Internet computing with distributed software agent

The phenomenonal growth of the Internet has connected us to a vast amount of computation and information resources around the world. However, making use of these resources is difficult due to the unparalleled massiveness, high communication latency, share-nothing architecture and unreliable connection of the Internet. In this dissertation, we present a distributed software agent approach, which brings a new distributed problem-solving paradigm to the Internet computing researches with enhanced client-server scheme, inherent scalability and heterogeneity. Our study discusses the role of a distributed software agent in Internet computing and classifies it into three major categories by the objects it interacts with: computation agent, information agent and interface agent. The discussion of the problem domain and the deployment of the computation agent and the information agent are presented with the analysis, design and implementation of the experimental systems in high performance Internet computing and in scalable Web searching. ^ In the computation agent study, high performance Internet computing can be achieved with our proposed Java massive computation agent (JAM) model. We analyzed the JAM computing scheme and built a brutal force cipher text decryption prototype. In the information agent study, we discuss the scalability problem of the existing Web search engines and designed the approach of Web searching with distributed collaborative index agent. This approach can be used for constructing a more accurate, reusable and scalable solution to deal with the growth of the Web and of the information on the Web. ^ Our research reveals that with the deployment of the distributed software agent in Internet computing, we can have a more cost effective approach to make better use of the gigantic scale network of computation and information resources on the Internet. The case studies in our research show that we are now able to solve many practically hard or previously unsolvable problems caused by the inherent difficulties of Internet computing. ^

Analytical approximations to predict performance measures of manufacturing systems with job failures and parallel processing

Parallel processing is prevalent in many manufacturing and service systems. Many manufactured products are built and assembled from several components fabricated in parallel lines. An example of this manufacturing system configuration is observed at a manufacturing facility equipped to assemble and test web servers. Characteristics of a typical web server assembly line are: multiple products, job circulation, and paralleling processing. The primary objective of this research was to develop analytical approximations to predict performance measures of manufacturing systems with job failures and parallel processing. The analytical formulations extend previous queueing models used in assembly manufacturing systems in that they can handle serial and different configurations of paralleling processing with multiple product classes, and job circulation due to random part failures. In addition, appropriate correction terms via regression analysis were added to the approximations in order to minimize the gap in the error between the analytical approximation and the simulation models. Markovian and general type manufacturing systems, with multiple product classes, job circulation due to failures, and fork and join systems to model parallel processing were studied. In the Markovian and general case, the approximations without correction terms performed quite well for one and two product problem instances. However, it was observed that the flow time error increased as the number of products and net traffic intensity increased. Therefore, correction terms for single and fork-join stations were developed via regression analysis to deal with more than two products. The numerical comparisons showed that the approximations perform remarkably well when the corrections factors were used in the approximations. In general, the average flow time error was reduced from 38.19% to 5.59% in the Markovian case, and from 26.39% to 7.23% in the general case. All the equations stated in the analytical formulations were implemented as a set of Matlab scripts. By using this set, operations managers of web server assembly lines, manufacturing or other service systems with similar characteristics can estimate different system performance measures, and make judicious decisions - especially setting delivery due dates, capacity planning, and bottleneck mitigation, among others.

Analytical Approximations to Predict Performance Measures of Manufacturing Systems with Job Failures and Parallel Processing

Parallel processing is prevalent in many manufacturing and service systems. Many manufactured products are built and assembled from several components fabricated in parallel lines. An example of this manufacturing system configuration is observed at a manufacturing facility equipped to assemble and test web servers. Characteristics of a typical web server assembly line are: multiple products, job circulation, and paralleling processing. The primary objective of this research was to develop analytical approximations to predict performance measures of manufacturing systems with job failures and parallel processing. The analytical formulations extend previous queueing models used in assembly manufacturing systems in that they can handle serial and different configurations of paralleling processing with multiple product classes, and job circulation due to random part failures. In addition, appropriate correction terms via regression analysis were added to the approximations in order to minimize the gap in the error between the analytical approximation and the simulation models. Markovian and general type manufacturing systems, with multiple product classes, job circulation due to failures, and fork and join systems to model parallel processing were studied. In the Markovian and general case, the approximations without correction terms performed quite well for one and two product problem instances. However, it was observed that the flow time error increased as the number of products and net traffic intensity increased. Therefore, correction terms for single and fork-join stations were developed via regression analysis to deal with more than two products. The numerical comparisons showed that the approximations perform remarkably well when the corrections factors were used in the approximations. In general, the average flow time error was reduced from 38.19% to 5.59% in the Markovian case, and from 26.39% to 7.23% in the general case. All the equations stated in the analytical formulations were implemented as a set of Matlab scripts. By using this set, operations managers of web server assembly lines, manufacturing or other service systems with similar characteristics can estimate different system performance measures, and make judicious decisions - especially setting delivery due dates, capacity planning, and bottleneck mitigation, among others.

