Learning Mechanisms for Information Filtering Agents

Postprint

Experience with Rule Induction & k-Nearest Neighbour Methods for Interface Agents that Learn

Peer reviewed

Case-based analysis in user requirements modelling for knowledge construction

Context: Learning can be regarded as knowledge construction in which prior knowledge and experience serve as basis for the learners to expand their knowledge base. Such a process of knowledge construction has to take place continuously in order to enhance the learners’ competence in a competitive working environment. As the information consumers, the individual users demand personalised information provision which meets their own specific purposes, goals, and expectations. Objectives: The current methods in requirements engineering are capable of modelling the common user’s behaviour in the domain of knowledge construction. The users’ requirements can be represented as a case in the defined structure which can be reasoned to enable the requirements analysis. Such analysis needs to be enhanced so that personalised information provision can be tackled and modelled. However, there is a lack of suitable modelling methods to achieve this end. This paper presents a new ontological method for capturing individual user’s requirements and transforming the requirements onto personalised information provision specifications. Hence the right information can be provided to the right user for the right purpose. Method: An experiment was conducted based on the qualitative method. A medium size of group of users participated to validate the method and its techniques, i.e. articulates, maps, configures, and learning content. The results were used as the feedback for the improvement. Result: The research work has produced an ontology model with a set of techniques which support the functions for profiling user’s requirements, reasoning requirements patterns, generating workflow from norms, and formulating information provision specifications. Conclusion: The current requirements engineering approaches provide the methodical capability for developing solutions. Our research outcome, i.e. the ontology model with the techniques, can further enhance the RE approaches for modelling the individual user’s needs and discovering the user’s requirements.

Profiling management for personalised multimedia delivery on-demand within the AXMEDIS framework

Media content distribution on-demand becomes more complex when performed on a mass scale involving various channels with distinct and dynamic network characteristics, and, deploying a variety of terminal devices offering a wide range of capabilities. It is practically impossible to create and prepackage various static versions of the same content to match all the varying demand parameters of clients for various contexts. In this paper we present a profiling management approach for dynamically personalised media content delivery on-demand integrated with the AXMEDIS Framework. The client profiles comprise the representation of User, Device, Network and Context of content delivery based on MPEG-21:DIA. Although the most challenging proving ground for this personalised content delivery has been the mobile testbed i.e. the distribution to mobile handsets, the framework described here can be deployed for disribution, by the AXMEDIS PnP module, through other channels e.g. satellite, Internet to a range of client terminals e.g. desktops, kiosks, IPtv and other terrminals whose baseline terminal capabilities can be made availabe by the manufacturers as is normal.

High-resolution Transcript Profiling Of The Atypical Biotrophic Interaction Between Theobroma Cacao And The Fungal Pathogen Moniliophthora Perniciosa.

Witches' broom disease (WBD), caused by the hemibiotrophic fungus Moniliophthora perniciosa, is one of the most devastating diseases of Theobroma cacao, the chocolate tree. In contrast to other hemibiotrophic interactions, the WBD biotrophic stage lasts for months and is responsible for the most distinctive symptoms of the disease, which comprise drastic morphological changes in the infected shoots. Here, we used the dual RNA-seq approach to simultaneously assess the transcriptomes of cacao and M. perniciosa during their peculiar biotrophic interaction. Infection with M. perniciosa triggers massive metabolic reprogramming in the diseased tissues. Although apparently vigorous, the infected shoots are energetically expensive structures characterized by the induction of ineffective defense responses and by a clear carbon deprivation signature. Remarkably, the infection culminates in the establishment of a senescence process in the host, which signals the end of the WBD biotrophic stage. We analyzed the pathogen's transcriptome in unprecedented detail and thereby characterized the fungal nutritional and infection strategies during WBD and identified putative virulence effectors. Interestingly, M. perniciosa biotrophic mycelia develop as long-term parasites that orchestrate changes in plant metabolism to increase the availability of soluble nutrients before plant death. Collectively, our results provide unique insight into an intriguing tropical disease and advance our understanding of the development of (hemi)biotrophic plant-pathogen interactions.

Sim-xl: A Powerful And User-friendly Tool For Peptide Cross-linking Analysis.

