Archives for 2008

Today I read a paper titled “Medical Image Segmentation and Localization using Deformable Templates”

The abstract is:
This paper presents deformable templates as a tool for segmentation and localization of biological structures in medical images.

Structures are represented by a prototype template, combined with a parametric warp mapping used to deform the original shape.

The localization procedure is achieved using a multi-stage, multi-resolution algorithm de-signed to reduce computational complexity and time.

The algorithm initially identifies regions in the image most likely to contain the desired objects and then examines these regions at progressively increasing resolutions.

The final stage of the algorithm involves warping the prototype template to match the localized objects.

The algorithm is presented along with the results of four example applications using MRI, x-ray and ultrasound images.

Today I read a paper titled “Time and the Prisoner’s Dilemma”

The abstract is:
This paper examines the integration of computational complexity into game theoretic models.

The example focused on is the Prisoner’s Dilemma, repeated for a finite length of time.

We show that a minimal bound on the players’ computational ability is sufficient to enable cooperative behavior.

In addition, a variant of the repeated Prisoner’s Dilemma game is suggested, in which players have the choice of opting out.

This modification enriches the game and suggests dominance of cooperative strategies.

Competitive analysis is suggested as a tool for investigating sub-optimal (but computationally tractable) strategies and game theoretic models in general.

Using competitive analysis, it is shown that for bounded players, a sub-optimal strategy might be the optimal choice, given resource limitations.

Today I read a paper titled “Optimization of Evolutionary Neural Networks Using Hybrid Learning Algorithms”

The abstract is:
Evolutionary artificial neural networks (EANNs) refer to a special class of artificial neural networks (ANNs) in which evolution is another fundamental form of adaptation in addition to learning.

Evolutionary algorithms are used to adapt the connection weights, network architecture and learning algorithms according to the problem environment.

Even though evolutionary algorithms are well known as efficient global search algorithms, very often they miss the best local solutions in the complex solution space.

In this paper, we propose a hybrid meta-heuristic learning approach combining evolutionary learning and local search methods (using 1st and 2nd order error information) to improve the learning and faster convergence obtained using a direct evolutionary approach.

The proposed technique is tested on three different chaotic time series and the test results are compared with some popular neuro-fuzzy systems and a recently developed cutting angle method of global optimization.

Empirical results reveal that the proposed technique is efficient in spite of the computational complexity.

Today I read a paper titled “Data-Structure Rewriting”

The abstract is:
We tackle the problem of data-structure rewriting including pointer redirections.

We propose two basic rewrite steps: (i) Local Redirection and Replacement steps the aim of which is redirecting specific pointers determined by means of a pattern, as well as adding new information to an existing data ; and (ii) Global Redirection steps which are aimed to redirect all pointers targeting a node towards another one.

We define these two rewriting steps following the double pushout approach.

We define first the category of graphs we consider and then define rewrite rules as pairs of graph homomorphisms of the form “L <- K ->R”.

Unfortunately, inverse pushouts (complement pushouts) are not unique in our setting and pushouts do not always exist.

Therefore, we define rewriting steps so that a rewrite rule can always be performed once a matching is found.

Today I read a paper titled “Mobile Agent Based Solutions for Knowledge Assessment in elearning Environments”

The abstract is:
E-learning is nowadays one of the most interesting of the “e- ” domains available through the Internet.

The main problem to create a Web-based, virtual environment is to model the traditional domain and to implement the model using the most suitable technologies.

We analyzed the distance learning domain and investigated the possibility to implement some e-learning services using mobile agent technologies.

This paper presents a model of the Student Assessment Service (SAS) and an agent-based framework developed to be used for implementing specific applications.

A specific Student Assessment application that relies on the framework was developed.

Today I read a paper titled “Evolutionary Computing”

The abstract is:
Evolutionary computing (EC) is an exciting development in Computer Science.

It amounts to building, applying and studying algorithms based on the Darwinian principles of natural selection.

In this paper we briefly introduce the main concepts behind evolutionary computing.

We present the main components all evolutionary algorithms (EA), sketch the differences between different types of EAs and survey application areas ranging from optimization, modeling and simulation to entertainment.

Today I read a paper titled “Efficiency Loss in a Network Resource Allocation Game: The Case of Elastic Supply”

The abstract is:
We consider a resource allocation problem where individual users wish to send data across a network to maximize their utility, and a cost is incurred at each link that depends on the total rate sent through the link.

It is known that as long as users do not anticipate the effect of their actions on prices, a simple proportional pricing mechanism can maximize the sum of users’ utilities minus the cost (called aggregate surplus).

Continuing previous efforts to quantify the effects of selfish behavior in network pricing mechanisms, we consider the possibility that users anticipate the effect of their actions on link prices.

