Archives for 2007

Today I read a paper titled “Hard Disk Drive as a Magnetomechanical Logic Device”

The abstract is:
We consider the conditions how two binary numbers can be superimposed on the same track with the use of different recording magnetic fields.

As a result the average magnetization of longitudinal medium along the track can have three states: -M, 0 and +M.

Possibility to perform logic operations with these states is considered.

We demonstrate OR, AND, XOR and NOT operations and discuss a modification of a recording device.

Today I read a paper titled “Two-dimensional cellular automata and the analysis of correlated time series”

The abstract is:
Correlated time series are time series that, by virtue of the underlying process to which they refer, are expected to influence each other strongly.

We introduce a novel approach to handle such time series, one that models their interaction as a two-dimensional cellular automaton and therefore allows them to be treated as a single entity.

We apply our approach to the problems of filling gaps and predicting values in rainfall time series.

Computational results show that the new approach compares favorably to Kalman smoothing and filtering.

Today I read a paper titled “Conflict-based Force Aggregation”

The abstract is:
In this paper we present an application where we put together two methods for clustering and classification into a force aggregation method.

Both methods are based on conflicts between elements.

These methods work with different type of elements (intelligence reports, vehicles, military units) on different hierarchical levels using specific conflict assessment methods on each level.

We use Dempster-Shafer theory for conflict calculation between elements, Dempster-Shafer clustering for clustering these elements, and templates for classification.

The result of these processes is a complete force aggregation on all levels handled.

Today I read a paper titled “On the possible Computational Power of the Human Mind”

The abstract is:
The aim of this paper is to address the question: Can an artificial neural network (ANN) model be used as a possible characterization of the power of the human mind? We will discuss what might be the relationship between such a model and its natural counterpart.

A possible characterization of the different power capabilities of the mind is suggested in terms of the information contained (in its computational complexity) or achievable by it.

Such characterization takes advantage of recent results based on natural neural networks (NNN) and the computational power of arbitrary artificial neural networks (ANN).

The possible acceptance of neural networks as the model of the human mind’s operation makes the aforementioned quite relevant.

Today I read a paper titled “Imagination as Holographic Processor for Text Animation”

The abstract is:
Imagination is the critical point in developing of realistic artificial intelligence (AI) systems.

One way to approach imagination would be simulation of its properties and operations.

We developed two models: AI-Brain Network Hierarchy of Languages and Semantical Holographic Calculus as well as simulation system ScriptWriter that emulate the process of imagination through an automatic animation of English texts.

The purpose of this paper is to demonstrate the model and to present ScriptWriter system this http URL&M=application/x-gtar for simulation of the imagination.

Today I read a paper titled “A Fast Block Matching Algorithm for Video Motion Estimation Based on Particle Swarm Optimization and Motion Prejudgment”

The abstract is:
In this paper, we propose a fast 2-D block-based motion estimation algorithm called Particle Swarm Optimization – Zero-motion Prejudgment(PSO-ZMP) which consists of three sequential routines: 1)Zero-motion prejudgment.

The routine aims at finding static macroblocks(MB) which do not need to perform remaining search thus reduces the computational cost; 2)Predictive image coding and 3)PSO matching routine.

Simulation results obtained show that the proposed PSO-ZMP algorithm achieves over 10 times of computation less than Diamond Search(DS) and 5 times less than the recent proposed Adaptive Rood Pattern Searching(ARPS).

Meanwhile the PSNR performances using PSO-ZMP are very close to that using DS and ARPS in some less-motioned sequences.

While in some sequences containing dense and complex motion contents, the PSNR performances of PSO-ZMP are several dB lower than that using DS and ARPS but in an acceptable degree.

Today I read a paper titled “A Sequential Algorithm for Training Text Classifiers”

The abstract is:
The ability to cheaply train text classifiers is critical to their use in information retrieval, content analysis, natural language processing, and other tasks involving data which is partly or fully textual.

An algorithm for sequential sampling during machine learning of statistical classifiers was developed and tested on a newswire text categorization task.

This method, which we call uncertainty sampling, reduced by as much as 500-fold the amount of training data that would have to be manually classified to achieve a given level of effectiveness..

Today I read a paper titled “Multi-agent coordination using nearest neighbor rules: revisiting the Vicsek model”

The abstract is:
Recently, Jadbabaie, Lin, and Morse (IEEE TAC, 48(6)2003:988-1001) offered a mathematical analysis of the discrete time model of groups of mobile autonomous agents raised by Vicsek et al.

in 1995.

In their paper, Jadbabaie et al.

showed that all agents shall move in the same heading, provided that these agents are periodically linked together.

This paper sharpens this result by showing that coordination will be reached under a very weak condition that requires all agents are finally linked together.

This condition is also strictly weaker than the one Jadbabaie et al.

desired.

