justin

Today I read a paper titled “A basic gesture and motion format for virtual reality multisensory applications”

The abstract is:
The question of encoding movements such as those produced by human gestures may become central in the coming years, given the growing importance of movement data exchanges between heterogeneous systems and applications (musical applications, 3D motion control, virtual reality interaction, etc.)

For the past 20 years, various formats have been proposed for encoding movement, especially gestures

Though, these formats, at different degrees, were designed in the context of quite specific applications (character animation, motion capture, musical gesture, biomechanical concerns…)

The article introduce a new file format, called GMS (for ‘Gesture and Motion Signal’), with the aim of being more low-level and generic, by defining the minimal features a format carrying movement/gesture information needs, rather than by gathering all the information generally given by the existing formats

The article argues that, given its growing presence in virtual reality situations, the “gesture signal” itself must be encoded, and that a specific format is needed

The proposed format features the inner properties of such signals: dimensionality, structural features, types of variables, and spatial and temporal properties

The article first reviews the various situations with multisensory virtual objects in which gesture controls intervene

The proposed format is then deduced, as a mean to encode such versatile and variable “gestural and animated scene”

Today I read a paper titled “Heterogenous scaling in interevent time of on-line bookmarking”

The abstract is:
In this paper, we study the statistical properties of bookmarking behaviors in Delicious.com

We find that the interevent time distributions of bookmarking decays powerlike as interevent time increases at both individual and population level

Remarkably, we observe a significant change in the exponent when interevent time increases from intra-day to inter-day range

In addition, dependence of exponent on individual Activity is found to be different in the two ranges

These results suggests that mechanisms driving human actions are different in intra- and inter-day range

Instead of monotonically increasing with Activity, we find that inter-day exponent peaks at value around 3

We further show that less active users are more likely to resemble poisson process in bookmarking

Based on the temporal-preference model, preliminary explanations for this dependence have been given

Finally, a universal behavior in inter-day scale is observed by considering the rescaled variable

Today I read a paper titled “A self-rendering digital image encoding”

The abstract is:
Without careful long-term preservation digital data may be lost to a number of factors, including physical media decay, lack of suitable decoding equipment, and the absence of software

When raw data can be read but lack suitable annotations as to provenance, the ability to interpret them is more straightforward if they can be assessed through simple visual techniques

In this regard digital images are a special case since their data have a natural representation on two-dimensional media surfaces

This paper presents a novel binary image pixel encoding that produces an approximate analog rendering of encoded images when the image bits are arranged spatially in an appropriate manner

This simultaneous digital and analog representation acts to inseparably annotate bits as image data, which may contribute to the longevity of so-encoded images

Today I read a paper titled “Measuring the Hierarchy of Feedforward Networks”

The abstract is:
In this paper we explore the concept of hierarchy as a quantifiable descriptor of ordered structures, departing from the definition of three conditions to be satisfied for a hierarchical structure: order, predictability and pyramidal structure

According to these principles we define a hierarchical index taking concepts from graph and information theory

This estimator allows to quantify the hierarchical character of any system susceptible to be abstracted in a feedforward causal graph, i.e., a directed acyclic graph defined in a single connected structure

Our hierarchical index is a balance between this predictability and pyramidal condition by the definition of two entropies: one attending the onward flow and other for the backward reversion

We show how this index allows to identify hierarchical, anti-hierarchical and non hierarchical structures

Our formalism reveals that departing from the defined conditions for a hierarchical structure, feedforward trees and the inverted tree graphs emerge as the only causal structures of maximal hierarchical and anti-hierarchical systems, respectively

Conversely, null values of the hierarchical index are attributed to a number of different configuration networks; from linear chains, due to their lack of pyramid structure, to full-connected feedforward graphs where the diversity of onward pathways is canceled by the uncertainty (lack of predictability) when going backwards

Some illustrative examples are provided for the distinction among these three types of hierarchical causal graphs

Today I read a paper titled “Towards plant wires”

The abstract is:
In experimental laboratory studies we evaluate a possibility of making electrical wires from living plants

In scoping experiments we use lettuce seedlings as a prototype model of a plant wire

We approximate an electrical potential transfer function by applying direct current voltage to the lettuce seedlings and recording output voltage

We analyse oscillation frequencies of the output potential and assess noise immunity of the plant wires