Under the assumption that the links’ marginal cost functions are convex, we establish existence of a Nash equilibrium.

We show that the aggregate surplus at a Nash equilibrium is no worse than a factor of 4*sqrt{2} – 5 times the optimal aggregate surplus; thus, the efficiency loss when users are selfish is no more than approximately 34%.

Today I read a paper titled “Distributed Control of Microscopic Robots in Biomedical Applications”

The abstract is:
Current developments in molecular electronics, motors and chemical sensors could enable constructing large numbers of devices able to sense, compute and act in micron-scale environments.

Such microscopic machines, of sizes comparable to bacteria, could simultaneously monitor entire populations of cells individually in vivo.

This paper reviews plausible capabilities for microscopic robots and the physical constraints due to operation in fluids at low Reynolds number, diffusion-limited sensing and thermal noise from Brownian motion.

Simple distributed controls are then presented in the context of prototypical biomedical tasks, which require control decisions on millisecond time scales.

The resulting behaviors illustrate trade-offs among speed, accuracy and resource use.

A specific example is monitoring for patterns of chemicals in a flowing fluid released at chemically distinctive sites.

Information collected from a large number of such devices allows estimating properties of cell-sized chemical sources in a macroscopic volume.

The microscopic devices moving with the fluid flow in small blood vessels can detect chemicals released by tissues in response to localized injury or infection.

We find the devices can readily discriminate a single cell-sized chemical source from the background chemical concentration, providing high-resolution sensing in both time and space.

By contrast, such a source would be difficult to distinguish from background when diluted throughout the blood volume as obtained with a blood sample.

Today I read a paper titled “Idiotypic Immune Networks in Mobile Robot Control”

The abstract is:
Jerne’s idiotypic network theory postulates that the immune response involves inter-antibody stimulation and suppression as well as matching to antigens.

The theory has proved the most popular Artificial Immune System (ais) model for incorporation into behavior-based robotics but guidelines for implementing idiotypic selection are scarce.

Furthermore, the direct effects of employing the technique have not been demonstrated in the form of a comparison with non-idiotypic systems.

This paper aims to address these issues.

A method for integrating an idiotypic ais network with a Reinforcement Learning based control system (rl) is described and the mechanisms underlying antibody stimulation and suppression are explained in detail.

Some hypotheses that account for the network advantage are put forward and tested using three systems with increasing idiotypic complexity.

The basic rl, a simplified hybrid ais-rl that implements idiotypic selection independently of derived concentration levels and a full hybrid ais-rl scheme are examined.

The test bed takes the form of a simulated Pioneer robot that is required to navigate through maze worlds detecting and tracking door markers.

Today I read a paper titled “Integration of a Balanced Virtual Manikin in a Virtual Reality Platform aimed at Virtual Prototyping”

The abstract is:
The work presented here is aimed at introducing a virtual human controller in a virtual prototyping framework.

After a brief introduction describing the problem solved in the paper, we describe the interest as for digital humans in the context of concurrent engineering.

This leads us to draw a control architecture enabling to drive virtual humans in a real-time immersed way, and to interact with the product, through motion capture.

Unfortunately, we show this control scheme can lead to unfeasible movements because of the lack of balance control.

Introducing such a controller is a problem that was never addressed in the context of real-time.

We propose an implementation of a balance controller, that we insert into the previously described control scheme.

Next section is dedicated to show the results we obtained.

Finally, we propose a virtual reality platform into which the digital character controller is integrated.

Today I read a paper titled “Mixed Reality States in a Bidirectionally Coupled Interreality System”

The abstract is:
We present experimental data on the limiting behavior of an interreality system comprising a virtual horizontally driven pendulum coupled to its real-world counterpart, where the interaction time scale is much shorter than the time scale of the dynamical system.

We present experimental evidence that if the physical parameters of the simplified virtual system match those of the real system within a certain tolerance, there is a transition from an uncorrelated dual reality state to a mixed reality state of the system in which the motion of the two pendula is highly correlated.

The region in parameter space for stable solutions has an Arnold tongue structure for both the experimental data and for a numerical simulation.

As virtual systems better approximate real ones, even weak coupling in other interreality systems may produce sudden changes to mixed reality states.

Today I read a paper titled “Comparison of the Bayesian and Randomised Decision Tree Ensembles within an Uncertainty Envelope Technique”

The abstract is:
Multiple Classifier Systems (MCSs) allow evaluation of the uncertainty of classification outcomes that is of crucial importance for safety critical applications.

The uncertainty of classification is determined by a trade-off between the amount of data available for training, the classifier diversity and the required performance.

The interpretability of MCSs can also give useful information for experts responsible for making reliable classifications.

For this reason Decision Trees (DTs) seem to be attractive classification models for experts.