Gestengestützte Schema- und Datenexploration

Der Zugang zu Datenbanken über die universelle Abfragesprache SQL stellt für Nicht-Spezialisten eine große Herausforderung dar. Als eine benutzerfreundliche Alternative wurden daher seit den 1970er-Jahren unterschiedliche visuelle Abfragesprachen (Visual Query Languages, kurz VQLs) für klassische PCs erforscht. Ziel der vorliegenden Arbeit ist es, eine generische VQL zu entwickeln und zu erproben, die eine gestenbasierte Exploration von Datenbanken auf Schema- und Instanzdatenebene für mobile Endgeräte, insbesondere Tablets, ermöglicht. Dafür werden verschiedene Darstellungsformen, Abfragestrategien und visuelle Hints für Fremdschlüsselbeziehungen untersucht, die den Benutzer bei der Navigation durch die Daten unterstützen. Im Rahmen einer Anforderungsanalyse erwies sich die Visualisierung der Daten und Beziehungen mittels einer platzsparenden geschachtelten NF2-Darstellung als besonders vorteilhaft. Zur Steuerung der Datenbankexploration wird eine geeignete Gestensprache, bestehend aus Stroke-, Multitouch- und Mid-Air-Gesten, vorgestellt. Das Gesamtkonzept aus Darstellung und Gestensteuerung wurde anhand des im Rahmen dieser Arbeit entwickelten GBXT-Prototyps auf seine reale Umsetzbarkeit hin, als plattformunabhängige Single-Page-Application für verschiedene mobile Endgeräte mittels JavaScript und HTML5/CSS3 untersucht.

Dynamic Link Inclusion in Online PDF Journals

Two complementary de facto standards for the publication of electronic documents are HTML on theWorldWideWeb and Adobe s PDF (Portable Document Format) language for use with Acrobat viewers. Both these formats provide support for hypertext features to be embedded within documents. We present a method, which allows links and other hypertext material to be kept in an abstract form in separate link databases. The links can then be interpreted or compiled at any stage and applied, in the correct format to some specific representation such as HTML or PDF. This approach is of great value in keeping hyperlinks relevant, up-to-date and in a form which is independent of the finally delivered electronic document format. Four models are discussed for allowing publishers to insert links into documents at a late stage. The techniques discussed have been implemented using a combination of Acrobat plug-ins, Web servers and Web browsers.

Machine learning tools for protein annotation: the cases of transmembrane β-barrel and myristoylated proteins

Biology is now a “Big Data Science” thanks to technological advancements allowing the characterization of the whole macromolecular content of a cell or a collection of cells. This opens interesting perspectives, but only a small portion of this data may be experimentally characterized. From this derives the demand of accurate and efficient computational tools for automatic annotation of biological molecules. This is even more true when dealing with membrane proteins, on which my research project is focused leading to the development of two machine learning-based methods: BetAware-Deep and SVMyr. BetAware-Deep is a tool for the detection and topology prediction of transmembrane beta-barrel proteins found in Gram-negative bacteria. These proteins are involved in many biological processes and primary candidates as drug targets. BetAware-Deep exploits the combination of a deep learning framework (bidirectional long short-term memory) and a probabilistic graphical model (grammatical-restrained hidden conditional random field). Moreover, it introduced a modified formulation of the hydrophobic moment, designed to include the evolutionary information. BetAware-Deep outperformed all the available methods in topology prediction and reported high scores in the detection task. Glycine myristoylation in Eukaryotes is the binding of a myristic acid on an N-terminal glycine. SVMyr is a fast method based on support vector machines designed to predict this modification in dataset of proteomic scale. It uses as input octapeptides and exploits computational scores derived from experimental examples and mean physicochemical features. SVMyr outperformed all the available methods for co-translational myristoylation prediction. In addition, it allows (as a unique feature) the prediction of post-translational myristoylation. Both the tools here described are designed having in mind best practices for the development of machine learning-based tools outlined by the bioinformatics community. Moreover, they are made available via user-friendly web servers. All this make them valuable tools for filling the gap between sequential and annotated data.

