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43bf4bad-9105-4bdf-bd78-d1ccdfa6dbfc
43bf4bad-9105-4bdf-bd78-d1ccdfa6dbfc
43bf4bad-9105-4bdf-bd78-d1ccdfa6dbfc
human
null
null
none
abstracts
DeepLab: Semantic Image Segmentation with Deep Convolutional Nets, Atrous Convolution, and Fully Connected CRFs
null
In this work we address the task of semantic image segmentation with Deep Learning and make three main contributions that are experimentally shown to have substantial practical merit. First, we highlight convolution with upsampled filters, or 'atrous convolution', as a powerful tool in dense prediction tasks. Atrous co...
771f8e8c-a41a-410b-bb61-2b0e70467c95
771f8e8c-a41a-410b-bb61-2b0e70467c95
771f8e8c-a41a-410b-bb61-2b0e70467c95
human
null
null
none
abstracts
Object Discovery via Cohesion Measurement
null
Color and intensity are two important components in an image. Usually, groups of image pixels, which are similar in color or intensity, are an informative representation for an object. They are therefore particularly suitable for computer vision tasks, such as saliency detection and object proposal generation. However,...
1afb7c7d-24f7-48d5-9f6a-aa755c67bca9
1afb7c7d-24f7-48d5-9f6a-aa755c67bca9
1afb7c7d-24f7-48d5-9f6a-aa755c67bca9
human
null
null
none
abstracts
Deep Learning for Multi-Task Medical Image Segmentation in Multiple Modalities
null
Automatic segmentation of medical images is an important task for many clinical applications. In practice, a wide range of anatomical structures are visualised using different imaging modalities. In this paper, we investigate whether a single convolutional neural network (CNN) can be trained to perform different segmen...
26d1f313-f244-4df4-9929-c66886bb29b3
26d1f313-f244-4df4-9929-c66886bb29b3
26d1f313-f244-4df4-9929-c66886bb29b3
human
null
null
none
abstracts
Structured Learning of Tree Potentials in CRF for Image Segmentation
null
We propose a new approach to image segmentation, which exploits the advantages of both conditional random fields (CRFs) and decision trees. In the literature, the potential functions of CRFs are mostly defined as a linear combination of some pre-defined parametric models, and then methods like structured support vector...
722f13c4-cf25-4279-9191-a023b49e53ea
722f13c4-cf25-4279-9191-a023b49e53ea
722f13c4-cf25-4279-9191-a023b49e53ea
human
null
null
none
abstracts
k-Means Clustering and Ensemble of Regressions: An Algorithm for the ISIC 2017 Skin Lesion Segmentation Challenge
null
This abstract briefly describes a segmentation algorithm developed for the ISIC 2017 Skin Lesion Detection Competition hosted at [ref]. The objective of the competition is to perform a segmentation (in the form of a binary mask image) of skin lesions in dermoscopic images as close as possible to a segmentation performe...
ce2077bf-e2d9-4ae6-b49b-25b586e4edf5
ce2077bf-e2d9-4ae6-b49b-25b586e4edf5
ce2077bf-e2d9-4ae6-b49b-25b586e4edf5
human
null
null
none
abstracts
Learning Normalized Inputs for Iterative Estimation in Medical Image Segmentation
null
In this paper, we introduce a simple, yet powerful pipeline for medical image segmentation that combines Fully Convolutional Networks (FCNs) with Fully Convolutional Residual Networks (FC-ResNets). We propose and examine a design that takes particular advantage of recent advances in the understanding of both Convolutio...
679eac63-52d1-4c28-82bb-ce60718ab36b
679eac63-52d1-4c28-82bb-ce60718ab36b
679eac63-52d1-4c28-82bb-ce60718ab36b
human
null
null
none
abstracts
Image Segmentation Using Overlapping Group Sparsity
null
Sparse decomposition has been widely used for different applications, such as source separation, image classification and image denoising. This paper presents a new algorithm for segmentation of an image into background and foreground text and graphics using sparse decomposition. First, the background is represented us...
405fe838-cab2-4f7e-9833-4c045c1bbdf3
405fe838-cab2-4f7e-9833-4c045c1bbdf3
405fe838-cab2-4f7e-9833-4c045c1bbdf3
human
null
null
none
abstracts
Fine-grained Recurrent Neural Networks for Automatic Prostate Segmentation in Ultrasound Images
null
Boundary incompleteness raises great challenges to automatic prostate segmentation in ultrasound images. Shape prior can provide strong guidance in estimating the missing boundary, but traditional shape models often suffer from hand-crafted descriptors and local information loss in the fitting procedure. In this paper,...
891c294c-58d9-4ba3-b085-b992f1ef2818
891c294c-58d9-4ba3-b085-b992f1ef2818
891c294c-58d9-4ba3-b085-b992f1ef2818
human
null
null
none
abstracts
MCMC Shape Sampling for Image Segmentation with Nonparametric Shape Priors
null
Segmenting images of low quality or with missing data is a challenging problem. Integrating statistical prior information about the shapes to be segmented can improve the segmentation results significantly. Most shape-based segmentation algorithms optimize an energy functional and find a point estimate for the object t...
ade3fd87-30b8-4664-91fa-61b2bb99c132
ade3fd87-30b8-4664-91fa-61b2bb99c132
ade3fd87-30b8-4664-91fa-61b2bb99c132
human
null
null
none
abstracts
Theoretical Analysis of Active Contours on Graphs
null
Active contour models based on partial differential equations have proved successful in image segmentation, yet the study of their geometric formulation on arbitrary geometric graphs is still at an early stage. In this paper, we introduce geometric approximations of gradient and curvature, which are used in the geodesi...
8bf02f83-d4a0-43dd-b7e5-e35d82337d9a
8bf02f83-d4a0-43dd-b7e5-e35d82337d9a
8bf02f83-d4a0-43dd-b7e5-e35d82337d9a
human
null
null
none
abstracts
Combinatorial Energy Learning for Image Segmentation
null
We introduce a new machine learning approach for image segmentation that uses a neural network to model the conditional energy of a segmentation given an image. Our approach, combinatorial energy learning for image segmentation (CELIS) places a particular emphasis on modeling the inherent combinatorial nature of dense ...
3ce9a084-3b0a-4e7c-aeab-acb4b02105b3
3ce9a084-3b0a-4e7c-aeab-acb4b02105b3
3ce9a084-3b0a-4e7c-aeab-acb4b02105b3
human
null
null
none
abstracts
A 4D Light-Field Dataset and CNN Architectures for Material Recognition
null
We introduce a new light-field dataset of materials, and take advantage of the recent success of deep learning to perform material recognition on the 4D light-field. Our dataset contains 12 material categories, each with 100 images taken with a Lytro Illum, from which we extract about 30,000 patches in total. To the be...
eed27bff-8deb-44ec-ad7b-3c6316bd345d
eed27bff-8deb-44ec-ad7b-3c6316bd345d
eed27bff-8deb-44ec-ad7b-3c6316bd345d
human
null
null
none
abstracts
SSHMT: Semi-supervised Hierarchical Merge Tree for Electron Microscopy Image Segmentation
null
Region-based methods have proven necessary for improving segmentation accuracy of neuronal structures in electron microscopy (EM) images. Most region-based segmentation methods use a scoring function to determine region merging. Such functions are usually learned with supervised algorithms that demand considerable grou...
