On Collision Course: The Nature of the Binary Star Cluster NGC 2006 / SL 538

The LMC hosts a rich variety of star clusters seen in close projected proximity. Ages have been derived for few of them showing differences up to few million years, hinting at being binary star clusters. However, final confirmation needs to be done through spectroscopic analysis. Here we focus on the LMC cluster pair NGC2006-SL538 and aim to determine whether the star cluster pair is a bound entity (binary star cluster) or a chance alignment. Using the MIKE echelle spectrograph at LCO we have acquired integrated-light spectra for each cluster. We have measured radial velocities by two methods: a) direct line profile measurement yields v$_r=300.3\pm5\pm6$ km/s for NGC2006 and $v_r=310.2\pm4\pm6$ km/s for SL538. b) By comparing observed spectra with synthetic bootstrapped spectra yielding $v_r=311.0\pm0.6$ km/s for NGC2006 and $v_r=309.4\pm0.5$ km/s for SL538. Finally when spectra are directly compared, we find a ${\Delta}v=1.08\pm0.47$ km/s. Full-spectrum SED fits reveal that the stellar population ages lie in the range 13-21 Myr with a metallicity of Z=0.008. We find indications for differences in the chemical abundance patterns as revealed by the helium absorption lines between the two clusters. The dynamical analysis shows that the two clusters are likely to merge within the next $\sim$150 Myr. The NGC2006-SL538 cluster pair shows radial velocities, stellar population and dynamical parameters consistent with a gravitational bound entity. We conclude that this is a genuine binary cluster pair, and we propose that their differences in ages and stellar population chemistry is most likely due to variances in their chemical enrichment history within their environment. We suggest that their formation may have taken place in a loosely bound star-formation complex which saw initial fragmentation but then had its clusters become a gravitationally bound pair by tidal capture.Comment: Accepted for publication in Astronomy & Astrophysics. 15 pages, 10 figures in low resolutio

Poster Abstract: Practical issues in image acquisition and transmission over wireless sensor network

Multimedia data have become an important objective in wireless sensor networks. Due to the node resource constraints (energy consumption, memory capacity, network latency and throughput) the incorporation of image sensor at the nodes is currently a challenge. In this paper, we study different node architectures, evaluating processing time, energy consumption, image quality and data delivery issues. The study shows that a specialized image co-processor is an optimal solutionJUnta de Andalucía P07-TIC-0247

Actividades en el club de matemáticas de la Universidad Pedagógica Nacional

Presentamos algunas de las actividades matemáticas diseñadas por integrantes del Grupo de Álgebra y por estudiantes practicantes del departamento de matemáticas de la Universidad Pedagógica Nacional, desarrolladas en el Club de matemáticas, éstas les ha permitido a los niños, descubrir relaciones, hacer hipótesis, simbolizar, enunciar teoremas y fascinarse con el trabajo matemático

A new QoS routing algorithm based on self-organizing maps for wireless sensor networks

For the past ten years, many authors have focused their investigations in wireless sensor networks. Different researching issues have been extensively developed: power consumption, MAC protocols, self-organizing network algorithms, data-aggregation schemes, routing protocols, QoS management, etc. Due to the constraints on data processing and power consumption, the use of artificial intelligence has been historically discarded. However, in some special scenarios the features of neural networks are appropriate to develop complex tasks such as path discovery. In this paper, we explore and compare the performance of two very well known routing paradigms, directed diffusion and Energy- Aware Routing, with our routing algorithm, named SIR, which has the novelty of being based on the introduction of neural networks in every sensor node. Extensive simulations over our wireless sensor network simulator, OLIMPO, have been carried out to study the efficiency of the introduction of neural networks. A comparison of the results obtained with every routing protocol is analyzed. This paper attempts to encourage the use of artificial intelligence techniques in wireless sensor nodes