Today I read a paper titled “An Example of Clifford Algebras Calculations with GiNaC”

The abstract is:
This example of Clifford algebras calculations uses GiNaC (this http URL) library, which includes a support for generic Clifford algebra starting from version~1.3.0.

Both symbolic and numeric calculation are possible and can be blended with other functions of GiNaC.

This calculations was made for the paper math.CV/0410399.

Described features of GiNaC are already available at PyGiNaC (this http URL) and due to course should propagate into other software like GNU Octave (this http URL), gTybalt (this http URL), which use GiNaC library as their back-end.

Today I read a paper titled “2D Electrophoresis Gel Image and Diagnosis of a Disease”

The abstract is:
The process of diagnosing a disease from the 2D gel electrophoresis image is a challenging problem.

This is due to technical difficulties of generating reproducible images with a normalized form and the effect of negative stain.

In this paper, we will discuss a new concept of interpreting the 2D images and overcoming the aforementioned technical difficulties using mathematical transformation.

The method makes use of 2D gel images of proteins in serums and we explain a way of representing the images into vectors in order to apply machine-learning methods, such as the support vector machine.

Today I read a paper titled “Path-independent load balancing with unreliable machines”

The abstract is:
We consider algorithms for load balancing on unreliable machines.

The objective is to optimize the two criteria of minimizing the makespan and minimizing job reassignments in response to machine failures.

We assume that the set of jobs is known in advance but that the pattern of machine failures is unpredictable.

Motivated by the requirements of BGP routing, we consider path-independent algorithms, with the property that the job assignment is completely determined by the subset of available machines and not the previous history of the assignments.

We examine first the question of performance measurement of path-independent load-balancing algorithms, giving the measure of makespan and the normalized measure of reassignments cost.

We then describe two classes of algorithms for optimizing these measures against an oblivious adversary for identical machines.

The first, based on independent random assignments, gives expected reassignment costs within a factor of 2 of optimal and gives a makespan within a factor of O(log m/log log m) of optimal with high probability, for unknown job sizes.

The second, in which jobs are first grouped into bins and at most one bin is assigned to each machine, gives constant-factor ratios on both reassignment cost and makespan, for known job sizes.

Several open problems are discussed.

Today I read a paper titled “Comparing Robustness of Pairwise and Multiclass Neural-Network Systems for Face Recognition”

The abstract is:
Noise, corruptions and variations in face images can seriously hurt the performance of face recognition systems.

To make such systems robust, multiclass neuralnetwork classifiers capable of learning from noisy data have been suggested.

However on large face data sets such systems cannot provide the robustness at a high level.

In this paper we explore a pairwise neural-network system as an alternative approach to improving the robustness of face recognition.

In our experiments this approach is shown to outperform the multiclass neural-network system in terms of the predictive accuracy on the face images corrupted by noise.

Today I read a paper titled “The Optimal Design of Three Degree-of-Freedom Parallel Mechanisms for Machining Applications”

The abstract is:
The subject of this paper is the optimal design of a parallel mechanism intended for three-axis machining applications.

Parallel mechanisms are interesting alternative designs in this context but most of them are designed for three- or six-axis machining applications.

In the last case, the position and the orientation of the tool are coupled and the shape of the workspace is complex.

The aim of this paper is to use a simple parallel mechanism with two-degree-of-freedom (dof) for translational motions and to add one leg to have one-dof rotational motion.

The kinematics and singular configurations are studied as well as an optimization method.

The three-degree-of-freedom mechanisms analyzed in this paper can be extended to four-axis machines by adding a fourth axis in series with the first two.

Today I read a paper titled “Games of fixed rank: A hierarchy of bimatrix games”

The abstract is:
We propose a new hierarchical approach to understand the complexity of the open problem of computing a Nash equilibrium in a bimatrix game.

Specifically, we investigate a hierarchy of bimatrix games $(A,B)$ which results from restricting the rank of the matrix $A+B$ to be of fixed rank at most $k$.

For every fixed $k$, this class strictly generalizes the class of zero-sum games, but is a very special case of general bimatrix games.

We show that even for $k=1$ the set of Nash equilibria of these games can consist of an arbitrarily large number of connected components.

While the question of exact polynomial time algorithms to find a Nash equilibrium remains open for games of fixed rank, we can provide polynomial time algorithms for finding an $\epsilon$-approximation.

Today I read a paper titled “Artificial Intelligence for Conflict Management”

The abstract is:
Militarised conflict is one of the risks that have a significant impact on society.

Militarised Interstate Dispute (MID) is defined as an outcome of interstate interactions, which result on either peace or conflict.

Effective prediction of the possibility of conflict between states is an important decision support tool for policy makers.

In a previous research, neural networks (NNs) have been implemented to predict the MID.

Support Vector Machines (SVMs) have proven to be very good prediction techniques and are introduced for the prediction of MIDs in this study and compared to neural networks.

The results show that SVMs predict MID better than NNs while NNs give more consistent and easy to interpret sensitivity analysis than SVMs.