54e0f95e-00d1-469e-ad5f-aee23ffdcc3d
54e0f95e-00d1-469e-ad5f-aee23ffdcc3d
54e0f95e-00d1-469e-ad5f-aee23ffdcc3d
human
null
null
none
abstracts
Superpixel Convolutional Networks using Bilateral Inceptions
null
In this paper we propose a CNN architecture for semantic image segmentation. We introduce a new 'bilateral inception' module that can be inserted in existing CNN architectures and performs bilateral filtering, at multiple feature-scales, between superpixels in an image. The feature spaces for bilateral filtering and ot...
fad4e6d3-4732-418a-9dcb-7722141430a3
fad4e6d3-4732-418a-9dcb-7722141430a3
fad4e6d3-4732-418a-9dcb-7722141430a3
human
null
null
none
abstracts
Screen Content Image Segmentation Using Sparse Decomposition and Total Variation Minimization
null
Sparse decomposition has been widely used for different applications, such as source separation, image classification, image denoising and more. This paper presents a new algorithm for segmentation of an image into background and foreground text and graphics using sparse decomposition and total variation minimization. ...
32ad507a-fd83-458a-8a3d-0d4f8c6b5b47
32ad507a-fd83-458a-8a3d-0d4f8c6b5b47
32ad507a-fd83-458a-8a3d-0d4f8c6b5b47
human
null
null
none
abstracts
Incorporating prior knowledge in medical image segmentation: a survey
null
Medical image segmentation, the task of partitioning an image into meaningful parts, is an important step toward automating medical image analysis and is at the crux of a variety of medical imaging applications, such as computer aided diagnosis, therapy planning and delivery, and computer aided interventions. However, ...
04284051-7a7a-4104-bd93-0f44b50ed616
04284051-7a7a-4104-bd93-0f44b50ed616
04284051-7a7a-4104-bd93-0f44b50ed616
human
null
null
none
abstracts
Efficient piecewise training of deep structured models for semantic segmentation
null
Recent advances in semantic image segmentation have mostly been achieved by training deep convolutional neural networks (CNNs). We show how to improve semantic segmentation through the use of contextual information; specifically, we explore `patch-patch' context between image regions, and `patch-background' context. Fo...
1091bb0b-6cb0-4667-b117-58ee4136ee94
1091bb0b-6cb0-4667-b117-58ee4136ee94
1091bb0b-6cb0-4667-b117-58ee4136ee94
human
null
null
none
abstracts
Bridging Category-level and Instance-level Semantic Image Segmentation
null
We propose an approach to instance-level image segmentation that is built on top of category-level segmentation. Specifically, for each pixel in a semantic category mask, its corresponding instance bounding box is predicted using a deep fully convolutional regression network. Thus it follows a different pipeline to the...
fe96becb-05e7-47fa-bf1f-41acbedb8636
fe96becb-05e7-47fa-bf1f-41acbedb8636
fe96becb-05e7-47fa-bf1f-41acbedb8636
human
null
null
none
abstracts
Fast Semantic Image Segmentation with High Order Context and Guided Filtering
null
This paper describes a fast and accurate semantic image segmentation approach that encodes not only the discriminative features from deep neural networks, but also the high-order context compatibility among adjacent objects as well as low level image features. We formulate the underlying problem as the conditional rand...
bd1160c4-4533-4102-b1bb-1c5b3304ff5f
bd1160c4-4533-4102-b1bb-1c5b3304ff5f
bd1160c4-4533-4102-b1bb-1c5b3304ff5f
human
null
null
none
abstracts
A Classifier-guided Approach for Top-down Salient Object Detection
null
We propose a framework for top-down salient object detection that incorporates a tightly coupled image classification module. The classifier is trained on novel category-aware sparse codes computed on object dictionaries used for saliency modeling. A misclassification indicates that the corresponding saliency model is ...
fce72cc8-d3d3-4ff3-973d-9371dceab939
fce72cc8-d3d3-4ff3-973d-9371dceab939
fce72cc8-d3d3-4ff3-973d-9371dceab939
human
null
null
none
abstracts
Fully-Automatic Synapse Prediction and Validation on a Large Data Set
null
Extracting a connectome from an electron microscopy (EM) data set requires identification of neurons and determination of synapses between neurons. As manual extraction of this information is very time-consuming, there has been extensive research effort to automatically segment the neurons to help guide and eventually ...
8a1ace59-3d8c-483d-a8dc-7a15e898f310
8a1ace59-3d8c-483d-a8dc-7a15e898f310
8a1ace59-3d8c-483d-a8dc-7a15e898f310
human
null
null
none
abstracts
Kernelized Weighted SUSAN based Fuzzy C-Means Clustering for Noisy Image Segmentation
null
The paper proposes a novel Kernelized image segmentation scheme for noisy images that utilizes the concept of Smallest Univalue Segment Assimilating Nucleus (SUSAN) and incorporates spatial constraints by computing circular colour map induced weights. Fuzzy damping coefficients are obtained for each nucleus or center p...
33990fb9-7202-4e37-8d52-b1df461a4951
33990fb9-7202-4e37-8d52-b1df461a4951
33990fb9-7202-4e37-8d52-b1df461a4951
human
null
null
none
abstracts
Integrated Inference and Learning of Neural Factors in Structural Support Vector Machines
null
Tackling pattern recognition problems in areas such as computer vision, bioinformatics, speech or text recognition is often done best by taking into account task-specific statistical relations between output variables. In structured prediction, this internal structure is used to predict multiple outputs simultaneously,...
df3be76c-8027-4379-a2d3-1f92e94a7842
df3be76c-8027-4379-a2d3-1f92e94a7842
df3be76c-8027-4379-a2d3-1f92e94a7842
human
null
null
none
abstracts
Graph entropies in texture segmentation of images
null
We study the applicability of a set of texture descriptors introduced in recent work by the author to texture-based segmentation of images. The texture descriptors under investigation result from applying graph indices from quantitative graph theory to graphs encoding the local structure of images. The underlying graph...
630ef64e-3295-4eaf-b366-69b602196016
630ef64e-3295-4eaf-b366-69b602196016
630ef64e-3295-4eaf-b366-69b602196016
human
null
null
none
abstracts
Regional Active Contours based on Variational level sets and Machine Learning for Image Segmentation
null
Image segmentation is the problem of partitioning an image into different subsets, where each subset may have a different characterization in terms of color, intensity, texture, and/or other features. Segmentation is a fundamental component of image processing, and plays a significant role in computer vision, object re...
