Dublin City University at CLEF 2006: Experiments for the ImageCLEF Photo Collection Standard Ad Hoc Task

We provide a technical description of our submission to the CLEF 2006 Cross Language Image Retrieval(ImageCLEF) Photo Collection Standard Ad Hoc task. We performed monolingual and cross language retrieval of photo images using photo annotations with and without feedback, and also a combined visual and text retrieval approach. Topics are translated into English using the Babelfish online machine translation system. Our text runs used the BM25 algorithm, while our visual approach used simple low-level features with matching based on the Jeffrey Divergence measure. Our results consistently indicate that the fusion of text and visual features is best for this task, and that performing feedback for text consistently improves on the baseline non-feedback BM25 text runs for all language pairs

Modular Invariance and Characteristic Numbers

We show that a general miraculous cancellation formula, the divisibility of certain characteristic numbers and some other topologiclal results are con- sequences of the modular invariance of elliptic operators on loop spaces. Previously we have shown that modular invariance also implies the rigidity of many elliptic operators on loop spaces.Comment: 14 page

On localization in holomorphic equivariant cohomology

We prove a localization formula for a "holomorphic equivariant cohomology" attached to the Atiyah algebroid of an equivariant holomorphic vector bundle. This generalizes Feng-Ma, Carrell-Liebermann, Baum-Bott and K. Liu's localization formulas.Comment: 16 pages. Completely rewritten, new title. v3: Minor changes in the exposition. v4: final version to appear in Centr. Eur. J. Mat

Probing partially localized supergravity background of fundamental string ending on Dp-brane

We study the dynamics of the probe fundamental string in the field background of the partially localized supergravity solution for the fundamental string ending on Dp-brane. We separately analyze the probe dynamics for its motion along the worldvolume direction and the transverse direction of the source Dp-brane. We compare the dynamics of the probe along the Dp-brane worldvolume direction to the BIon dynamics.Comment: 20 pages, LaTeX, revised version to appear in Phys. Rev.

Quantifying key factors for optimised manufacturing of Li-ion battery anode and cathode via artificial intelligence

Li-ion battery is one of the key players in energy storage technology empowering electrified and clean transportation systems. However, it is still associated with high costs due to the expensive material as well as high fluctuations of the manufacturing process. Complicated production processes involving mechanical, chemical, and electrical operations makes the predictability of the manufacturing process a challenge, hence the process is optimised through trial and error rather systematic simulation. To establish an in-depth understanding of the interconnected processes and manufacturing parameters, this paper combines data-mining techniques and real production to offer a method for the systematic analysis, understanding and improving the Li-ion battery electrode manufacturing chain. The novelty of this research is that unlike most of the existing research that are focused on cathode manufacturing only, it covers both of the cathode and anode case studies. Furthermore, it is based on real manufacturing data, proposes a systematic design of experiment method for generating high quality and representative data, and leverages the artificial intelligence techniques to identify the dependencies in between the manufacturing parameters and the key quality factors of the electrode. Through this study, machine learning models are developed to quantify the predictability of electrode and cell properties given the coating process control parameters. Moreover, the manufacturing parameters are ranked and their contribution to the electrode and cell characteristics are quantified by models. The systematic data acquisition approach as well as the quantified interdependencies are expected to assist the manufacturer when moving towards an improved battery production chain

Machine learning for optimised and clean Li-ion battery manufacturing: Revealing the dependency between electrode and cell characteristics

The large number of parameters involved in each step of Li-ion electrode manufacturing process as well as the complex electrochemical interactions in those affect the properties of the final product. Optimization of the manufacturing process, although very challenging, is critical for reducing the production time, cost, and carbon footprint. Data-driven models offer a solution for manufacturing optimization problems and underpin future aspirations for manufacturing volumes. This study combines machine-learning approaches with the experimental data to build data-driven models for predicting final battery performance. The models capture the interdependencies between the key parameters of electrode manufacturing, its structural features, and the electrical performance characteristics of the associated Li-ion cells. The methodology here is based on a set of designed experiments conducted in a controlled environment, altering electrode coating control parameters of comma bar gap, line speed and coating ratio, obtaining the electrode structural properties of active material mass loading, thickness, and porosity, extracting the manufactured half-cell characteristics at various cycling conditions, and finally building models for interconnectivity studies and predictions. Investigating and quantifying performance predictability through a systems' view of the manufacturing process is the main novelty of this paper. Comparisons between different machine-learning models, analysis of models’ performance with a limited number of inputs, analysis of robustness to measurement noise and data-size are other contributions of this study. The results suggest that, given manufacturing parameters, the coated electrode properties and cell characteristics can be predicted with about 5% and 3% errors respectively. The presented concepts are believed to link the manufacturing at lab-scale to the pilot-line scale and support smart, optimised, and clean production of electrodes for high-quality Li-ion batteries

