Embedding agents in business applications using enterprise integration patterns

This paper addresses the issue of integrating agents with a variety of external resources and services, as found in enterprise computing environments. We propose an approach for interfacing agents and existing message routing and mediation engines based on the endpoint concept from the enterprise integration patterns of Hohpe and Woolf. A design for agent endpoints is presented, and an architecture for connecting the Jason agent platform to the Apache Camel enterprise integration framework using this type of endpoint is described. The approach is illustrated by means of a business process use case, and a number of Camel routes are presented. These demonstrate the benefits of interfacing agents to external services via a specialised message routing tool that supports enterprise integration patterns

Searching Design Patterns Fast by Using Tree Traversals

Large software systems need to be modified to remain useful. Changes can be more easily performed when their design has been carefully documented. This paper presents an approach to quickly find design patterns that have been implemented into a software system. The devised solution greatly reduces the performed checks by organising the search for a design pattern as tree traversals, where candidate classes are carefully positioned into trees. By automatically tagging classes with design pattern roles we make it easier for developers to reason with large software systems. Our approach can provide documentation that lets developers understand the role each class is playing, assess the quality of the code, have assistance for refactoring and enhancing the functionalities of the software system.

Harmony and Technology Enhanced Learning

New technologies offer rich opportunities to support education in harmony. In this chapter we consider theoretical perspectives and underlying principles behind technologies for learning and teaching harmony. Such perspectives help in matching existing and future technologies to educational purposes, and to inspire the creative re-appropriation of technologies

Extracting biologically relevant information from microarray data as related to nitrate response in maize roots and node development in rice

The studies described herein explore the biological implications behind genes determined to be significant during the response of maize seedling roots to nitrate and the development of nodes in rice utilizing microarray technology to explore the genetic interactions of these two biological processes and analysis of functional annotation assigned to these sets of genes. In the first study, a total of 465 genes were identified to be differentially regulated in maize seedling roots following exposure to 5mM calcium nitrate at two time points (early: 0.5 hour and late: 24 hours). Considering the functional annotation of these genes and comparisons to previous studies performed in different biological systems, the pentose phosphate pathway, glycolysis, and Calvin cycle appear to play important roles in nitrate response. This study identified novel genes in these pathways as being differentially expressed following nitrate exposure, and implicated a unique role played by malate dehydrogenase between C3 and C4 plants. The second study describes the molecular genetics of node development in rice over four anatomical and four temporal points (nodes 1-4; days 46, 53, 60, and 67 post-planting). A total of 1,945 genes were found to be significantly differentially regulated in at least one of the 38 possible comparisons. Further, these genes were found to cluster into 10 groups of co-regulated expression. Exploration of these 10 clusters as well as consistency of differential expression between comparisons indicate that transcription is relatively stable over time for a given node, but varies to a much wider extent among nodes on a given day. The difference in expression between spatially divided nodes is especially pronounced when comparing the basal node to higher nodes. In addition, the current study has identified five putative transcription factors that may play important roles in regulating differential expression between node 1 and higher nodes

Towards an aspect weaving BPEL engine

This position paper proposes the use of dynamic aspects and the visitor design pattern to obtain a highly configurable and extensible BPEL engine. Using these two techniques, the core of this infrastructural software can be customised to meet new requirements and add features such as debugging, execution monitoring, or changing to another Web Service selection policy. Additionally, it can easily be extended to cope with customer-specific BPEL extensions. We propose the use of dynamic aspects not only on the engine itself but also on the workflow in order to tackle the problems of Web Service hot deployment and hot fixes to long running processes. In this way, composing aWeb Service "on-the-fly" means weaving its choreography interface into the workflow

DGD Gallery: Storage, sharing, and publication of digital research data

We describe a project, called the "Discretization in Geometry and Dynamics Gallery", or DGD Gallery for short, whose goal is to store geometric data and to make it publicly available. The DGD Gallery offers an online web service for the storage, sharing, and publication of digital research data.Comment: 19 pages, 8 figures, to appear in "Advances in Discrete Differential Geometry", ed. A. I. Bobenko, Springer, 201

An agent-driven semantical identifier using radial basis neural networks and reinforcement learning

Due to the huge availability of documents in digital form, and the deception possibility raise bound to the essence of digital documents and the way they are spread, the authorship attribution problem has constantly increased its relevance. Nowadays, authorship attribution,for both information retrieval and analysis, has gained great importance in the context of security, trust and copyright preservation. This work proposes an innovative multi-agent driven machine learning technique that has been developed for authorship attribution. By means of a preprocessing for word-grouping and time-period related analysis of the common lexicon, we determine a bias reference level for the recurrence frequency of the words within analysed texts, and then train a Radial Basis Neural Networks (RBPNN)-based classifier to identify the correct author. The main advantage of the proposed approach lies in the generality of the semantic analysis, which can be applied to different contexts and lexical domains, without requiring any modification. Moreover, the proposed system is able to incorporate an external input, meant to tune the classifier, and then self-adjust by means of continuous learning reinforcement.Comment: Published on: Proceedings of the XV Workshop "Dagli Oggetti agli Agenti" (WOA 2014), Catania, Italy, Sepember. 25-26, 201