56166659-ec7a-41d0-9396-fd6abfdf7861
56166659-ec7a-41d0-9396-fd6abfdf7861
56166659-ec7a-41d0-9396-fd6abfdf7861
human
null
null
none
abstracts
Deeply Learning the Messages in Message Passing Inference
null
Deep structured output learning shows great promise in tasks like semantic image segmentation. We proffer a new, efficient deep structured model learning scheme, in which we show how deep Convolutional Neural Networks (CNNs) can be used to estimate the messages in message passing inference for structured prediction wit...
36db5def-75bc-48cc-9d66-1e673e563773
36db5def-75bc-48cc-9d66-1e673e563773
36db5def-75bc-48cc-9d66-1e673e563773
human
null
null
none
abstracts
A Novel Approach Towards Clustering Based Image Segmentation
null
In computer vision, image segmentation is always selected as a major research topic by researchers. Due to its vital rule in image processing, there always arises the need of a better image segmentation method. Clustering is an unsupervised study with its application in almost every field of science and engineering. Ma...
5bd44b68-d473-4224-82a7-b1023155c1ba
5bd44b68-d473-4224-82a7-b1023155c1ba
5bd44b68-d473-4224-82a7-b1023155c1ba
human
null
null
none
abstracts
Deep Learning for Medical Image Segmentation
null
This report provides an overview of the current state of the art deep learning architectures and optimisation techniques, and uses the ADNI hippocampus MRI dataset as an example to compare the effectiveness and efficiency of different convolutional architectures on the task of patch-based 3-dimensional hippocampal segm...
00bc54c0-632d-49a1-afec-0b813da77a46
00bc54c0-632d-49a1-afec-0b813da77a46
00bc54c0-632d-49a1-afec-0b813da77a46
human
null
null
none
abstracts
Evolving Fuzzy Image Segmentation with Self-Configuration
null
Current image segmentation techniques usually require that the user tune several parameters in order to obtain maximum segmentation accuracy, a computationally inefficient approach, especially when a large number of images must be processed sequentially in daily practice. The use of evolving fuzzy systems for designing...
1e2a9ff9-abdb-4a71-b656-3dcefbf0faab
1e2a9ff9-abdb-4a71-b656-3dcefbf0faab
1e2a9ff9-abdb-4a71-b656-3dcefbf0faab
human
null
null
none
abstracts
Bethe Learning of Conditional Random Fields via MAP Decoding
null
Many machine learning tasks can be formulated in terms of predicting structured outputs. In frameworks such as the structured support vector machine (SVM-Struct) and the structured perceptron, discriminative functions are learned by iteratively applying efficient maximum a posteriori (MAP) decoding. However, maximum li...
0efbebca-d6fa-4e22-848c-d880b538be06
0efbebca-d6fa-4e22-848c-d880b538be06
0efbebca-d6fa-4e22-848c-d880b538be06
human
null
null
none
abstracts
Fast Constraint Propagation for Image Segmentation
null
This paper presents a novel selective constraint propagation method for constrained image segmentation. In the literature, many pairwise constraint propagation methods have been developed to exploit pairwise constraints for cluster analysis. However, since most of these methods have a polynomial time complexity, they a...
5c337fac-1159-4849-a09e-aad39334e431
5c337fac-1159-4849-a09e-aad39334e431
5c337fac-1159-4849-a09e-aad39334e431
human
null
null
none
abstracts
Unsupervised image segmentation by Global and local Criteria Optimization Based on Bayesian Networks
null
Today Bayesian networks are more used in many areas of decision support and image processing. In this way, our proposed approach uses Bayesian Network to modelize the segmented image quality. This quality is calculated on a set of attributes that represent local evaluation measures. The idea is to have these local leve...
a29d1548-e47d-4a63-b18d-706267efdf14
a29d1548-e47d-4a63-b18d-706267efdf14
a29d1548-e47d-4a63-b18d-706267efdf14
human
null
null
none
abstracts
Highly Efficient Forward and Backward Propagation of Convolutional Neural Networks for Pixelwise Classification
null
We present highly efficient algorithms for performing forward and backward propagation of Convolutional Neural Network (CNN) for pixelwise classification on images. For pixelwise classification tasks, such as image segmentation and object detection, surrounding image patches are fed into CNN for predicting the classes ...
a99184a4-6066-4778-99ed-4f3c9d98ba83
a99184a4-6066-4778-99ed-4f3c9d98ba83
a99184a4-6066-4778-99ed-4f3c9d98ba83
human
null
null
none
abstracts
Fast Edge Detection Using Structured Forests
null
Edge detection is a critical component of many vision systems, including object detectors and image segmentation algorithms. Patches of edges exhibit well-known forms of local structure, such as straight lines or T-junctions. In this paper we take advantage of the structure present in local image patches to learn both ...
7fdb0b4a-1cf4-4a4d-8ab5-c221c8e1ada9
7fdb0b4a-1cf4-4a4d-8ab5-c221c8e1ada9
7fdb0b4a-1cf4-4a4d-8ab5-c221c8e1ada9
human
null
null
none
abstracts
Open-set Person Re-identification
null
Person re-identification is becoming a hot research for developing both machine learning algorithms and video surveillance applications. The task of person re-identification is to determine which person in a gallery has the same identity to a probe image. This task basically assumes that the subject of the probe image ...
59dd570d-3eda-49b1-85aa-fa94abaabaec
59dd570d-3eda-49b1-85aa-fa94abaabaec
59dd570d-3eda-49b1-85aa-fa94abaabaec
human
null
null
none
abstracts
Near-optimal Keypoint Sampling for Fast Pathological Lung Segmentation
null
Accurate delineation of pathological lungs from computed tomography (CT) images remains mostly unsolved because available methods fail to provide a reliable generic solution due to high variability of abnormality appearance. Local descriptor-based classification methods have shown to work well in annotating pathologies...
51d16092-4f0c-4c73-9d5e-13fc713cb941
51d16092-4f0c-4c73-9d5e-13fc713cb941
51d16092-4f0c-4c73-9d5e-13fc713cb941
human
null
null
none
abstracts
Incorporating Near-Infrared Information into Semantic Image Segmentation
null
Recent progress in computational photography has shown that we can acquire near-infrared (NIR) information in addition to the normal visible (RGB) band, with only slight modifications to standard digital cameras. Due to the proximity of the NIR band to visible radiation, NIR images share many properties with visible im...
5c9dc6c5-d804-48a3-8309-5c671883d770
5c9dc6c5-d804-48a3-8309-5c671883d770
5c9dc6c5-d804-48a3-8309-5c671883d770
human
null
null
none
abstracts
Variational Image Segmentation Model Coupled with Image Restoration Achievements
null
Image segmentation and image restoration are two important topics in image processing with great achievements. In this paper, we propose a new multiphase segmentation model by combining image restoration and image segmentation models. Utilizing image restoration aspects, the proposed segmentation model can effectively ...
34276620-b1c3-4c30-97d5-2f222f881076
34276620-b1c3-4c30-97d5-2f222f881076
34276620-b1c3-4c30-97d5-2f222f881076
human
null
null
none
abstracts
A Tiered Move-making Algorithm for General Non-submodular Pairwise Energies
null
A large number of problems in computer vision can be modelled as energy minimization problems in a Markov Random Field (MRF) or Conditional Random Field (CRF) framework. Graph-cuts based $\alpha$-expansion is a standard move-making method to minimize the energy functions with sub-modular pairwise terms. However, certai...