The required diversity of MCSs exploiting such classification models can be achieved by using two techniques, the Bayesian model averaging and the randomised DT ensemble.

Both techniques have revealed promising results when applied to real-world problems.

In this paper we experimentally compare the classification uncertainty of the Bayesian model averaging with a restarting strategy and the randomised DT ensemble on a synthetic dataset and some domain problems commonly used in the machine learning community.

To make the Bayesian DT averaging feasible, we use a Markov Chain Monte Carlo technique.

The classification uncertainty is evaluated within an Uncertainty Envelope technique dealing with the class posterior distribution and a given confidence probability.

Exploring a full posterior distribution, this technique produces realistic estimates which can be easily interpreted in statistical terms.

In our experiments we found out that the Bayesian DTs are superior to the randomised DT ensembles within the Uncertainty Envelope technique.

Today I read a paper titled “Algorithms for Max Hamming Exact Satisfiability”

The abstract is:
We here study Max Hamming XSAT, ie, the problem of finding two XSAT models at maximum Hamming distance.

By using a recent XSAT solver as an auxiliary function, an O(1.911^n) time algorithm can be constructed, where n is the number of variables.

This upper time bound can be further improved to O(1.8348^n) by introducing a new kind of branching, more directly suited for finding models at maximum Hamming distance.

The techniques presented here are likely to be of practical use as well as of theoretical value, proving that there are non-trivial algorithms for maximum Hamming distance problems.

Today I read a paper titled “Self-organizing neural networks in classification and image recognition”

The abstract is:
Self-organizing neural networks are used for brick finding in OPERA experiment.

Self-organizing neural networks and wavelet analysis used for recognition and extraction of car numbers from images.

Today I read a paper titled “Bayesian Restoration of Digital Images Employing Markov Chain Monte Carlo a Review”

The abstract is:
A review of Bayesian restoration of digital images based on Monte Carlo techniques is presented.

The topics covered include Likelihood, Prior and Posterior distributions, Poisson, Binay symmetric channel, and Gaussian channel models of Likelihood distribution,Ising and Potts spin models of Prior distribution, restoration of an image through Posterior maximization, statistical estimation of a true image from Posterior ensembles, Markov Chain Monte Carlo methods and cluster algorithms.

Today I read a paper titled “Evolving controllers for simulated car racing”

The abstract is:
This paper describes the evolution of controllers for racing a simulated radio-controlled car around a track, modelled on a real physical track.

Five different controller architectures were compared, based on neural networks, force fields and action sequences.

The controllers use either egocentric (first person), Newtonian (third person) or no information about the state of the car (open-loop controller).

The only controller that was able to evolve good racing behaviour was based on a neural network acting on egocentric inputs.

Today I read a paper titled “Diagnostic Rule Extraction Using Neural Networks”

The abstract is:
The neural networks have trained on incomplete sets that a doctor could collect.

Trained neural networks have correctly classified all the presented instances.

The number of intervals entered for encoding the quantitative variables is equal two.

The number of features as well as the number of neurons and layers in trained neural networks was minimal.

Trained neural networks are adequately represented as a set of logical formulas that more comprehensible and easy-to-understand.

These formulas are as the syndrome-complexes, which may be easily tabulated and represented as a diagnostic table that the doctors usually use.

Decision rules provide the evaluations of their confidence in which interested a doctor.

Conducted clinical researches have shown that iagnostic decisions produced by symbolic rules have coincided with the doctor’s conclusions.

Today I read a paper titled “Sharp transition towards shared vocabularies in multi-agent systems”

The abstract is:
What processes can explain how very large populations are able to converge on the use of a particular word or grammatical construction without global coordination? Answering this question helps to understand why new language constructs usually propagate along an S-shaped curve with a rather sudden transition towards global agreement.

It also helps to analyze and design new technologies that support or orchestrate self-organizing communication systems, such as recent social tagging systems for the web.

The article introduces and studies a microscopic model of communicating autonomous agents performing language games without any central control.

We show that the system undergoes a disorder/order transition, going trough a sharp symmetry breaking process to reach a shared set of conventions.

Before the transition, the system builds up non-trivial scale-invariant correlations, for instance in the distribution of competing synonyms, which display a Zipf-like law.

These correlations make the system ready for the transition towards shared conventions, which, observed on the time-scale of collective behaviors, becomes sharper and sharper with system size.

This surprising result not only explains why human language can scale up to very large populations but also suggests ways to optimize artificial semiotic dynamics.

Today I read a paper titled “Quantum Computers”

The abstract is:
This research paper gives an overview of quantum computers – description of their operation, differences between quantum and silicon computers, major construction problems of a quantum computer and many other basic aspects.

No special scientific knowledge is necessary for the reader.