A geometric algorithm for an artificial life form based on anachronistic methods

Modern methods of spawning new technological motifs are not appropriate when it is desired to realize artificial life as an actual real world entity unto itself (Pattee 1995; Brooks 2006; Chalmers 1995). Many fundamental aspects of such a machine are absent in common methods, which generally lack methodologies of construction. In this paper we mix classical and modern studies in order to attempt to realize an artificial life form from first principles. A model of an algorithm is introduced, its methodology of construction is presented, and the fundamental source from which it sprang is discussed.

Architecture for Living Neuronal Network Control of a mobile robot

The intelligent controlling mechanism of a typical mobile robot is usually a computer system. Research is however now ongoing in which biological neural networks are being cultured and trained to act as the brain of an interactive real world robot – thereby either completely replacing or operating in a cooperative fashion with a computer system. Studying such neural systems can give a distinct insight into biological neural structures and therefore such research has immediate medical implications. The principal aims of the present research are to assess the computational and learning capacity of dissociated cultured neuronal networks with a view to advancing network level processing of artificial neural networks. This will be approached by the creation of an artificial hybrid system (animat) involving closed loop control of a mobile robot by a dissociated culture of rat neurons. This paper details the components of the overall animat closed loop system architecture and reports on the evaluation of the results from preliminary real-life and simulated robot experiments.

Convectively coupled equatorial waves in high resolution Hadley centre climate models

Current global atmospheric models fail to simulate well organised tropical phenomena in which convection interacts with dynamics and physics. A new methodology to identify convectively coupled equatorial waves, developed by NCAS-Climate, has been applied to output from the two latest models of the Met Office/Hadley Centre which have fundamental differences in dynamical formulation. Variability, horizontal and vertical structures, and propagation characteristics of tropical convection and equatorial waves, along with their coupled behaviour in the models are examined and evaluated against a previous comprehensive study of observations. It is shown that, in general, the models perform well for equatorial waves coupled with off-equatorial convection. However they perform poorly for waves coupled with equatorial convection. The vertical structure of the simulated wave is not conducive to energy conversion/growth and does not support the correct physical-dynamical coupling that occurs in the real world. The following figure shows an example of the Kelvin wave coupled with equatorial convection. It shows that the models fail to simulate a key feature of convectively coupled Kelvin wave in observations, namely near surface anomalous equatorial zonal winds together with intensified equatorial convection and westerly winds in phase with the convection. The models are also not able to capture the observed vertical tilt structure and the vertical propagation of the Kelvin wave into the lower stratosphere as well as the secondary peak in the mid-troposphere, particularly in HadAM3. These results can be used to provide a test-bed for experimentation to improve the coupling of physics and dynamics in climate and weather models.

Fast training of self organizing maps for the visual exploration of molecular compounds

Visual exploration of scientific data in life science area is a growing research field due to the large amount of available data. The Kohonen’s Self Organizing Map (SOM) is a widely used tool for visualization of multidimensional data. In this paper we present a fast learning algorithm for SOMs that uses a simulated annealing method to adapt the learning parameters. The algorithm has been adopted in a data analysis framework for the generation of similarity maps. Such maps provide an effective tool for the visual exploration of large and multi-dimensional input spaces. The approach has been applied to data generated during the High Throughput Screening of molecular compounds; the generated maps allow a visual exploration of molecules with similar topological properties. The experimental analysis on real world data from the National Cancer Institute shows the speed up of the proposed SOM training process in comparison to a traditional approach. The resulting visual landscape groups molecules with similar chemical properties in densely connected regions.

Recent trends in sea level pressure in the Indian Ocean region

During the second half of the twentieth century the Indian Ocean exhibited a rapid rise in sea surface temperatures (SST). It has been argued - largely on the basis of experiments with atmospheric GCMs - that this rapid warming was an important cause of remote changes in climate, in particular an increasing trend in the North Atlantic Oscillation Index and decreases in African rainfall. Here however we present evidence that the Indian Ocean warming was associated with local increases in sea level pressure (SLP). These increases are inconsistent with results from experiments in which an atmospheric GCM is forced by historical SST, which show robust decreases in SLP. The clear discrepancy between the observed and simulated trends in SLP suggests that the response of some atmospheric GCMs to the Indian Ocean warming may not provide a reliable guide to the behaviour of the real world.

