Archives for 2014

Today I read a paper titled “Visualizing Flat Spacetime: Viewing Optical versus Special Relativistic Effects”

The abstract is:
A simple visual representation of Minkowski spacetime appropriate for a student with a background in geometry and algebra is presented

Minkowski spacetime can be modeled with a Euclidean 4-space to yield accurate visualizations as predicted by special relativity theory

The contributions of relativistic aberration as compared to classical pre-relativistic aberration to the geometry are discussed in the context of its visual representation

Today I read a paper titled “Percolation in networks composed of connectivity and dependency links”

The abstract is:
Networks composed from both connectivity and dependency links were found to be more vulnerable compared to classical networks with only connectivity links

Their percolation transition is usually of a first order compared to the second order transition found in classical networks

We analytically analyze the effect of different distributions of dependencies links on the robustness of networks

For networks with Gaussian distribution of dependency links we show how the average and width of the distribution affect the robustness of the networks

Today I read a paper titled “Nano-scale reservoir computing”

The abstract is:
This work describes preliminary steps towards nano-scale reservoir computing using quantum dots

Our research has focused on the development of an accumulator-based sensing system that reacts to changes in the environment, as well as the development of a software simulation

The investigated systems generate nonlinear responses to inputs that make them suitable for a physical implementation of a neural network

This development will enable miniaturisation of the neurons to the molecular level, leading to a range of applications including monitoring of changes in materials or structures

The system is based around the optical properties of quantum dots

The paper will report on experimental work on systems using Cadmium Selenide (CdSe) quantum dots and on the various methods to render the systems sensitive to pH, redox potential or specific ion concentration

Once the quantum dot-based systems are rendered sensitive to these triggers they can provide a distributed array that can monitor and transmit information on changes within the material

Today I read a paper titled “Geodesics in Heat”

The abstract is:
We introduce the heat method for computing the shortest geodesic distance to a specified subset (e.g., point or curve) of a given domain

The heat method is robust, efficient, and simple to implement since it is based on solving a pair of standard linear elliptic problems

The method represents a significant breakthrough in the practical computation of distance on a wide variety of geometric domains, since the resulting linear systems can be prefactored once and subsequently solved in near-linear time

In practice, distance can be updated via the heat method an order of magnitude faster than with state-of-the-art methods while maintaining a comparable level of accuracy

We provide numerical evidence that the method converges to the exact geodesic distance in the limit of refinement; we also explore smoothed approximations of distance suitable for applications where more regularity is required

Today I read a paper titled “Memory Based Machine Intelligence Techniques in VLSI hardware”

The abstract is:
We briefly introduce the memory based approaches to emulate machine intelligence in VLSI hardware, describing the challenges and advantages

Implementation of artificial intelligence techniques in VLSI hardware is a practical and difficult problem

Deep architectures, hierarchical temporal memories and memory networks are some of the contemporary approaches in this area of research

The techniques attempt to emulate low level intelligence tasks and aim at providing scalable solutions to high level intelligence problems such as sparse coding and contextual processing

Today I read a paper titled “Augmented Reality in Astrophysics”

The abstract is:
Augmented Reality consists of merging live images with virtual layers of information

The rapid growth in the popularity of smartphones and tablets over recent years has provided a large base of potential users of Augmented Reality technology, and virtual layers of information can now be attached to a wide variety of physical objects

In this article, we explore the potential of Augmented Reality for astrophysical research with two distinct experiments: (1) Augmented Posters and (2) Augmented Articles

We demonstrate that the emerging technology of Augmented Reality can already be used and implemented without expert knowledge using currently available apps

Our experiments highlight the potential of Augmented Reality to improve the communication of scientific results in the field of astrophysics

We also present feedback gathered from the Australian astrophysics community that reveals evidence of some interest in this technology by astronomers who experimented with Augmented Posters

In addition, we discuss possible future trends for Augmented Reality applications in astrophysics, and explore the current limitations associated with the technology

This Augmented Article, the first of its kind, is designed to allow the reader to directly experiment with this technology

Today I read a paper titled “Community Detection in Networks: The Leader-Follower Algorithm”

The abstract is:
Traditional spectral clustering methods cannot naturally learn the number of communities in a network and often fail to detect smaller community structure in dense networks because they are based upon external community connectivity properties such as graph cuts

We propose an algorithm for detecting community structure in networks called the leader-follower algorithm which is based upon the natural internal structure expected of communities in social networks

The algorithm uses the notion of network centrality in a novel manner to differentiate leaders (nodes which connect different communities) from loyal followers (nodes which only have neighbors within a single community)

Using this approach, it is able to naturally learn the communities from the network structure and does not require the number of communities as an input, in contrast to other common methods such as spectral clustering

We prove that it will detect all of the communities exactly for any network possessing communities with the natural internal structure expected in social networks

More importantly, we demonstrate the effectiveness of the leader-follower algorithm in the context of various real networks ranging from social networks such as Facebook to biological networks such as an fMRI based human brain network

We find that the leader-follower algorithm finds the relevant community structure in these networks without knowing the number of communities beforehand

Also, because the leader-follower algorithm detects communities using their internal structure, we find that it can resolve a finer community structure in dense networks than common spectral clustering methods based on external community structure

Today I read a paper titled “Physical Modeling Techniques in Active Contours for Image Segmentation”

The abstract is:
Physical modeling method, represented by simulation and visualization of the principles in physics, is introduced in the shape extraction of the active contours

The objectives of adopting this concept are to address the several major difficulties in the application of Active Contours

Primarily, a technique is developed to realize the topological changes of Parametric Active Contours (Snakes)

The key strategy is to imitate the process of a balloon expanding and filling in a closed space with several objects

After removing the touched balloon surfaces, the objects can be identified by surrounded remaining balloon surfaces

A burned region swept by Snakes is utilized to trace the contour and to give a criterion for stopping the movement of Snake curve

When the Snakes terminates evolution totally, through ignoring this criterion, it can form a connected area by evolving the Snakes again and continuing the region burning

The contours extracted from the boundaries of the burned area can represent the child snake of each object respectively

Secondly, a novel scheme is designed to solve the problems of leakage of the contour from the large gaps, and the segmentation error in Geometric Active Contours (GAC)

It divides the segmentation procedure into two processing stages

By simulating the wave propagating in the isotropic substance at the final stage, it can significantly enhance the effect of image force in GAC based on Level Set and give the satisfied solutions to the two problems

Thirdly, to support the physical models for active contours above, we introduce a general image force field created on a template plane over the image plane

This force is more adaptable to noisy images with complicated geometric shapes

Today I read a paper titled “Labeling 3D scenes for Personal Assistant Robots”

The abstract is:
Inexpensive RGB-D cameras that give an RGB image together with depth data have become widely available

We use this data to build 3D point clouds of a full scene

In this paper, we address the task of labeling objects in this 3D point cloud of a complete indoor scene such as an office

We propose a graphical model that captures various features and contextual relations, including the local visual appearance and shape cues, object co-occurrence relationships and geometric relationships

With a large number of object classes and relations, the model’s parsimony becomes important and we address that by using multiple types of edge potentials

The model admits efficient approximate inference, and we train it using a maximum-margin learning approach

In our experiments over a total of 52 3D scenes of homes and offices (composed from about 550 views, having 2495 segments labeled with 27 object classes), we get a performance of 84.06% in labeling 17 object classes for offices, and 73.38% in labeling 17 object classes for home scenes

Finally, we applied these algorithms successfully on a mobile robot for the task of finding an object in a large cluttered room