902 resultados para Math Applications in Computer Science


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To construct Biodiversity richness maps from Environmental Niche Models (ENMs) of thousands of species is time consuming. A separate species occurrence data pre-processing phase enables the experimenter to control test AUC score variance due to species dataset size. Besides, removing duplicate occurrences and points with missing environmental data, we discuss the need for coordinate precision, wide dispersion, temporal and synonymity filters. After species data filtering, the final task of a pre-processing phase should be the automatic generation of species occurrence datasets which can then be directly ’plugged-in’ to the ENM. A software application capable of carrying out all these tasks will be a valuable time-saver particularly for large scale biodiversity studies.

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In the BiodiversityWorld project we are building a GRID to support scientific biodiversity-related research. The requirements associated with such a GRID are somewhat different from other GRIDs, and this has influenced the architecture that we have developed. In this paper we outline these requirements, most notably the need to interoperate over a diverse set of legacy databases and applications in an environment that supports effective resource discovery and use of these resources in complex workflows. Our architecture provides an invocation model that is usable over a wide range of resource types and underlying GRID middleware. However, there is a trade-off between the flexibility provided by our architecture and its performance. We discuss how this affects the inclusion of computationally intensive applications and applications that are highly interactive; we also consider the broader issue of interoperation with other GRIDs.

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Two novel benzodioxotetraaza macrocycles [2,9-dioxo-1,4,7,10-tetraazabicyclo[10.4.0]1,11-hexadeca-1(11),13,15-triene (H(2)L1) and 2,10-dioxo-1,4,8,11-tetraazabicyclo[11.4.0]1,12-heptadeca-1(12),14,16-triene (H(2)L2)] were synthesized by a [1 + 1] crablike cyclization. The protonation constants of both ligands were determined by H-1 NMR titration and by potentiometry at 25.0 degrees C in 0.10 M ionic strength in KNO3. The latter method was also used to ascertain the stability constants of their copper(II) complexes. These studies showed that the CuL1 complex has a much lower thermodynamic stability than the CuL2, and the H(2)L2 displays an excellent affinity for copper(II), due to the good fit of copper(II) into its cavity. The copper complexes of the novel ligands were characterized by electronic spectroscopy in solution and by crystal X-ray diffraction. These studies indicated that the copper center in the CuL1 complex adopts a square-pyramidal geometry with the four nitrogen atoms of the macrocycle forming the equatorial plane and a water molecule at axial position, and the copper in the CuL2 complex is square-planar. Several labeling conditions were tested, and only H(2)L2 could be labeled with Cu-67 efficiently (> 98%) in mild conditions (39 degrees C, 15 min) to provide a slightly hydrophilic radioligand (log D = -0.19 +/- 0.03 at pH 7.4). The in vitro stability was studied in the presence of different buffers or with an excess of diethylenetriamine-pentaethanoic acid. Very high stability was shown under these conditions for over 5 days. The incubation of the radiocopper complex in human serum showed 6% protein binding.

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Finding an estimate of the channel impulse response (CIR) by correlating a received known (training) sequence with the sent training sequence is commonplace. Where required, it is also common to truncate the longer correlation to a sub-set of correlation coefficients by finding the set of N sequential correlation coefficients with the maximum power. This paper presents a new approach to selecting the optimal set of N CIR coefficients from the correlation rather than relying on power. The algorithm reconstructs a set of predicted symbols using the training sequence and various sub-sets of the correlation to find the sub-set that results in the minimum mean squared error between the actual received symbols and the reconstructed symbols. The application of the algorithm is presented in the context of the TDMA based GSM/GPRS system to demonstrate an improvement in the system performance with the new algorithm and the results are presented in the paper. However, the application lends itself to any training sequence based communication system often found within wireless consumer electronic device(1).

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When using e-learning material some students progress readily, others have difficulties. In a traditional classroom the teacher would identify those with difficulties and direct them to additional resources. This support is not easily available within e-learning. A new approach to providing constructive feedback is developed that will enable an e-learning system to identify areas of weakness and provide guidance on further study. The approach is based on the tagging of learning material with appropriate keywords that indicate the contents. Thus if a student performs poorly on an assessment on topic X, there is a need to suggest further study of X and participation in activities related to X such as forums. As well as supporting the learner this type of constructive feedback can also inform other stakeholders. For example a tutor can monitor the progress of a cohort; an instructional designer can monitor the quality of learning objects in facilitating the appropriate knowledge across many learners.

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There are three key driving forces behind the development of Internet Content Management Systems (CMS) - a desire to manage the explosion of content, a desire to provide structure and meaning to content in order to make it accessible, and a desire to work collaboratively to manipulate content in some meaningful way. Yet the traditional CMS has been unable to meet the latter of these requirements, often failing to provide sufficient tools for collaboration in a distributed context. Peer-to-Peer (P2P) systems are networks in which every node is an equal participant (whether transmitting data, exchanging content, or invoking services) and there is an absence of any centralised administrative or coordinating authorities. P2P systems are inherently more scalable than equivalent client-server implementations as they tend to use resources at the edge of the network much more effectively. This paper details the rationale and design of a P2P middleware for collaborative content management.

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Many evolutionary algorithm applications involve either fitness functions with high time complexity or large dimensionality (hence very many fitness evaluations will typically be needed) or both. In such circumstances, there is a dire need to tune various features of the algorithm well so that performance and time savings are optimized. However, these are precisely the circumstances in which prior tuning is very costly in time and resources. There is hence a need for methods which enable fast prior tuning in such cases. We describe a candidate technique for this purpose, in which we model a landscape as a finite state machine, inferred from preliminary sampling runs. In prior algorithm-tuning trials, we can replace the 'real' landscape with the model, enabling extremely fast tuning, saving far more time than was required to infer the model. Preliminary results indicate much promise, though much work needs to be done to establish various aspects of the conditions under which it can be most beneficially used. A main limitation of the method as described here is a restriction to mutation-only algorithms, but there are various ways to address this and other limitations.