Our findings will be used in future designs of self-growing wetware circuits and devices, and integration of plant-based electronic components into future and emergent bio-hybrid systems

Today I read a paper titled “Path lengths, correlations, and centrality in temporal networks”

The abstract is:
In temporal networks, where nodes interact via sequences of temporary events, information or resources can only flow through paths that follow the time-ordering of events

Such temporal paths play a crucial role in dynamic processes

However, since networks have so far been usually considered static or quasi-static, the properties of temporal paths are not yet well understood

Building on a definition and algorithmic implementation of the average temporal distance between nodes, we study temporal paths in empirical networks of human communication and air transport

Although temporal distances correlate with static graph distances, there is a large spread, and nodes that appear close from the static network view may be connected via slow paths or not at all

Differences between static and temporal properties are further highlighted in studies of the temporal closeness centrality

In addition, correlations and heterogeneities in the underlying event sequences affect temporal path lengths, increasing temporal distances in communication networks and decreasing them in the air transport network

Today I read a paper titled “Thinking like Archimedes with a 3D printer”

The abstract is:
We illustrate Archimedes’ method using models produced with 3D printers

This approach allowed us to create physical proofs of results known to Archimedes and illustrate ideas of a mathematician who is known both for his for his mechanical inventions as well as his breakthroughs in geometry and calculus

We use technology from the 21st century to trace intellectual achievements from the 3rd century BC

While we celebrate the 2300th birthday of Archimedes (287-212 BC) in 2013, we also live in an exciting time, where 3D printing is becoming popular and affordable

Today I read a paper titled “A Novel Algorithm for Real-time Procedural Generation of Building Floor Plans”

The abstract is:
Real-time generation of natural-looking floor plans is vital in games with dynamic environments

This paper presents an algorithm to generate suburban house floor plans in real-time

The algorithm is based on the work presented in [1]

However, the corridor placement is redesigned to produce floor plans similar to real houses

Moreover, an optimization stage is added to find a corridor placement with the minimum used space, an approach that is designed to mimic the real-life practices to minimize the wasted spaces in the design

The results show very similar floor plans to the ones designed by an architect

Today I read a paper titled “Logging safely in public spaces using color PINs”

The abstract is:
Nowadays, we are increasingly logging on many different Internet sites to access private data like emails or photos remotely stored in the clouds

This makes us all the more concerned with digital identity theft and passwords being stolen either by key loggers or shoulder-surfing attacks

Quite surprisingly, the current bottleneck of computer security when logging for authentication is the User Interface (UI): How can we enter safely secret passwords when concealed spy cameras or key loggers may be recording the login session? Logging safely requires to design a secure Human Computer Interface (HCI) robust to those attacks

We describe a novel method and system based on entering secret ID passwords by means of associative secret UI passwords that provides zero-knowledge to observers

We demonstrate the principles using a color Personal Identification Numbers (PINs) login system and describes its various extensions

Today I read a paper titled “Finding statistically significant communities in networks”

The abstract is:
Community structure is one of the main structural features of networks, revealing both their internal organization and the similarity of their elementary units

Despite the large variety of methods proposed to detect communities in graphs, there is a big need for multi-purpose techniques, able to handle different types of datasets and the subtleties of community structure

In this paper we present OSLOM (Order Statistics Local Optimization Method), the first method capable to detect clusters in networks accounting for edge directions, edge weights, overlapping communities, hierarchies and community dynamics

It is based on the local optimization of a fitness function expressing the statistical significance of clusters with respect to random fluctuations, which is estimated with tools of Extreme and Order Statistics

OSLOM can be used alone or as a refinement procedure of partitions/covers delivered by other techniques

We have also implemented sequential algorithms combining OSLOM with other fast techniques, so that the community structure of very large networks can be uncovered

Our method has a comparable performance as the best existing algorithms on artificial benchmark graphs

Several applications on real networks are shown as well

OSLOM is implemented in a freely available software (this http URL), and we believe it will be a valuable tool in the analysis of networks

Today I read a paper titled “Detecting Important Nodes to Community Structure Using the Spectrum of the Graph”

The abstract is:
Many complex systems can be represented as networks, and how a network breaks up into subnetworks or communities is of wide interest

However, the development of a method to detect nodes important to communities that is both fast and accurate is a very challenging and open problem

In this manuscript, we introduce a new approach to characterize the node importance to communities

