justin

Today I read a paper titled “Impact of Gender and Age on performing Search Tasks Online”

The abstract is:
More and more people use the Internet to work on duties of their daily work routine

To find the right information online, Web search engines are the tools of their choice

Apart from finding facts, people use Web search engines to also execute rather complex and time consuming search tasks

So far search engines follow the one-for-all approach to serve its users and little is known about the impact of gender and age on people’s Web search behavior

In this article we present a study that examines (1) how female and male web users carry out simple and complex search tasks and what are the differences between the two user groups, and (2) how the age of the users impacts their search performance

The laboratory study was done with 56 ordinary people each carrying out 12 search tasks

Our findings confirm that age impacts behavior and search performance significantly, while gender influences were smaller than expected

Today I read a paper titled “A List of Household Objects for Robotic Retrieval Prioritized by People with ALS (Version 092008)”

The abstract is:
This technical report is designed to serve as a citable reference for the original prioritized object list that the Healthcare Robotics Lab at Georgia Tech released on its website in September of 2008

It is also expected to serve as the primary citable reference for the research associated with this list until the publication of a detailed, peer-reviewed paper

The original prioritized list of object classes resulted from a needs assessment involving 8 motor-impaired patients with amyotrophic lateral sclerosis (ALS) and targeted, in-person interviews of 15 motor-impaired ALS patients

All of these participants were drawn from the Emory ALS Center

The prioritized object list consists of 43 object classes ranked by how important the participants considered each class to be for retrieval by an assistive robot

We intend for this list to be used by researchers to inform the design and benchmarking of robotic systems, especially research related to autonomous mobile manipulation

Today I read a paper titled “Relativistic virtual worlds: an emerging framework”

The abstract is:
In this paper, I will attempt to establish a framework for representation in virtual worlds that may allow for input data from many different scales and virtual physics to be merged

For example, a typical virtual environment must effectively handle user input, sensor data, and virtual world physics all in real- time

Merging all of these data into a single interactive system requires that we adapt approaches from topological methods such as n-dimensional relativistic representation

A number of hypothetical examples will be provided throughout the paper to clarify technical challenges that need to be overcome to realize this vision

The long-term goal of this work is that truly invariant representations will ultimately result from establishing formal, inclusive relationships between these different domains

Using this framework, incomplete information in one or more domains can be compensated for by parallelism and mappings within the virtual world representation

To introduce this approach, I will review recent developments in embodiment, virtual world technology, and neuroscience relevant to the control of virtual worlds

The next step will be to borrow ideas from fields such as brain science, applied mathematics, and cosmology to give proper perspective to this approach

A simple demonstration will then be given using an intuitive example of physical relativism

Finally, future directions for the application of this method will be considered

Today I read a paper titled “Image Retargeting by Content-Aware Synthesis”

The abstract is:
Real-world images usually contain vivid contents and rich textural details, which will complicate the manipulation on them

In this paper, we design a new framework based on content-aware synthesis to enhance content-aware image retargeting

By detecting the textural regions in an image, the textural image content can be synthesized rather than simply distorted or cropped

This method enables the manipulation of textural & non-textural regions with different strategy since they have different natures

We propose to retarget the textural regions by content-aware synthesis and non-textural regions by fast multi-operators

To achieve practical retargeting applications for general images, we develop an automatic and fast texture detection method that can detect multiple disjoint textural regions

We adjust the saliency of the image according to the features of the textural regions

To validate the proposed method, comparisons with state-of-the-art image targeting techniques and a user study were conducted

Convincing visual results are shown to demonstrate the effectiveness of the proposed method

Today I read a paper titled “Complex Eigenvalues for Binary Subdivision Schemes”

The abstract is:
Convergence properties of binary stationary subdivision schemes for curves have been analyzed using the techniques of z-transforms and eigenanalysis

Eigenanalysis provides a way to determine derivative continuity at specific points based on the eigenvalues of a finite matrix

None of the well-known subdivision schemes for curves have complex eigenvalues

We prove when a convergent scheme with palindromic mask can have complex eigenvalues and that a lower limit for the size of the mask exists in this case

We find a scheme with complex eigenvalues achieving this lower bound

Furthermore we investigate this scheme numerically and explain from a geometric viewpoint why such a scheme has not yet been used in computer-aided geometric design

Today I read a paper titled “Image Deblurring and Super-resolution by Adaptive Sparse Domain Selection and Adaptive Regularization”

The abstract is:
As a powerful statistical image modeling technique, sparse representation has been successfully used in various image restoration applications

The success of sparse representation owes to the development of l1-norm optimization techniques, and the fact that natural images are intrinsically sparse in some domain

The image restoration quality largely depends on whether the employed sparse domain can represent well the underlying image

Considering that the contents can vary significantly across different images or different patches in a single image, we propose to learn various sets of bases from a pre-collected dataset of example image patches, and then for a given patch to be processed, one set of bases are adaptively selected to characterize the local sparse domain

We further introduce two adaptive regularization terms into the sparse representation framework

First, a set of autoregressive (AR) models are learned from the dataset of example image patches

The best fitted AR models to a given patch are adaptively selected to regularize the image local structures

Second, the image non-local self-similarity is introduced as another regularization term

In addition, the sparsity regularization parameter is adaptively estimated for better image restoration performance

Extensive experiments on image deblurring and super-resolution validate that by using adaptive sparse domain selection and adaptive regularization, the proposed method achieves much better results than many state-of-the-art algorithms in terms of both PSNR and visual perception

Today I read a paper titled “How to build a DNA search engine like Google?”

The abstract is:
This paper proposed a new method to build the large scale DNA sequences search system based on web search engine technology

We give a very brief introduction for the methods used in search engine first

Then how to build a DNA search system like Google is illustrated in detail

Since there is no local alignment process, this system is able to provide the ms level search services for billions of DNA sequences in a typical server

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