4b1ca80e-60c9-4567-b437-90fc7c4545af
4b1ca80e-60c9-4567-b437-90fc7c4545af
4b1ca80e-60c9-4567-b437-90fc7c4545af
human
null
null
none
abstracts
Clustering using Vector Membership: An Extension of the Fuzzy C-Means Algorithm
null
Clustering is an important facet of explorative data mining and finds extensive use in several fields. In this paper, we propose an extension of the classical Fuzzy C-Means clustering algorithm. The proposed algorithm, abbreviated as VFC, adopts a multi-dimensional membership vector for each data point instead of the t...
d491aa7c-3468-4ac9-acd1-d72353da723b
d491aa7c-3468-4ac9-acd1-d72353da723b
d491aa7c-3468-4ac9-acd1-d72353da723b
human
null
null
none
abstracts
Efficient Energy Minimization for Enforcing Statistics
null
Energy minimization algorithms, such as graph cuts, enable the computation of the MAP solution under certain probabilistic models such as Markov random fields. However, for many computer vision problems, the MAP solution under the model is not the ground truth solution. In many problem scenarios, the system has access ...
39b84587-7fd4-4a2b-a566-aaad6d196df1
39b84587-7fd4-4a2b-a566-aaad6d196df1
39b84587-7fd4-4a2b-a566-aaad6d196df1
human
null
null
none
abstracts
Live-wire 3D medical images segmentation
null
This report describes the design, implementation, evaluation and original enhancements to the Live-Wire method for 2D and 3D image segmentation. Live-Wire 2D employs a semi-automatic paradigm; the user is asked to select a few boundary points of the object to segment, to steer the process in the right direction, while ...
c7755a04-f926-4698-9639-a3613011e9f9
c7755a04-f926-4698-9639-a3613011e9f9
c7755a04-f926-4698-9639-a3613011e9f9
human
null
null
none
abstracts
Robust Image Segmentation in Low Depth Of Field Images
null
In photography, low depth of field (DOF) is an important technique to emphasize the object of interest (OOI) within an image. Thus, low DOF images are widely used in the application area of macro, portrait or sports photography. When viewing a low DOF image, the viewer implicitly concentrates on the regions that are sh...
5995c43a-4d3e-4323-b562-9617d4756b35
5995c43a-4d3e-4323-b562-9617d4756b35
5995c43a-4d3e-4323-b562-9617d4756b35
human
null
null
none
abstracts
Gray Image extraction using Fuzzy Logic
null
Fuzzy systems concern fundamental methodology to represent and process uncertainty and imprecision in the linguistic information. The fuzzy systems that use fuzzy rules to represent the domain knowledge of the problem are known as Fuzzy Rule Base Systems (FRBS). On the other hand image segmentation and subsequent extra...
b78ac52e-93ca-4ed2-9b68-32f6cf1f4617
b78ac52e-93ca-4ed2-9b68-32f6cf1f4617
b78ac52e-93ca-4ed2-9b68-32f6cf1f4617
human
null
null
none
abstracts
3D Model Assisted Image Segmentation
null
The problem of segmenting a given image into coherent regions is important in Computer Vision and many industrial applications require segmenting a known object into its components. Examples include identifying individual parts of a component for process control work in a manufacturing plant and identifying parts of a ...
2dca91ca-3683-4870-92c8-e9172f837fa9
2dca91ca-3683-4870-92c8-e9172f837fa9
2dca91ca-3683-4870-92c8-e9172f837fa9
human
null
null
none
abstracts
A linear framework for region-based image segmentation and inpainting involving curvature penalization
null
We present the first method to handle curvature regularity in region-based image segmentation and inpainting that is independent of initialization. To this end we start from a new formulation of length-based optimization schemes, based on surface continuation constraints, and discuss the connections to existing schem...
8c9cafc4-fe7b-4b95-9ed7-ac1e5f2cafea
8c9cafc4-fe7b-4b95-9ed7-ac1e5f2cafea
8c9cafc4-fe7b-4b95-9ed7-ac1e5f2cafea
human
null
null
none
abstracts
Multi-environment model estimation for motility analysis of Caenorhabditis Elegans
null
The nematode Caenorhabditis elegans is a well-known model organism used to investigate fundamental questions in biology. Motility assays of this small roundworm are designed to study the relationships between genes and behavior. Commonly, motility analysis is used to classify nematode movements and characterize them qu...
4c4676d5-c143-448c-b058-9c360b04d900
4c4676d5-c143-448c-b058-9c360b04d900
4c4676d5-c143-448c-b058-9c360b04d900
human
null
null
none
abstracts
A Topological derivative based image segmentation for sign language recognition system using isotropic filter
null
The need of sign language is increasing radically especially to hearing impaired community. Only few research groups try to automatically recognize sign language from video, colored gloves and etc. Their approach requires a valid segmentation of the data that is used for training and of the data that is used to be reco...
dfae1272-4190-42eb-bc08-706538d93519
dfae1272-4190-42eb-bc08-706538d93519
dfae1272-4190-42eb-bc08-706538d93519
human
null
null
none
abstracts
An information-theoretic derivation of min-cut based clustering
null
Min-cut clustering, based on minimizing one of two heuristic cost-functions proposed by Shi and Malik, has spawned tremendous research, both analytic and algorithmic, in the graph partitioning and image segmentation communities over the last decade. It is however unclear if these heuristics can be derived from a more g...
106a77e0-cf20-44a6-bfa9-6ffd08551882
106a77e0-cf20-44a6-bfa9-6ffd08551882
106a77e0-cf20-44a6-bfa9-6ffd08551882
human
null
null
none
abstracts
$L^2$ well-posedness of boundary value problems for parabolic systems with measurable coefficients
null
We prove the first positive results concerning boundary value problems in the upper half-space of second order parabolic systems only assuming measurability and some transversal regularity in the coefficients of the elliptic part. To do so, we introduce and develop a first order strategy by means of a parabolic Dirac...
f1d0a319-76ee-4cf2-9ca0-51ecc51f7f2d
f1d0a319-76ee-4cf2-9ca0-51ecc51f7f2d
f1d0a319-76ee-4cf2-9ca0-51ecc51f7f2d
human
null
null
none
abstracts
Design and Application of Variable Temperature Environmental Capsule for Scanning Electron Microscopy in Gases and Liquids at Ambient Conditions
null
Scanning electron microscopy (SEM) of nanoscale objects in their native conditions and at different temperatures are of critical importance in revealing details of their interactions with ambient environments. Currently available environmental capsules are equipped with thin electron transparent membranes and allow i...
c1eebe39-464c-45c7-8ff7-6f85731b0df3
c1eebe39-464c-45c7-8ff7-6f85731b0df3
c1eebe39-464c-45c7-8ff7-6f85731b0df3
human
null
null
none
abstracts
Effective results for Diophantine equations over finitely generated domains
null
Let A be an arbitrary integral domain of characteristic 0 which is finitely generated over Z. We consider Thue equations $F(x,y)=b$ with unknowns x,y from A and hyper- and superelliptic equations $f(x)=by^m$ with unknowns from A, where the binary form F and the polynomial f have their coefficients in A, where b is a ...