First, a centrality metric is proposed to measure the importance of network nodes to community structure using the spectrum of the adjacency matrix

We define the node importance to communities as the relative change in the eigenvalues of the network adjacency matrix upon their removal

Second, we also propose an index to distinguish two kinds of important nodes in communities, i.e., “community core” and “bridge”

Our indices are only relied on the spectrum of the graph matrix

They are applied in many artificial networks as well as many real-world networks

This new methodology gives us a basic approach to solve this challenging problem and provides a realistic result

Today I read a paper titled “Survey on Various Gesture Recognition Techniques for Interfacing Machines Based on Ambient Intelligence”

The abstract is:
Gesture recognition is mainly apprehensive on analyzing the functionality of human wits

The main goal of gesture recognition is to create a system which can recognize specific human gestures and use them to convey information or for device control

Hand gestures provide a separate complementary modality to speech for expressing ones ideas

Information associated with hand gestures in a conversation is degree,discourse structure, spatial and temporal structure

The approaches present can be mainly divided into Data-Glove Based and Vision Based approaches

An important face feature point is the nose tip

Since nose is the highest protruding point from the face

Besides that, it is not affected by facial expressions.Another important function of the nose is that it is able to indicate the head pose

Knowledge of the nose location will enable us to align an unknown 3D face with those in a face database

Eye detection is divided into eye position detection and eye contour detection

Existing works in eye detection can be classified into two major categories: traditional image-based passive approaches and the active IR based approaches

The former uses intensity and shape of eyes for detection and the latter works on the assumption that eyes have a reflection under near IR illumination and produce bright/dark pupil effect

The traditional methods can be broadly classified into three categories: template based methods,appearance based methods and feature based methods

The purpose of this paper is to compare various human Gesture recognition systems for interfacing machines directly to human wits without any corporeal media in an ambient environment

Today I read a paper titled “Irrelevance of information outflow in opinion dynamics models”

The abstract is:
The Sznajd model for opinion dynamics has attracted a large interest as a simple realization of the psychological principle of social validation

As its most salient feature, it has been claimed that the Sznajd model is qualitatively different from other ordering processes, because it is the only one featuring outflow of information as opposed to inflow

We show that this claim is unfounded by presenting a generalized zero-temperature Glauber-type of dynamics which yields results indistinguishable from those of the Sznajd model

In one-dimension we also derive an exact expression for the exit probability of the Sznajd model, that turns out to coincide with the result of an analytical approach based on the Kirkwood approximation

This observation raises interesting questions about the applicability and limitations of this approach

Today I read a paper titled “Mining User Comment Activity for Detecting Forum Spammers in YouTube”

The abstract is:
Research shows that comment spamming (comments which are unsolicited, unrelated, abusive, hateful, commercial advertisements etc) in online discussion forums has become a common phenomenon in Web 2.0 applications and there is a strong need to counter or combat comment spamming

We present a method to automatically detect comment spammer in YouTube (largest and a popular video sharing website) forums

The proposed technique is based on mining comment activity log of a user and extracting patterns (such as time interval between subsequent comments, presence of exactly same comment across multiple unrelated videos) indicating spam behavior

We perform empirical analysis on data crawled from YouTube and demonstrate that the proposed method is effective for the task of comment spammer detection

Today I read a paper titled “Physically-based particle simulation and visualization of pastes and gels”

The abstract is:
This paper is focused on the question of simulation and visualiza- tion of 3D gel and paste dynamic effects

In a first part, we introduce a 3D physically based particle (or mass-interaction) model, with a small number of masses and few powerful interaction parameters, which is able to generate the dynamic features of both gels and pastes

This model proves that the 3D mass-interaction method is relevant for the simulation of such phenomena, without an explicit knowledge of their underly- ing physics

In a second part, we expose an original rendering process, the Flow Structuring Method that enhances the dynamic properties of the simulation and offers a realistic visualization

This process ignores all the properties of the underlying physical model

It leads to a reconstruction of the spatial structure of the gel (or paste) flow only through an analysis of the output of the simula- tion which is a set of unorganized points moving in a 3D space

Finally, the paper presents realistic renderings obtained by using implicit surfaces and ray-tracing techniques on the Structured Flow previously obtained

Today I read a paper titled “Noise in Naming Games, partial synchronization and community detection in social networks”