Chemical cross-linking has emerged as a powerful approach for the structural characterization of proteins and protein complexes. However, the correct identification of covalently linked (cross-linked or XL) peptides analyzed by tandem mass spectrometry is still an open challenge. Here we present SIM-XL, a software tool that can analyze data generated through commonly used cross-linkers (e.g., BS3/DSS). Our software introduces a new paradigm for search-space reduction, which ultimately accounts for its increase in speed and sensitivity. Moreover, our search engine is the first to capitalize on reporter ions for selecting tandem mass spectra derived from cross-linked peptides. It also makes available a 2D interaction map and a spectrum-annotation tool unmatched by any of its kind. We show SIM-XL to be more sensitive and faster than a competing tool when analyzing a data set obtained from the human HSP90. The software is freely available for academic use at http://patternlabforproteomics.org/sim-xl. A video demonstrating the tool is available at http://patternlabforproteomics.org/sim-xl/video. SIM-XL is the first tool to support XL data in the mzIdentML format; all data are thus available from the ProteomeXchange consortium (identifier PXD001677).

Transcriptional profiling reveals the expression of novel genes in response to various stimuli in the human dermatophyte Trichophyton rubrum

Background: Cutaneous mycoses are common human infections among healthy and immunocompromised hosts, and the anthropophilic fungus Trichophyton rubrum is the most prevalent microorganism isolated from such clinical cases worldwide. The aim of this study was to determine the transcriptional profile of T. rubrum exposed to various stimuli in order to obtain insights into the responses of this pathogen to different environmental challenges. Therefore, we generated an expressed sequence tag (EST) collection by constructing one cDNA library and nine suppression subtractive hybridization libraries. Results: The 1388 unigenes identified in this study were functionally classified based on the Munich Information Center for Protein Sequences (MIPS) categories. The identified proteins were involved in transcriptional regulation, cellular defense and stress, protein degradation, signaling, transport, and secretion, among other functions. Analysis of these unigenes revealed 575 T. rubrum sequences that had not been previously deposited in public databases. Conclusion: In this study, we identified novel T. rubrum genes that will be useful for ORF prediction in genome sequencing and facilitating functional genome analysis. Annotation of these expressed genes revealed metabolic adaptations of T. rubrum to carbon sources, ambient pH shifts, and various antifungal drugs used in medical practice. Furthermore, challenging T. rubrum with cytotoxic drugs and ambient pH shifts extended our understanding of the molecular events possibly involved in the infectious process and resistance to antifungal drugs.

Differential gene expression profiling in mucus glands of honey bee (Apis mellifera) drones during sexual maturation

The mating sign that each drone leaves when mating with a queen essentially consists of mucus gland proteins. We employed a Representational Difference Analysis (RDA) methodology to identify genes that are differentially expressed in mucus glands during sexual maturation of drones. The RDA library for mucus glands of newly emerged drones was more complex than that of 8 day-old drones, with matches to 20 predicted genes. Another 26 reads matched to the Apis genome but not to any predicted gene. Since these ESTs were located within ORFs they may represent novel honey bee genes, possibly fast evolving mucus gland proteins. In the RDA library for mucus glands of 8 day-old drones, most reads corresponded to a capsid protein of deformed wing virus, indicating high viral loads in these glands. The expression of two genes encoding venom allergens, acid phosphatase-1 and hyaluronidase, in drone mucus glands argues for their homology with the female venom glands, both associated with the reproductive system.

A score system for quality evaluation of RNA sequence tags: an improvement for gene expression profiling

Background: High-throughput molecular approaches for gene expression profiling, such as Serial Analysis of Gene Expression (SAGE), Massively Parallel Signature Sequencing (MPSS) or Sequencing-by-Synthesis (SBS) represent powerful techniques that provide global transcription profiles of different cell types through sequencing of short fragments of transcripts, denominated sequence tags. These techniques have improved our understanding about the relationships between these expression profiles and cellular phenotypes. Despite this, more reliable datasets are still necessary. In this work, we present a web-based tool named S3T: Score System for Sequence Tags, to index sequenced tags in accordance with their reliability. This is made through a series of evaluations based on a defined rule set. S3T allows the identification/selection of tags, considered more reliable for further gene expression analysis. Results: This methodology was applied to a public SAGE dataset. In order to compare data before and after filtering, a hierarchical clustering analysis was performed in samples from the same type of tissue, in distinct biological conditions, using these two datasets. Our results provide evidences suggesting that it is possible to find more congruous clusters after using S3T scoring system. Conclusion: These results substantiate the proposed application to generate more reliable data. This is a significant contribution for determination of global gene expression profiles. The library analysis with S3T is freely available at http://gdm.fmrp.usp.br/s3t/.S3T source code and datasets can also be downloaded from the aforementioned website.