4eaa8a84-736e-415b-a272-74e2e37328e3
4eaa8a84-736e-415b-a272-74e2e37328e3
4eaa8a84-736e-415b-a272-74e2e37328e3
human
null
null
none
abstracts
Blow-ups in generalized complex geometry
null
We study blow-ups in generalized complex geometry. To that end we introduce the concept of holomorphic ideal, which allows one to define a blow-up in the category of smooth manifolds. We then investigate which generalized complex submanifolds are suitable for blowing up. Two classes naturally appear; generalized Pois...
10187bc0-8c50-4561-bc3e-f7f933527be3
10187bc0-8c50-4561-bc3e-f7f933527be3
10187bc0-8c50-4561-bc3e-f7f933527be3
human
null
null
none
abstracts
An Icosahedral Quasicrystal as a Packing of Regular Tetrahedra
null
We present the construction of a dense, quasicrystalline packing of regular tetrahedra with icosahedral symmetry. This quasicrystalline packing was achieved through two independent approaches. The first approach originates in the Elser-Sloane 4D quasicrystal. A 3D slice of the quasicrystal contains a few types of pro...
a623e336-ca8b-4330-b4b8-dd3f464577af
a623e336-ca8b-4330-b4b8-dd3f464577af
a623e336-ca8b-4330-b4b8-dd3f464577af
human
null
null
none
abstracts
Detection of hidden structures on all scales in amorphous materials and complex physical systems: basic notions and applications to networks, lattice systems, and glasses
null
Recent decades have seen the discovery of numerous complex materials. At the root of the complexity underlying many of these materials lies a large number of possible contending atomic- and larger-scale configurations and the intricate correlations between their constituents. For a detailed understanding, there is a ...
62a9d698-4df2-488a-a05a-64f3ed0e604d
62a9d698-4df2-488a-a05a-64f3ed0e604d
62a9d698-4df2-488a-a05a-64f3ed0e604d
human
null
null
none
abstracts
Copula Correlation: An Equitable Dependence Measure and Extension of Pearson's Correlation
null
In Science, Reshef et al. (2011) proposed the concept of equitability for measures of dependence between two random variables. To this end, they proposed a novel measure, the maximal information coefficient (MIC). Recently a PNAS paper (Kinney and Atwal, 2014) gave a mathematical definition for equitability. They pro...
a1d3e078-3981-4961-b58a-2c6d5fac8345
a1d3e078-3981-4961-b58a-2c6d5fac8345
a1d3e078-3981-4961-b58a-2c6d5fac8345
human
null
null
none
abstracts
Harmonic maps of finite uniton type into inner symmetric spaces
null
In this paper, we develop a loop group description of harmonic maps $\mathcal{F}: M \rightarrow G/K$ ``of finite uniton type", from a Riemann surface $M$ into inner symmetric spaces of compact or non-compact type. This develops work of Uhlenbeck, Segal, and Burstall-Guest to non-compact inner symmetric spaces. To be ...
97c9041b-25b0-49cf-8f47-58f1fe5ed38c
97c9041b-25b0-49cf-8f47-58f1fe5ed38c
97c9041b-25b0-49cf-8f47-58f1fe5ed38c
human
null
null
none
abstracts
Presupernova neutrinos: realistic emissivities from stellar evolution
null
We present a new calculation of neutrino emissivities and energy spectra from a massive star going through the advanced stages of nuclear burning (presupernova) in the months before becoming a supernova. The contributions from beta decay and electron capture, pair annihilation, plasmon decay, and the photoneutrino pr...
a0fc146e-35bb-4139-8bdd-6c74df7ff3a4
a0fc146e-35bb-4139-8bdd-6c74df7ff3a4
a0fc146e-35bb-4139-8bdd-6c74df7ff3a4
human
null
null
none
abstracts
A Framework for Non-Gaussian Functional Integrals with Applications
null
Functional integrals can be defined on topological groups in terms of families of locally compact topological groups and their associated Banach-valued Haar integrals. The definition forgoes the goal of constructing a genuine measure on a space of functions, and instead provides for a topological realization of local...
3f271786-6120-4b7f-9bab-3615e5ea24d7
3f271786-6120-4b7f-9bab-3615e5ea24d7
3f271786-6120-4b7f-9bab-3615e5ea24d7
human
null
null
none
abstracts
FPGA Based Data Read-Out System of the Belle 2 Pixel Detector
null
The upgrades of the Belle experiment and the KEKB accelerator aim to increase the data set of the experiment by the factor 50. This will be achieved by increasing the luminosity of the accelerator which requires a significant upgrade of the detector. A new pixel detector based on DEPFET technology will be installed t...
85e1cdd2-1f54-478c-bdd4-8f6bfd0cd0b4
85e1cdd2-1f54-478c-bdd4-8f6bfd0cd0b4
85e1cdd2-1f54-478c-bdd4-8f6bfd0cd0b4
human
null
null
none
abstracts
Noise reduction and hyperfine level coherence in spontaneous noise spectroscopy of atomic vapor
null
We develop a system for measurements of power spectra of transmitted light intensity fluctuations, in which the extraneous noise, including shot noise, is reduced. In essence, we just apply light, measure the power of the transmitted light and derive its power spectrum. We use this to observe the spontaneous noise sp...
31e8b9c1-bd31-4cd3-adf7-55968245bd6c
31e8b9c1-bd31-4cd3-adf7-55968245bd6c
31e8b9c1-bd31-4cd3-adf7-55968245bd6c
human
null
null
none
abstracts
Experimental Evidence Supporting a New "Osmosis Law & Theory" Derived New Formula that Improves van't Hoff Osmotic Pressure Equation
null
Experimental data were used to support a new concept of osmotic force and a new osmotic law that can explain the osmotic process without the difficulties encountered with van't Hoff osmotic pressure theory. Derived new osmotic formula with curvilinear equation (via new osmotic law) overcomes the limitations and incom...
da1956b4-7d83-46a7-a0f1-a5e6b1e966c5
da1956b4-7d83-46a7-a0f1-a5e6b1e966c5
da1956b4-7d83-46a7-a0f1-a5e6b1e966c5
human
null
null
none
abstracts
Femtosecond resolution timing jitter correction on a TW scale Ti:sapphire laser system for FEL pump-probe experiments
null
Intense ultrashort pulse lasers are used for fs resolution pumpprobe experiments more and more at large scale facilities, such as free electron lasers (FEL). Measurement of the arrival time of the laser pulses and stabilization to the machine or other sub-systems on the target, is crucial for high time-resolution mea...
b2a09e80-2df6-42bc-a5e4-4c5923927c70
b2a09e80-2df6-42bc-a5e4-4c5923927c70
b2a09e80-2df6-42bc-a5e4-4c5923927c70
human
null
null
none
abstracts
Sparsity and Parallel Acquisition: Optimal Uniform and Nonuniform Recovery Guarantees
null
The problem of multiple sensors simultaneously acquiring measurements of a single object can be found in many applications. In this paper, we present the optimal recovery guarantees for the recovery of compressible signals from multi-sensor measurements using compressed sensing. In the first half of the paper, we pre...