Specific Heat Exponent for the 3-d Ising Model from a 24-th Order High Temperature Series

We compute high temperature expansions of the 3-d Ising model using a recursive transfer-matrix algorithm and extend the expansion of the free energy to 24th order. Using ID-Pade and ratio methods, we extract the critical exponent of the specific heat to be alpha=0.104(4).Comment: 10 pages, LaTeX with 5 eps-figures using epsf.sty, IASSNS-93/83 and WUB-93-4

Brane Gas Cosmology, M-theory and Little String Theory

We generalize the Brane Gas Cosmological Scenario to M-theory degrees of freedom, namely $M5$ and $M2$ branes. Without brane intersections, the Brandenberger Vafa(BV) arguments applied to M-theory degrees of freedom generically predict a large 6 dimensional spacetime. We show that intersections of $M5$ and $M2$ branes can instead lead to a large 4 dimensional spacetime. One dimensional intersections in 11D is related to (2,0) little strings (LST) on NS5 branes in type IIA. The gas regime of membranes in M-theory corresponds to the thermodynamics of LST obtained from holography. We propose a mechanism whereby LST living on the worldvolume of NS5 (M5)-branes wrapping a five dimensional torus, annihilate most efficiently in 3+1 dimensions leading to a large 3+1 dimensional spacetime. We also show that this picture is consistent with the gas approximation in M-theory.Comment: 8 page

Developing an improved soil moisture dataset by blending passive and active microwave satellite-based retrievals

Combining information derived from satellitebased passive and active microwave sensors has the potential to offer improved estimates of surface soil moisture at global scale. We develop and evaluate a methodology that takes advantage of the retrieval characteristics of passive (AMSR-E) and active (ASCAT) microwave satellite estimates to produce an improved soil moisture product. First, volumetric soil water content (m3 m−3) from AMSR-E and degree of saturation (%) from ASCAT are rescaled against a reference land surface model data set using a cumulative distribution function matching approach. While this imposes any bias of the reference on the rescaled satellite products, it adjusts them to the same range and preserves the dynamics of original satellite-based products. Comparison with in situ measurements demonstrates that where the correlation coefficient between rescaled AMSR-E and ASCAT is greater than 0.65 (“transitional regions”), merging the different satellite products increases the number of observations while minimally changing the accuracy of soil moisture retrievals. These transitional regions also delineate the boundary between sparsely and moderately vegetated regions where rescaled AMSR-E and ASCAT, respectively, are used for the merged product. Therefore the merged product carries the advantages of better spatial coverage overall and increased number of observations, particularly for the transitional regions. The combination method developed has the potential to be applied Correspondence to: Y. Y. Liu ([email protected]) to existing microwave satellites as well as to new missions. Accordingly, a long-term global soil moisture dataset can be developed and extended, enhancing basic understanding of the role of soil moisture in the water, energy and carbon cycles

A novel axial flux magnetically geared machine for power split application

This paper proposes an axial flux magnetically geared (AFMG) permanent magnet (PM) machine for power split application in hybrid electric vehicles. The proposed AFMG machine has the merits of simple structure and improved torque density by combining a magnetic gear with a PM machine. The machine can realize power split with the help of dual mechanical ports and one electrical port, i.e., the input mechanical power and/or electrical power produced by the machine can be split or integrated. The operation principle and two feasible stator slot/rotor pole combinations are analyzed. Moreover, the influence of the machine parameters on the output torque as well as the performance of both combinations are investigated and compared by using JMAG three-dimensional finite element analysis (FEA). In addition, the method of boosting the machine torque is described and experiment results of the proposed machine prototype are provided and compared with FEA results