MilliSonic: Pushing the Limits of Acoustic Motion Tracking

Recent years have seen interest in device tracking and localization using acoustic signals. State-of-the-art acoustic motion tracking systems however do not achieve millimeter accuracy and require large separation between microphones and speakers, and as a result, do not meet the requirements for many VR/AR applications. Further, tracking multiple concurrent acoustic transmissions from VR devices today requires sacrificing accuracy or frame rate. We present MilliSonic, a novel system that pushes the limits of acoustic based motion tracking. Our core contribution is a novel localization algorithm that can provably achieve sub-millimeter 1D tracking accuracy in the presence of multipath, while using only a single beacon with a small 4-microphone array.Further, MilliSonic enables concurrent tracking of up to four smartphones without reducing frame rate or accuracy. Our evaluation shows that MilliSonic achieves 0.7mm median 1D accuracy and a 2.6mm median 3D accuracy for smartphones, which is 5x more accurate than state-of-the-art systems. MilliSonic enables two previously infeasible interaction applications: a) 3D tracking of VR headsets using the smartphone as a beacon and b) fine-grained 3D tracking for the Google Cardboard VR system using a small microphone array

Preparation and Mechanical Properties of Continuous Carbon Nanotube Networks Modified C f

Continuous carbon nanotube (CNT) networks were formed in Cf/SiC composites via freeze-drying method. Composites were fabricated by precursor infiltration and pyrolysis (PIP) process afterwards. The different distribution morphologies of CNTs in the preforms originating from the different CNT contents were analyzed while the influence of the distribution of CNTs was discussed in detail. Compared to composites without CNTs, the interfacial shear strength (ILSS) and the flexural strength of Cf/1%CNTs/SiC were increased by 31% and 27%, respectively, but the values of Cf/2.5%CNTs/SiC decreased as a result of lots of defects caused by excess CNTs. With the analysis of ILSS, the flexural strengths, and the fracture morphologies, CNTs effectively improved the weak interfacial strength between T700SC carbon fibers and SiC matrix

Approximation algorithms for product framing and pricing

We propose one of the first models of “product framing” and pricing. Product framing refers to the way consumer choice is influenced by how the products are framed or displayed. We present a model in which a set of products is displayed or framed into a set of virtual web pages. We assume that consumers consider only products in the top pages with different consumers willing to see different numbers of pages. Consumers select a product, if any, from these pages following a general choice model. We show that the product-framing problem is NP-hard. We derive algorithms with guaranteed performance relative to an optimal algorithm under reasonable assumptions. Our algorithms are fast and easy to implement. We also present structural results and design algorithms for pricing under framing effects for the multinomial logit model. We show that, for profit maximization problems, at optimality, products are displayed in descending order of their value gap and in ascending order of their markups

Morphomics predicts response to ipilimumab in patients with stage IV melanoma

Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/113727/1/jso24003.pd

ManiCLIP: Multi-Attribute Face Manipulation from Text

In this paper we present a novel multi-attribute face manipulation method based on textual descriptions. Previous text-based image editing methods either require test-time optimization for each individual image or are restricted to single attribute editing. Extending these methods to multi-attribute face image editing scenarios will introduce undesired excessive attribute change, e.g., text-relevant attributes are overly manipulated and text-irrelevant attributes are also changed. In order to address these challenges and achieve natural editing over multiple face attributes, we propose a new decoupling training scheme where we use group sampling to get text segments from same attribute categories, instead of whole complex sentences. Further, to preserve other existing face attributes, we encourage the model to edit the latent code of each attribute separately via an entropy constraint. During the inference phase, our model is able to edit new face images without any test-time optimization, even from complex textual prompts. We show extensive experiments and analysis to demonstrate the efficacy of our method, which generates natural manipulated faces with minimal text-irrelevant attribute editing. Code and pre-trained model will be released

Ground state solutions for nonlinearly coupled systems of Choquard type with lower critical exponent

In this paper, we study the existence of ground state solutions for the following nonlinearly coupled systems of Choquard type with lower critical exponent by variational methods \begin{equation*} \begin{cases} \displaystyle-\Delta u+V(x)u=(I_\alpha\ast|u|^{\frac{\alpha}{N}+1})|u|^{\frac{\alpha}{N}-1}u+p|u|^{p-2}u|\upsilon|^q,&\mbox{in }\mathbb{R}^N,\\ \displaystyle-\Delta\upsilon+V(x)\upsilon=(I_\alpha\ast|\upsilon|^{\frac{\alpha}{N}+1})|\upsilon|^{\frac{\alpha}{N}-1}\upsilon+q|\upsilon|^{q-2}\upsilon|u|^p,&\mbox{in } \mathbb{R}^N. \end{cases} \end{equation*} Where $N\geq3$, $\alpha\in(0,N)$, $I_\alpha$ is the Riesz potential, $p,q\in\big(1,\sqrt{\frac{N}{N-2}}\big)$ and $Np+(N+2)q<2N+4$, $\frac{N+\alpha}{N}$ is the lower critical exponent in the sense of Hardy–Littlewood–Sobolev inequality and $V\in C(\mathbb{R}^N,(0,\infty))$ is a bounded potential function. As far as we have known, little research has been done on this type of coupled systems up to now. Our research is a promotion and supplement to previous research