The abstract is:
The Naming Games (NG) are agent-based models for agreement dynamics, peer pressure and herding in social networks, and protocol selection in autonomous ad-hoc sensor networks

By introducing a small noise term to the NG, the resulting Markov Chain model called Noisy Naming Games (NNG) are ergodic, in which all partial consensus states are recurrent

By using Gibbs-Markov equivalence we show how to get the NNG’s stationary distribution in terms of the local specification of a related Markov Random Field (MRF)

By ordering the partially-synchronized states according to their Gibbs energy, taken here to be a good measure of social tension, this method offers an enhanced method for community-detection in social interaction data

We show how the lowest Gibbs energy multi-name states separate and display the hidden community structures within a social network

Today I read a paper titled “Computation of the Travelling Salesman Problem by a Shrinking Blob”

The abstract is:
The Travelling Salesman Problem (TSP) is a well known and challenging combinatorial optimisation problem

Its computational intractability has attracted a number of heuristic approaches to generate satisfactory, if not optimal, candidate solutions

In this paper we demonstrate a simple unconventional computation method to approximate the Euclidean TSP using a virtual material approach

The morphological adaptation behaviour of the material emerges from the low-level interactions of a population of particles moving within a diffusive lattice

A `blob’ of this material is placed over a set of data points projected into the lattice, representing TSP city locations, and the blob is reduced in size over time

As the blob shrinks it morphologically adapts to the configuration of the cities

The shrinkage process automatically stops when the blob no longer completely covers all cities

By manually tracing the perimeter of the blob a path between cities is elicited corresponding to a TSP tour

Over 6 runs on 20 randomly generated datasets of 20 cities this simple and unguided method found tours with a mean best tour length of 1.04, mean average tour length of 1.07 and mean worst tour length of 1.09 when expressed as a fraction of the minimal tour computed by an exact TSP solver

We examine the insertion mechanism by which the blob constructs a tour, note some properties and limitations of its performance, and discuss the relationship between the blob TSP and proximity graphs which group points on the plane

The method is notable for its simplicity and the spatially represented mechanical mode of its operation

We discuss similarities between this method and previously suggested models of human performance on the TSP and suggest possibilities for further improvement

Today I read a paper titled “Injectivity of 2D Toric Bézier Patches”

The abstract is:
Rational Bezier functions are widely used as mapping functions in surface reparameterization, finite element analysis, image warping and morphing

The injectivity (one-to-one property) of a mapping function is typically necessary for these applications

Toric Bezier patches are generalizations of classical patches (triangular, tensor product) which are defined on the convex hull of a set of integer lattice points

We give a geometric condition on the control points that we show is equivalent to the injectivity of every 2D toric Bezier patch with those control points for all possible choices of weights

This condition refines that of Craciun, et al., which only implied injectivity on the interior of a patch

Today I read a paper titled “A mathematical model for networks with structures in the mesoscale”

The abstract is:
The new concept of multilevel network is introduced in order to embody some topological properties of complex systems with structures in the mesoscale which are not completely captured by the classical models

This new model, which generalizes the hyper-network and hyper-structure models, fits perfectly with several real-life complex systems, including social and public transportation networks

We present an analysis of the structural properties of the multilevel network, including the clustering and the metric structures

Some analytical relationships amongst the efficiency and clustering coefficient of this new model and the corresponding parameters of the underlying network are obtained

Finally some random models for multilevel networks are given to illustrate how different multilevel structures can produce similar underlying networks and therefore that the mesoscale structure should be taken into account in many applications

Today I read a paper titled “Understanding Cascading Failures in Power Grids”

The abstract is:
In the past, we have observed several large blackouts, i.e

loss of power to large areas

It has been noted by several researchers that these large blackouts are a result of a cascade of failures of various components

As a power grid is made up of several thousands or even millions of components (relays, breakers, transformers, etc.), it is quite plausible that a few of these components do not perform their function as desired

Their failure/misbehavior puts additional burden on the working components causing them to misbehave, and thus leading to a cascade of failures

The complexity of the entire power grid makes it difficult to model each and every individual component and study the stability of the entire system

For this reason, it is often the case that abstract models of the working of the power grid are constructed and then analyzed

These models need to be computationally tractable while serving as a reasonable model for the entire system

In this work, we construct one such model for the power grid, and analyze it