dimension salience, which in turn influences the cumulative cultural evolution of information.<br/