Var transcription profiling of Plasmodium falciparum 3D7: assignment of cytoadherent phenotypes to dominant transcripts

Background: Cytoadherence of Plasmodium falciparum-infected red blood cells is mediated by var gene-encoded P. falciparum erythrocyte membrane protein-1 and host receptor preference depends in most cases on which of the 50-60 var genes per genome is expressed. Enrichment of phenotypically homogenous parasites by panning on receptor expressing cells is fundamental for the identification of the corresponding var transcript. Methods: P. falciparum 3D7 parasites were panned on several transfected CHO-cell lines and their var transcripts analysed by i) reverse transcription/PCR/cloning/sequencing using a universal DBL alpha specific oligonucleotide pair and ii) by reverse transcription followed by quantitative PCR using 57 different oligonucleotide pairs. Results: Each cytoadherence selected parasite line also adhered to untransfected CHO-745 cells and upregulation of the var gene PFD995/PFD1000c was consistently associated with cytoadherence to all but one CHO cell line. In addition, parasites panned on different CHO cell lines revealed candidate var genes which reproducibly associated to the respective cytoadherent phenotype. The transcription profile obtained by RT-PCR/cloning/sequencing differed significantly from that of RT-quantitative PCR. Conclusion: Transfected CHO cell lines are of limited use for the creation of monophenotypic cytoadherent parasite lines. Nevertheless, 3D7 parasites can be reproducibly selected for the transcription of different determined var genes without genetic manipulation. Most importantly, var transcription analysis by RT-PCR/cloning/sequencing may lead to erroneous interpretation of var transcription profiles.

Learning Profile Identification Based on the Analysis of the User Context of Interaction

One of the e-learning environment goal is to attend the individual needs of students during the learning process. The adaptation of contents, activities and tools into different visualization or in a variety of content types is an important feature of this environment, bringing to the user the sensation that there are suitable workplaces to his profile in the same system. Nevertheless, it is important the investigation of student behaviour aspects, considering the context where the interaction happens, to achieve an efficient personalization process. The paper goal is to present an approach to identify the student learning profile analyzing the context of interaction. Besides this, the learning profile could be analyzed in different dimensions allows the system to deal with the different focus of the learning.

Performance analysis of a single-user MISO ultra-wideband time reversal system with DFE

This paper presents an analysis of the performance of a baseband multiple-input single-output (MISO) time reversal ultra-wideband system (TR-UWB) incorporating a symbol spaced decision feedback equalizer (DFE). A semi-analytical performance analysis based on a Gaussian approach is considered, which matched well with simulation results, even for the DFE case. The channel model adopted is based on the IEEE 802.15.3a model, considering correlated shadowing across antenna elements. In order to provide a more realistic analysis, channel estimation errors are considered for the design of the TR filter. A guideline for the choice of equalizer length is provided. The results show that the system`s performance improves with an increase in the number of transmit antennas and when a symbol spaced equalizer is used with a relatively small number of taps compared to the number of resolvable paths in the channel impulse response. Moreover, it is possible to conclude that due to the time reversal scheme, the error propagation in the DFE does not play a role in the system`s performance.

Jointly multi-user detection and channel estimation with genetic algorithm

This work aims at proposing the use of the evolutionary computation methodology in order to jointly solve the multiuser channel estimation (MuChE) and detection problems at its maximum-likelihood, both related to the direct sequence code division multiple access (DS/CDMA). The effectiveness of the proposed heuristic approach is proven by comparing performance and complexity merit figures with that obtained by traditional methods found in literature. Simulation results considering genetic algorithm (GA) applied to multipath, DS/CDMA and MuChE and multi-user detection (MuD) show that the proposed genetic algorithm multi-user channel estimation (GAMuChE) yields a normalized mean square error estimation (nMSE) inferior to 11%, under slowly varying multipath fading channels, large range of Doppler frequencies and medium system load, it exhibits lower complexity when compared to both maximum likelihood multi-user channel estimation (MLMuChE) and gradient descent method (GrdDsc). A near-optimum multi-user detector (MuD) based on the genetic algorithm (GAMuD), also proposed in this work, provides a significant reduction in the computational complexity when compared to the optimum multi-user detector (OMuD). In addition, the complexity of the GAMuChE and GAMuD algorithms were (jointly) analyzed in terms of number of operations necessary to reach the convergence, and compared to other jointly MuChE and MuD strategies. The joint GAMuChE-GAMuD scheme can be regarded as a promising alternative for implementing third-generation (3G) and fourth-generation (4G) wireless systems in the near future. Copyright (C) 2010 John Wiley & Sons, Ltd.