Factors influencing anthropogenic carbon dioxide uptake in the North Atlantic in models of the ocean carbon cycle

The uptake and storage of anthropogenic carbon in the North Atlantic is investigated using different configurations of ocean general circulation/carbon cycle models. We investigate how different representations of the ocean physics in the models, which represent the range of models currently in use, affect the evolution of CO2 uptake in the North Atlantic. The buffer effect of the ocean carbon system would be expected to reduce ocean CO2 uptake as the ocean absorbs increasing amounts of CO2. We find that the strength of the buffer effect is very dependent on the model ocean state, as it affects both the magnitude and timing of the changes in uptake. The timescale over which uptake of CO2 in the North Atlantic drops to below preindustrial levels is particularly sensitive to the ocean state which sets the degree of buffering; it is less sensitive to the choice of atmospheric CO2 forcing scenario. Neglecting physical climate change effects, North Atlantic CO2 uptake drops below preindustrial levels between 50 and 300 years after stabilisation of atmospheric CO2 in different model configurations. Storage of anthropogenic carbon in the North Atlantic varies much less among the different model configurations, as differences in ocean transport of dissolved inorganic carbon and uptake of CO2 compensate each other. This supports the idea that measured inventories of anthropogenic carbon in the real ocean cannot be used to constrain the surface uptake. Including physical climate change effects reduces anthropogenic CO2 uptake and storage in the North Atlantic further, due to the combined effects of surface warming, increased freshwater input, and a slowdown of the meridional overturning circulation. The timescale over which North Atlantic CO2 uptake drops to below preindustrial levels is reduced by about one-third, leading to an estimate of this timescale for the real world of about 50 years after the stabilisation of atmospheric CO2. In the climate change experiment, a shallowing of the mixed layer depths in the North Atlantic results in a significant reduction in primary production, reducing the potential role for biology in drawing down anthropogenic CO2.

Goal sketching: towards agile requirements engineering

This paper describes a technique that can be used as part of a simple and practical agile method for requirements engineering. The technique can be used together with Agile Programming to develop software in internet time. We illustrate the technique and introduce lazy refinement, responsibility composition and context sketching. Goal sketching has been used in a number of real-world development projects, one of which is described here.

A hierarchical distributed approach for mining molecular fragments

Recently, two approaches have been introduced that distribute the molecular fragment mining problem. The first approach applies a master/worker topology, the second approach, a completely distributed peer-to-peer system, solves the scalability problem due to the bottleneck at the master node. However, in many real world scenarios the participating computing nodes cannot communicate directly due to administrative policies such as security restrictions. Thus, potential computing power is not accessible to accelerate the mining run. To solve this shortcoming, this work introduces a hierarchical topology of computing resources, which distributes the management over several levels and adapts to the natural structure of those multi-domain architectures. The most important aspect is the load balancing scheme, which has been designed and optimized for the hierarchical structure. The approach allows dynamic aggregation of heterogenous computing resources and is applied to wide area network scenarios.

Distributed mining of molecular fragments

In real world applications sequential algorithms of data mining and data exploration are often unsuitable for datasets with enormous size, high-dimensionality and complex data structure. Grid computing promises unprecedented opportunities for unlimited computing and storage resources. In this context there is the necessity to develop high performance distributed data mining algorithms. However, the computational complexity of the problem and the large amount of data to be explored often make the design of large scale applications particularly challenging. In this paper we present the first distributed formulation of a frequent subgraph mining algorithm for discriminative fragments of molecular compounds. Two distributed approaches have been developed and compared on the well known National Cancer Institute’s HIV-screening dataset. We present experimental results on a small-scale computing environment.

The method of least squares used to invert an orbit problem

Six parameters uniquely describe the orbit of a body about the Sun. Given these parameters, it is possible to make predictions of the body's position by solving its equation of motion. The parameters cannot be directly measured, so they must be inferred indirectly by an inversion method which uses measurements of other quantities in combination with the equation of motion. Inverse techniques are valuable tools in many applications where only noisy, incomplete, and indirect observations are available for estimating parameter values. The methodology of the approach is introduced and the Kepler problem is used as a real-world example. (C) 2003 American Association of Physics Teachers.

Controlling a mobile robot with a biological brain

The intelligent controlling mechanism of a typical mobile robot is usually a computer system. Some recent research is ongoing in which biological neurons are being cultured and trained to act as the brain of an interactive real world robot�thereby either completely replacing, or operating in a cooperative fashion with, a computer system. Studying such hybrid systems can provide distinct insights into the operation of biological neural structures, and therefore, such research has immediate medical implications as well as enormous potential in robotics. The main aim of the research is to assess the computational and learning capacity of dissociated cultured neuronal networks. A hybrid system incorporating closed-loop control of a mobile robot by a dissociated culture of neurons has been created. The system is flexible and allows for closed-loop operation, either with hardware robot or its software simulation. The paper provides an overview of the problem area, gives an idea of the breadth of present ongoing research, establises a new system architecture and, as an example, reports on the results of conducted experiments with real-life robots.