justin

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

Today I read a paper titled “The effects of computer assisted and distance learning of geometric modelling”

The abstract is:
The effects of computer-assisted and distance learning of geometric modeling and computer aided geometric design are studied

It was shown that computer algebra systems and dynamic geometric environments can be considered as excellent tools for teaching mathematical concepts of mentioned areas, and distance education technologies would be indispensable for consolidation of successfully passed topics

Today I read a paper titled “Parsimonious Flooding in Geometric Random-Walks”

The abstract is:
We study the information spreading yielded by the Parsimonious-Flooding Protocol in geometric Mobile Ad-Hoc Networks

We consider $n$ agents on a convex plane region of diameter $D$ performing independent random walks with move radius $\rho$

At any time step, every active agent $v$ informs every non-informed agent which is within distance $R$ from $v$ ($R>0$ is the transmission radius)

An agent is only active at the time step immediately after the one in which has been informed and, after that, she is removed

At the initial time step, a source agent is informed and we look at the completion time of the protocol, i.e., the first time step (if any) in which all agents are informed

This random process is equivalent to the well-known Susceptible-Infective-Removed (SIR) infection process in Mathematical Epidemiology

No analytical results are available for this random process over any explicit mobility model

The presence of removed agents makes this process much more complex than the (standard) flooding

We prove optimal bounds on the completion time depending on the parameters $n$, $D$, $R$, and $\rho$

The obtained bounds hold with high probability

We remark that our method of analysis provides a clear picture of the dynamic shape of the information spreading (or infection wave) over the time

Today I read a paper titled “Writer Identification Using Inexpensive Signal Processing Techniques”

The abstract is:
We propose to use novel and classical audio and text signal-processing and otherwise techniques for “inexpensive” fast writer identification tasks of scanned hand-written documents “visually”

The “inexpensive” refers to the efficiency of the identification process in terms of CPU cycles while preserving decent accuracy for preliminary identification

This is a comparative study of multiple algorithm combinations in a pattern recognition pipeline implemented in Java around an open-source Modular Audio Recognition Framework (MARF) that can do a lot more beyond audio

We present our preliminary experimental findings in such an identification task

We simulate “visual” identification by “looking” at the hand-written document as a whole rather than trying to extract fine-grained features out of it prior classification

Today I read a paper titled “Experimental evidence for mixed reality states”

The abstract is:
Recently researchers at the University of Illinois coupled a real pendulum to its virtual counterpart

They observed that the two pendulums suddenly start to move in synchrony if their lengths are sufficiently close

In this synchronized state, the boundary between the real system and the virtual system is blurred, that is, the pendulums are in a mixed reality state

An instantaneous, bidirectional coupling is a prerequisite for mixed reality states

In this article we explore the implications of mixed reality states in the context of controlling real-world systems

Today I read a paper titled “Dynamic Simulation of Soft Heterogeneous Objects”

The abstract is:
This paper describes a 2D and 3D simulation engine that quantitatively models the statics, dynamics, and non-linear deformation of heterogeneous soft bodies in a computationally efficient manner

There is a large body of work simulating compliant mechanisms

These normally assume small deformations with homogeneous material properties actuated with external forces

There is also a large body of research on physically-based deformable objects for applications in computer graphics with the purpose of generating realistic appearances at the expense of accuracy

Here we present a simulation framework in which an object may be composed of any number of interspersed materials with varying properties (stiffness, density, etc.) to enable true heterogeneous multi-material simulation

Collisions are handled to prevent self-penetration due to large deformation, which also allows multiple bodies to interact

A volumetric actuation method is implemented to impart motion to the structures which opens the door to the design of novel structures and mechanisms

The simulator was implemented efficiently such that objects with thousands of degrees of freedom can be simulated at suitable framerates for user interaction using a single thread of a typical desktop computer

The code is written in platform agnostic C++ and is fully open source

This research opens the door to the dynamic simulation of freeform 3D multi-material mechanisms and objects in a manner suitable for design automation

Today I read a paper titled “WoodTouch, a new interaction interface for wooden furniture”

The abstract is:
If wood has been with us since time immemorial, being part of our environment, housing and tools, now wood has gain momentum, as it is clear that wood improves our life style

Because of the healthiness, resistance, ecology and comfort, wood is important for all of us, no matter what our life style is

WOODTOUCH Project aims to open a completely new market for furniture and interior design companies, enabling touch interaction between the user and wooden furniture surfaces

Why not switch on or dim the lights touching a wooden table? Why not turn on the heating system? Why not use wood as a touch sensitive surface for domotic control? The furniture designed with this novel technology, offers a wooden outer image and has different touch sensitive areas over the ones the user is able to control all sorts of electric appliances touching over a wooden surface