898b6636-9cd9-4461-be26-a773676619f6
898b6636-9cd9-4461-be26-a773676619f6
898b6636-9cd9-4461-be26-a773676619f6
human
null
null
none
abstracts
Analyzing Timed Systems Using Tree Automata
null
Timed systems, such as timed automata, are usually analyzed using their operational semantics on timed words. The classical region abstraction for timed automata reduces them to (untimed) finite state automata with the same time-abstract properties, such as state reachability. We propose a new technique to analyze su...
60831204-d729-421b-b559-3d5dfd26479c
60831204-d729-421b-b559-3d5dfd26479c
60831204-d729-421b-b559-3d5dfd26479c
human
null
null
none
abstracts
Defining implication relation for classical logic
null
In classical logic, "P implies Q" is equivalent to "not-P or Q". It is well known that the equivalence is problematic. Actually, from "P implies Q", "not-P or Q" can be inferred ("Implication-to-disjunction" is valid), while from "not-P or Q", "P implies Q" cannot be inferred in general ("Disjunction-to-implication" ...
df21a737-97ab-459c-a73b-5805a2494bac
df21a737-97ab-459c-a73b-5805a2494bac
df21a737-97ab-459c-a73b-5805a2494bac
human
null
null
none
abstracts
Most Complex Regular Ideal Languages
null
A right ideal (left ideal, two-sided ideal) is a non-empty language $L$ over an alphabet $\Sigma$ such that $L=L\Sigma^*$ ($L=\Sigma^*L$, $L=\Sigma^*L\Sigma^*$). Let $k=3$ for right ideals, 4 for left ideals and 5 for two-sided ideals. We show that there exist sequences ($L_n \mid n \ge k $) of right, left, and two-s...
f4d5ea1c-b951-482b-ac91-8b56c9834124
f4d5ea1c-b951-482b-ac91-8b56c9834124
f4d5ea1c-b951-482b-ac91-8b56c9834124
human
null
null
none
abstracts
Algebraic and logical descriptions of generalized trees
null
Quasi-trees generalize trees in that the unique "path" between two nodes may be infinite and have any countable order type. They are used to define the rank-width of a countable graph in such a way that it is equal to the least upper-bound of the rank-widths of its finite induced subgraphs. Join-trees are the corresp...
90ba909a-1986-450b-b156-f8e371772dc2
90ba909a-1986-450b-b156-f8e371772dc2
90ba909a-1986-450b-b156-f8e371772dc2
human
null
null
none
abstracts
Analysis of Fisher Information and the Cram\'{e}r-Rao Bound for Nonlinear Parameter Estimation after Compressed Sensing
null
In this paper, we analyze the impact of compressed sensing with complex random matrices on Fisher information and the Cram\'{e}r-Rao Bound (CRB) for estimating unknown parameters in the mean value function of a complex multivariate normal distribution. We consider the class of random compression matrices whose distri...
b2fcea6b-22f5-48f0-ab07-1c00fd48b8f0
b2fcea6b-22f5-48f0-ab07-1c00fd48b8f0
b2fcea6b-22f5-48f0-ab07-1c00fd48b8f0
human
null
null
none
abstracts
The $\pi$-Calculus is Behaviourally Complete and Orbit-Finitely Executable
null
Reactive Turing machines extend classical Turing machines with a facility to model observable interactive behaviour. We call a behaviour (finitely) executable if, and only if, it is equivalent to the behaviour of a (finite) reactive Turing machine. In this paper, we study the relationship between executable behaviour...
35e43de4-b951-4ff4-9974-c1706cc4b178
35e43de4-b951-4ff4-9974-c1706cc4b178
35e43de4-b951-4ff4-9974-c1706cc4b178
human
null
null
none
abstracts
Petersen cores and the oddness of cubic graphs
null
Let $G$ be a bridgeless cubic graph. Consider a list of $k$ 1-factors of $G$. Let $E_i$ be the set of edges contained in precisely $i$ members of the $k$ 1-factors. Let $\mu_k(G)$ be the smallest $|E_0|$ over all lists of $k$ 1-factors of $G$. If $G$ is not 3-edge-colorable, then $\mu_3(G) \geq 3$. In [E. Steffen, 1-...
b5e9b503-6ca3-4017-8eb7-ec2c77b1888b
b5e9b503-6ca3-4017-8eb7-ec2c77b1888b
b5e9b503-6ca3-4017-8eb7-ec2c77b1888b
human
null
null
none
abstracts
On homotopy invariants of combings of 3-manifolds
null
Combings of oriented compact 3-manifolds are homotopy classes of nowhere zero vector fields in these manifolds. A first known invariant of a combing is its Euler class, that is the Euler class of the normal bundle to a combing representative in the tangent bundle of the 3-manifold $M$. It only depends on the Spin$^c$...
e7368eaa-a7c3-4392-b61d-95472fc78115
e7368eaa-a7c3-4392-b61d-95472fc78115
e7368eaa-a7c3-4392-b61d-95472fc78115
human
null
null
none
abstracts
Graphs of Edge-Intersecting and Non-Splitting One Bend Paths in a Grid
null
The families EPT (resp. EPG) Edge Intersection Graphs of Paths in a tree (resp. in a grid) are well studied graph classes. Recently we introduced the graph classes Edge-Intersecting and Non-Splitting Paths in a Tree ENPT, and in a Grid (ENPG). It was shown that ENPG contains an infinite hierarchy of subclasses that a...
0257fafa-5675-4dc7-91a8-d29ef8b32e26
0257fafa-5675-4dc7-91a8-d29ef8b32e26
0257fafa-5675-4dc7-91a8-d29ef8b32e26
human
null
null
none
abstracts
Anomalously Robust Valley Polarization and Valley Coherence in Bilayer WS2
null
Coherence is a crucial requirement to realize quantum manipulation through light-matter interactions. Here we report the observation of anomalously robust valley polarization and valley coherence in bilayer WS2. The polarization of the photoluminescence from bilayer WS2 inherits that of the excitation source with bot...
a94fcac1-596b-4653-a746-e19849c01dd5
a94fcac1-596b-4653-a746-e19849c01dd5
a94fcac1-596b-4653-a746-e19849c01dd5
human
null
null
none
abstracts
Snow Leopard Permutations and Their Even and Odd Threads
null
Caffrey, Egge, Michel, Rubin and Ver Steegh recently introduced snow leopard permutations, which are the anti-Baxter permutations that are compatible with the doubly alternating Baxter permutations. Among other things, they showed that these permutations preserve parity, and that the number of snow leopard permutatio...