Using artificial intelligence in routing schemes for wireless networks

For the latest 10 years, many authors have focused their investigations in wireless sensor networks. Different researching issues have been extensively developed: power consumption, MAC protocols, self-organizing network algorithms, data-aggregation schemes, routing protocols, QoS management, etc. Due to the constraints on data processing and power consumption, the use of artificial intelligence has been historically discarded. However, in some special scenarios the features of neural networks are appropriate to develop complex tasks such as path discovery. In this paper, we explore the performance of two very well-known routing paradigms, directed diffusion and Energy-Aware Routing, and our routing algorithm, named SIR, which has the novelty of being based on the introduction of neural networks in every sensor node. Extensive simulations over our wireless sensor network simulator, OLIMPO, have been carried out to study the efficiency of the introduction of neural networks. A comparison of the results obtained with every routing protocol is analyzed. This paper attempts to encourage the use of artificial intelligence techniques in wireless sensor nodes

Giving Neurons to Sensors: An Approach to QoS Management Through Artificial Intelligence in Wireless Networks

For the latest ten years, many authors have focused their investigations in wireless sensor networks. Different researching issues have been extensively developed: power consumption, MAC protocols, selforganizing network algorithms, data-aggregation schemes, routing protocols, QoS management, etc. Due to the constraints on data processing and power consumption, the use of artificial intelligence has been historically discarded. However, in some special scenarios the features of neural networks are appropriate to develop complex tasks such as path discovery. In this paper, we explore the performance of two very well known routing paradigms, directed diffusion and Energy-Aware Routing, and our routing algorithm, named SIR, which has the novelty of being based on the introduction of neural networks in every sensor node. Extensive simulations over our wireless sensor network simulator, OLIMPO, have been carried out to study the efficiency of the introduction of neural networks. A comparison of the results obtained with every routing protocol is analyzed. This paper attempts to encourage the use of artificial intelligence techniques in wireless sensor nodes

Using Artificial Intelligence in Wireless Sensor Routing Protocols

This paper represents a dissertation about how an artificial intelligence technique can be applied to wireless sensor networks. Due to the constraints on data processing and power consumption, the use of artificial intelligence has been historically discarded in these kind of networks. However, in some special scenarios the features of neural networks are appropriate to develop complex tasks such as path discovery. In this paper, we explore the performance of two very well known routing paradigms, directed diffusion and Energy-Aware Routing, and our routing algorithm, named SIR, which has the novelty of being based on the introduction of neural networks in every sensor node. Extensive simulations over our wireless sensor network simulator, OLIMPO, have been carried out to study the efficiency of the introduction of neural networks. A comparison of the results obtained with every routing protocol is analyzed

SIR: A New Wireless Sensor Network Routing Protocol Based on Artificial Intelligence

Currently, Wireless Sensor Networks (WSNs) are formed by hundreds of low energy and low cost micro-electro-mechanical systems. Routing and low power consumption have become important research issues to interconnect this kind of networks. However, conventional Quality of Service routing models, are not suitable for ad hoc sensor networks, due to the dynamic nature of such systems. This paper introduces a new QoS-driven routing algorithm, named SIR: Sensor Intelligence Routing. We have designed an artificial neural network based on Kohonen self organizing features map. Every node implements this artificial neural network forming a distributed intelligence and ubiquitous computing system

Giving neurons to sensors. QoS management in wireless sensors networks

Public utilities services (gas, water and electricity) have been traditionally automated with several technologies. The main functions that these technologies must support are AMR, Automated Meter Reading, and SCADA, Supervisory Control And Data Acquisition. Most meter manufacturers provide devices with Bluetoothr or ZigBeeTM communication features. This characteristic has allowed the inclusion of wireless sensor networks (WSN) in these systems. Once WSNs have appeared in such a scenario, real-time AMR and SCADA applications can be developed with low cost. Data must be routed from every meter to a base station. This paper describes the use of a novel QoS-driven routing algorithm, named SIR: Sensor Intelligence Routing, over a network of meters. An arti cial neural network is introduced in every node to manage the routes that data have to follow. The resulting system is named Intelligent Wireless Sensor Network (IWSN)