A computational investigation of the plasmon modes of tessellated arrays

University of Technology Sydney. Faculty of Science.This study investigates localized surface plasmon resonance (LSPR) phenomena occurring on metallic nanoparticles arranged in tessellated arrays. Clusters of nanoparticles have interesting optical properties, which could be exploited for enhancement of Surface Enhancement Raman Spectroscopy (SERS) and provide the possibility of tailoring novel technological applications entailing metamaterials for anti-reflecting coatings, superlenses, cloaking and bio-sensing. The geometric arrangement of metallic nanoparticles, and the physical parameters such as size, shape and material, affects the optical response; this leads to significant variation of the transmission spectrum with compared to isolated nanoparticles, and enhanced concentration of energy in the gaps between particles. Finite element simulations of single and dimer nanoparticles (with an electrodynamic approach) and of a unit cell of tessellated array of different symmetrical shape nanoparticles (with an electrostatic approach) have been performed. The single and dimer results provide a basis for understanding the effect of shape, corner sharpness and gap size on resonant spectra; which provide absorption enhancement and spectral shift according to the geometrical nanoparticle under simulation. The tessellated arrays are interpreted in terms of the effective permittivity, which is an important material factor that can be continuously tuned, enabling improvement of plasmon-based technological applications. Here we investigate a number of lattices including square and hexagonal arrangements of cylindrical, square, triangular and hexagonal nanoparticles and find that the peaks of resonance and the higher-order modes of the optical response can be mapped thoroughly. Overall these results further develop our perspective of the plasmon modes of arrays and offer some potential for improved tunability of the optical properties of nanocomposite materials. This provides improved strategies for designing meta-materials with specific electric transport and thermal properties

On the use of case-based planning for e-learning personalization

This is the author’s version of a work that was accepted for publication in Expert Systems with Applications. Changes resulting from the publishing process, such as peer review, editing, corrections, structural formatting, and other quality control mechanisms may not be reflected in this document. Changes may have been made to this work since it was submitted for publication. A definitive version was subsequently published in Expert Systems with Applications, 60, 1-15, 2016. DOI:10.1016/j.eswa.2016.04.030In this paper we propose myPTutor, a general and effective approach which uses AI planning techniques to create fully tailored learning routes, as sequences of Learning Objects (LOs) that fit the pedagogical and students’ requirements. myPTutor has a potential applicability to support e-learning personalization by producing, and automatically solving, a planning model from (and to) e-learning standards in a vast number of real scenarios, from small to medium/large e-learning communities. Our experiments demonstrate that we can solve scenarios with large courses and a high number of students. Therefore, it is perfectly valid for schools, high schools and universities, especially if they already use Moodle, on top of which we have implemented myPTutor. It is also of practical significance for repairing unexpected discrepancies (while the students are executing their learning routes) by using a Case-Based Planning adaptation process that reduces the differences between the original and the new route, thus enhancing the learning process. © 2016 Elsevier Ltd. All rights reserved.This work has been partially funded by the Consolider AT project CSD2007-0022 INGENIO 2010 of the Spanish Ministry of Science and Innovation, the MICINN project TIN2011-27652-C03-01, the MINECO and FEDER project TIN2014-55637-C2-2-R, the Mexican National Council of Science and Technology, the Valencian Prometeo project II/2013/019 and the BW5053 research project of the Free University of Bozen-Bolzano.Garrido Tejero, A.; Morales, L.; Serina, I. (2016). On the use of case-based planning for e-learning personalization. Expert Systems with Applications. 60:1-15. https://doi.org/10.1016/j.eswa.2016.04.030S1156

MAST: an Agent Framework to Support B2C

In this paper we present an XML-based multi-agent system, called Multi Agent System for Traders (MAST), that completely supports Business-to-Customer E-commerce activities, including advertisements and payments. MAST helps both customers and merchants in their tasks with a homogeneous and personalized approach. In particular, E-payments in MAST are implemented under the availability of financial institutions. This avoids exchanging of sensible customers' information and reinforces the confidence between customers and merchants. A complete prototype of MAST has been implemented in the JADE framework, and it has been exploited for realizing some experiments, in order to evaluate its performances

Information Agents that Learn to Understand Each Other via Semantic Negotiation

Abstract. A key issue in Distributed Applications, that widely use Information Agents for implementing several typologies of services, is that of making reciprocally understandable the meaning of terms contained in the exchanged messages, in those cases where agents use different, heterogeneous ontologies. A possible way for facing this issue is offered by the semantic negotiation, a framework in which agents try to understand each other by negotiating the semantic of the terms. Several models and protocols of semantic negotiation have been proposed in the last years. However, most of these approaches are not able to support semantic negotiation without requiring agents either to share knowledge or to use a global common ontology, and none of them provides a semantic negotiation protocol that allows the whole agent community to contribute to the semantic understanding process between each agent pair. In this work, we propose the HIerarchical SEmantic NEgotiation (HISENE) protocol, based on the idea that an agent a should be able to partition the set of the other agents on the basis both of their personal expertise of the application domain, as well as on the particular capability that each of them shows in understanding a. We also give an implementation of the proposed protocol in the standard Java Agent DEvelopment Framework (JADE)

An XML-based agent model for supporting user activities on the Web

In this paper we present X-Compass, an XML-based agent model for supporting a user in his Web activities. X-Compass is the result of our attempt of synthesizing, in a unique context, important guidelines currently characterizing the research in various Computer Science sectors. Indeed, it constructs and handles a rather rich, even if light, user profile; this latter is exploited for supporting the user in an efficient search of information of his interest; in this way, it behaves as a content-based Recommender System. Moreover, it is particularly suited for constructing multi-agent systems and, therefore, for implementing collaborative filtering recommendation techniques. In addition, since it widely uses XML technology, it is particularly light and capable of operating on various hardware and software platforms. The adoption of XML also facilitates the information exchange among X-Compass agents and, consequently, makes the management and the exploitation of X-Compass based multi-agent systems easier.</p

X-Compass: an XML agent for supporting user navigation on the Web

In this paper we present X-Compass, an XML agent for supporting a user during her/his navigation on the Web. This agent is the result of our attempt of synthesizing, in a unique context, important guidelines currently characterizing the research in various Computer Science sectors. X-Compass constructs and handles a rather rich, even if light, user profile. This latter is, then, exploited for supporting the user in the efficient search of information of her/his interest; in this way, the proposed agent behaves as a content-based recommender system. Moreover, X-Compass is particularly suited for constructing multi-agent systems and, therefore, for implementing collaborative filtering recommendation techniques. In addition, being based on XML, X-Compass is particularly light and capable of operating on various hardware and software platforms. Finally, the exploitation of XML makes the information exchange among X-Compass agents and, therefore, the management and the exploitation of X-Compass multi-agent systems, easy.</p