909795aa-53e6-48b7-be21-e9509f263a31
909795aa-53e6-48b7-be21-e9509f263a31
909795aa-53e6-48b7-be21-e9509f263a31
human
null
null
none
abstracts
Interval identification of FMR parameters for spin reorientation transition in (Ga,Mn)As
null
In this work we report results of ferromagnetic resonance studies of a 6% 15 nm (Ga,Mn)As layer, deposited on (001)-oriented GaAs. The measurements were performed with in-plane oriented magnetic field, in the temperature range between 5K and 120K. We observe a temperature induced reorientation of the effective in-pla...
749be9ce-4f8b-4e69-a05a-27d3730368da
749be9ce-4f8b-4e69-a05a-27d3730368da
749be9ce-4f8b-4e69-a05a-27d3730368da
human
null
null
none
abstracts
A generalised comparison principle for the Monge-Amp\`ere equation and the pressure in 2D fluid flows
null
We extend the generalised comparison principle for the Monge-Amp\`ere equation due to Rauch & Taylor (Rocky Mountain J. Math. 7, 1977) to nonconvex domains. From the generalised comparison principle we deduce bounds (from above and below) on solutions of the Monge-Amp\`ere equation with sign-changing right-hand side....
86484d14-c9f8-48f1-9335-45e90b944c97
86484d14-c9f8-48f1-9335-45e90b944c97
86484d14-c9f8-48f1-9335-45e90b944c97
human
null
null
none
abstracts
A Galois-dynamics correspondence for unicritical polynomials
null
In an analogy with the Galois homothety property for torsion points of abelian varieties that was used in the proof of the Mordell-Lang conjecture, we describe a correspondence between the action of a Galois group and the dynamical action of a rational map. For nonlinear polynomials with rational coefficients, the ir...
5ee089b2-f76f-4937-8124-a50e97cca937
5ee089b2-f76f-4937-8124-a50e97cca937
5ee089b2-f76f-4937-8124-a50e97cca937
human
null
null
none
abstracts
Positively deflected anomaly mediation in the light of the Higgs boson discovery
null
Anomaly-mediated supersymmetry breaking (AMSB) is a well-known mechanism for flavor-blind transmission of supersymmetry breaking from the hidden sector to the visible sector. However, the pure AMSB scenario suffers from a serious drawback, namely, the tachyonic slepton problem, and needs to be extended. The so-called...
79ecf2c6-7247-4fbf-9fba-fc8b2cc25f83
79ecf2c6-7247-4fbf-9fba-fc8b2cc25f83
79ecf2c6-7247-4fbf-9fba-fc8b2cc25f83
human
null
null
none
abstracts
Remote transfer of Gaussian quantum discord
null
Quantum discord quantifies quantum correlation between quantum systems, which has potential application in quantum information processing. In this paper, we propose a scheme realizing the remote transfer of Gaussian quantum discord, in which another quantum discordant state or an Einstein-Podolsky-Rosen entangled sta...
6229cf32-7026-477a-92a7-7e875ae06994
6229cf32-7026-477a-92a7-7e875ae06994
6229cf32-7026-477a-92a7-7e875ae06994
human
null
null
none
abstracts
Minimalist design of a robust real-time quantum random number generator
null
We present a simple and robust construction of a real-time quantum random number generator (QRNG). Our minimalist approach ensures stable operation of the device as well as its simple and straightforward hardware implementation as a stand-alone module. As a source of randomness the device uses measurements of time in...
85b78479-e917-4a67-8f3a-56b8ac43bd57
85b78479-e917-4a67-8f3a-56b8ac43bd57
85b78479-e917-4a67-8f3a-56b8ac43bd57
human
null
null
none
abstracts
Fast Solvers for Unsteady Thermal Fluid Structure Interaction
null
We consider time dependent thermal fluid structure interaction. The respective models are the compressible Navier-Stokes equations and the nonlinear heat equation. A partitioned coupling approach via a Dirichlet-Neumann method and a fixed point iteration is employed. As a refence solver a previously developed efficie...
ef2f4ac0-546f-4dc0-a07e-9fd37bd51dfb
ef2f4ac0-546f-4dc0-a07e-9fd37bd51dfb
ef2f4ac0-546f-4dc0-a07e-9fd37bd51dfb
human
null
null
none
abstracts
Impact of electrode density of states on transport through pyridine-linked single molecule junctions
null
We study the impact of electrode band structure on transport through single-molecule junctions by measuring the conductance of pyridine-based molecules using Ag and Au electrodes. Our experiments are carried out using the scanning tunneling microscope based break-junction technique and are supported by density functi...
7a0944e8-f2a5-4c82-87b5-232fcad14e61
7a0944e8-f2a5-4c82-87b5-232fcad14e61
7a0944e8-f2a5-4c82-87b5-232fcad14e61
human
null
null
none
abstracts
Quantitative Automata under Probabilistic Semantics
null
Automata with monitor counters, where the transitions do not depend on counter values, and nested weighted automata are two expressive automata-theoretic frameworks for quantitative properties. For a well-studied and wide class of quantitative functions, we establish that automata with monitor counters and nested wei...
064f466c-9fd4-442b-9f0d-105eb023214f
064f466c-9fd4-442b-9f0d-105eb023214f
064f466c-9fd4-442b-9f0d-105eb023214f
human
null
null
none
abstracts
Solving the Crystallographic Phase Problem using Dynamical Scattering in Electron Diffraction
null
Solving crystal structures from kinematical X-ray or electron diffraction patterns of single crystals requires many more diffracted beams to be recorded than there are atoms in the structure, since the phases of the structure factors can only be retrieved from such data if the atoms can be resolved as sharply peaked ...
b47fe644-edfe-4c59-9bb7-21fd35d526c7
b47fe644-edfe-4c59-9bb7-21fd35d526c7
b47fe644-edfe-4c59-9bb7-21fd35d526c7
human
null
null
none
abstracts
Operational Concurrency Control in the Face of Arbitrary Scale and Latency
null
We present for the first time a complete solution to the problem of proving the correctness of a concurrency control algorithm for collaborative text editors against the standard consistency model. The success of our approach stems from the use of comprehensive stringwise operational transformations, which appear to ...
3eb80403-4158-42dd-8a9a-e5157c77be3f
3eb80403-4158-42dd-8a9a-e5157c77be3f
3eb80403-4158-42dd-8a9a-e5157c77be3f
human
null
null
none
abstracts
A Demonstration of Spectral Level Reconstruction of Intrinsic $B$-mode Power
null
We investigate the prospects and consequences of the spectral level reconstruction of primordial $B$-mode power by solving the systems of linear equations assuming that the lensing potential together with the lensed polarization spectra are already in hand. We find that this reconstruction technique may be very usefu...
ab094ddc-e98e-47f6-887c-5395c56a5bf0
ab094ddc-e98e-47f6-887c-5395c56a5bf0
ab094ddc-e98e-47f6-887c-5395c56a5bf0
human
null
null
none
abstracts
A Universal Parallel Two-Pass MDL Context Tree Compression Algorithm
null
Computing problems that handle large amounts of data necessitate the use of lossless data compression for efficient storage and transmission. We present a novel lossless universal data compression algorithm that uses parallel computational units to increase the throughput. The length-$N$ input sequence is partitioned...
c1d1f89f-6fab-486a-93a1-5d06f4fcedf1
c1d1f89f-6fab-486a-93a1-5d06f4fcedf1
c1d1f89f-6fab-486a-93a1-5d06f4fcedf1
human
null
null
none
abstracts
Multicell Coordinated Beamforming with Rate Outage Constraint--Part II: Efficient Approximation Algorithms
null
This paper studies the coordinated beamforming (CoBF) design for the multiple-input single-output interference channel, provided that only channel distribution information is known to the transmitters. The problem under consideration is a probabilistically constrained optimization problem which maximizes a predefined...
30c90b06-1b85-4df9-8f8b-b1336b0da6ff
30c90b06-1b85-4df9-8f8b-b1336b0da6ff
30c90b06-1b85-4df9-8f8b-b1336b0da6ff
human
null
null
none
abstracts
Analyzing sparse dictionaries for online learning with kernels
null
Many signal processing and machine learning methods share essentially the same linear-in-the-parameter model, with as many parameters as available samples as in kernel-based machines. Sparse approximation is essential in many disciplines, with new challenges emerging in online learning with kernels. To this end, seve...
24d1869e-7eb9-47df-95ab-559549c3b8b3
24d1869e-7eb9-47df-95ab-559549c3b8b3
24d1869e-7eb9-47df-95ab-559549c3b8b3
human
null
null
none
abstracts
Similar submodules and coincidence site modules
null
We consider connections between similar sublattices and coincidence site lattices (CSLs), and more generally between similar submodules and coincidence site modules of general (free) $\mathbb{Z}$-modules in $\mathbb{R}^d$. In particular, we generalise results obtained by S. Glied and M. Baake [1,2] on similarity an...
5ca598f9-77fd-4317-b7ad-6cec20c8e51e
5ca598f9-77fd-4317-b7ad-6cec20c8e51e
5ca598f9-77fd-4317-b7ad-6cec20c8e51e
human
null
null
none
abstracts
Residual Amplitude Modulation in Interferometric Gravitational Wave Detectors
null
The effects of residual amplitude modulation (RAM) in laser interferometers using heterodyne sensing can be substantial and difficult to mitigate. In this work, we analyze the effects of RAM on a complex laser interferometer used for gravitational wave detection. The RAM introduces unwanted offsets in the cavity leng...
7e134c6f-bb25-4cf2-b274-5f288af3209e
7e134c6f-bb25-4cf2-b274-5f288af3209e
7e134c6f-bb25-4cf2-b274-5f288af3209e
human
null
null
none
abstracts
A Large Scale Pattern from Optical Quasar Polarization Vectors
null
The 355 optically polarized QSOs have redshifts from 0.061 to 3.94 and are spread out over the sky except for a 60 degree band centered on the Galactic Equator. The data we analyze was measured, collected and published by others. Here, we apply tests suitable for large-scale samples and find that the polarization dir...
b8249d5a-52e4-4f91-9ce6-8cb6c7d70e71
b8249d5a-52e4-4f91-9ce6-8cb6c7d70e71
b8249d5a-52e4-4f91-9ce6-8cb6c7d70e71
human
null
null
none
abstracts
A Framework for Certified Self-Stabilization
null
We propose a general framework to build certified proofs of distributed self-stabilizing algorithms with the proof assistant Coq. We first define in Coq the locally shared memory model with composite atomicity, the most commonly used model in the self-stabilizing area. We then validate our framework by certifying a n...
0cfff216-72b5-4897-92ea-4bb3a85e8967
0cfff216-72b5-4897-92ea-4bb3a85e8967
0cfff216-72b5-4897-92ea-4bb3a85e8967
human
null
null
none
abstracts
Irreversible 2-conversion set in graphs of bounded degree
null
An irreversible $k$-threshold process (also a $k$-neighbor bootstrap percolation) is a dynamic process on a graph where vertices change color from white to black if they have at least $k$ black neighbors. An irreversible $k$-conversion set of a graph $G$ is a subset $S$ of vertices of $G$ such that the irreversible $...
7024dcad-779f-49d6-8b37-469fa4e6666a
7024dcad-779f-49d6-8b37-469fa4e6666a
7024dcad-779f-49d6-8b37-469fa4e6666a
human
null
null
none
abstracts
Discrete and Continuous-time Soft-Thresholding with Dynamic Inputs
null
There exist many well-established techniques to recover sparse signals from compressed measurements with known performance guarantees in the static case. However, only a few methods have been proposed to tackle the recovery of time-varying signals, and even fewer benefit from a theoretical analysis. In this paper, we...
ad7cc68e-e486-4e98-9bba-bfc51931edc3
ad7cc68e-e486-4e98-9bba-bfc51931edc3
ad7cc68e-e486-4e98-9bba-bfc51931edc3
human
null
null
none
abstracts
Who Can Win a Single-Elimination Tournament?
null
A single-elimination (SE) tournament is a popular way to select a winner in both sports competitions and in elections. A natural and well-studied question is the tournament fixing problem (TFP): given the set of all pairwise match outcomes, can a tournament organizer rig an SE tournament by adjusting the initial seed...
f44b18d2-a324-4798-9b17-81df038cef9b
f44b18d2-a324-4798-9b17-81df038cef9b
f44b18d2-a324-4798-9b17-81df038cef9b
human
null
null
none
abstracts
Collaborative sparse regression using spatially correlated supports - Application to hyperspectral unmixing
null
This paper presents a new Bayesian collaborative sparse regression method for linear unmixing of hyperspectral images. Our contribution is twofold; first, we propose a new Bayesian model for structured sparse regression in which the supports of the sparse abundance vectors are a priori spatially correlated across pix...
11ad7099-7db8-4014-af2d-9652ef0f7876
11ad7099-7db8-4014-af2d-9652ef0f7876
11ad7099-7db8-4014-af2d-9652ef0f7876
human
null
null
none
abstracts
Van der Waals density-functional theory study for bulk solids with BCC, FCC, and diamond structures
null
Proper inclusion of van der Waals (vdW) interactions in theoretical simulations based on standard density functional theory (DFT) is crucial to describe the physics and chemistry of systems such as organic and layered materials. Many encouraging approaches have been proposed to combine vdW interactions with standard ...
871ae8c7-ec54-4eed-b654-17812828bbe4
871ae8c7-ec54-4eed-b654-17812828bbe4
871ae8c7-ec54-4eed-b654-17812828bbe4
human
null
null
none
abstracts
Weighted Sobolev Spaces on Metric Measure Spaces
null
We investigate weighted Sobolev spaces on metric measure spaces $(X,d,m)$. Denoting by $\rho$ the weight function, we compare the space $W^{1,p}(X,d,\rho m)$ (which always concides with the closure $H^{1,p}(X,d,\rho m)$ of Lipschitz functions) with the weighted Sobolev spaces $W^{1,p}_\rho(X,d,m)$ and $H^{1,p}_\rho(X...