Deep learning and embeddings for problems of computational biology

The development of Next Generation Sequencing promotes Biology in the Big Data era. The ever-increasing gap between proteins with known sequences and those with a complete functional annotation requires computational methods for automatic structure and functional annotation. My research has been focusing on proteins and led so far to the development of three novel tools, DeepREx, E-SNPs&GO and ISPRED-SEQ, based on Machine and Deep Learning approaches. DeepREx computes the solvent exposure of residues in a protein chain. This problem is relevant for the definition of structural constraints regarding the possible folding of the protein. DeepREx exploits Long Short-Term Memory layers to capture residue-level interactions between positions distant in the sequence, achieving state-of-the-art performances. With DeepRex, I conducted a large-scale analysis investigating the relationship between solvent exposure of a residue and its probability to be pathogenic upon mutation. E-SNPs&GO predicts the pathogenicity of a Single Residue Variation. Variations occurring on a protein sequence can have different effects, possibly leading to the onset of diseases. E-SNPs&GO exploits protein embeddings generated by two novel Protein Language Models (PLMs), as well as a new way of representing functional information coming from the Gene Ontology. The method achieves state-of-the-art performances and is extremely time-efficient when compared to traditional approaches. ISPRED-SEQ predicts the presence of Protein-Protein Interaction sites in a protein sequence. Knowing how a protein interacts with other molecules is crucial for accurate functional characterization. ISPRED-SEQ exploits a convolutional layer to parse local context after embedding the protein sequence with two novel PLMs, greatly surpassing the current state-of-the-art. All methods are published in international journals and are available as user-friendly web servers. They have been developed keeping in mind standard guidelines for FAIRness (FAIR: Findable, Accessible, Interoperable, Reusable) and are integrated into the public collection of tools provided by ELIXIR, the European infrastructure for Bioinformatics.

Document engineering approaches toward scalable and structured multimedia, web and printable documents

Document engineering is the computer science discipline that investigates systems for documents in any form and in all media. As with the relationship between software engineering and software, document engineering is concerned with principles, tools and processes that improve our ability to create, manage, and maintain documents (http://www.documentengineering.org). The ACM Symposium on Document Engineering is an annual meeting of researchers active in document engineering: it is sponsored by ACM by means of the ACM SIGWEB Special Interest Group. In this editorial, we first point to work carried out in the context of document engineering, which are directly related to multimedia tools and applications. We conclude with a summary of the papers presented in this special issue.

A web-based platform for biosignal visualization and annotation

With the advent of wearable sensing and mobile technologies, biosignals have seen an increasingly growing number of application areas, leading to the collection of large volumes of data. One of the difficulties in dealing with these data sets, and in the development of automated machine learning systems which use them as input, is the lack of reliable ground truth information. In this paper we present a new web-based platform for visualization, retrieval and annotation of biosignals by non-technical users, aimed at improving the process of ground truth collection for biomedical applications. Moreover, a novel extendable and scalable data representation model and persistency framework is presented. The results of the experimental evaluation with possible users has further confirmed the potential of the presented framework.

The web feature service: transaction standard: an example of prototype implementation

Trabalho de Projecto apresentado como requisito parcial para obtenção do grau de Mestre em Ciência e Sistemas de Informação Geográfica

RealCrono –sistema de difusão de resultados em tempo real na web

A velocidade de difusão de conteúdos numa plataforma web, assume uma elevada relevância em serviços onde a informação se pretende atualizada e em tempo real. Este projeto de Mestrado, apresenta uma abordagem de um sistema distribuído de recolher e difundir resultados em tempo real entre várias plataformas, nomeadamente sistemas móveis. Neste contexto, tempo real entende-se como uma diferença de tempo nula entre a recolha e difusão, ignorando fatores que não podem ser controlados pelo sistema, como latência de comunicação e tempo de processamento. Este projeto tem como base uma arquitetura existente de processamento e publicação de resultados desportivos, que apresentava alguns problemas relacionados com escalabilidade, segurança, tempos de entrega de resultados longos e sem integração com outras plataformas. Ao longo deste trabalho procurou-se investigar fatores que condicionassem a escalabilidade de uma aplicação web dando ênfase à implementação de uma solução baseada em replicação e escalabilidade horizontal. Procurou-se também apresentar uma solução de interoperabilidade entre sistemas e plataformas heterogêneas, mantendo sempre elevados níveis de performance e promovendo a introdução de plataformas móveis no sistema. De várias abordagens existentes para comunicação em tempo real sobre uma plataforma web, adotou-se um implementação baseada em WebSocket que elimina o tempo desperdiçado entre a recolha de informação e sua difusão. Neste projeto é descrito o processo de implementação da API de recolha de dados (Collector), da biblioteca de comunicação com o Collector, da aplicação web (Publisher) e sua API, da biblioteca de comunicação com o Publisher e por fim a implementação da aplicação móvel multi-plataforma. Com os componentes criados, avaliaram-se os resultados obtidos com a nova arquitetura de forma a aferir a escalabilidade e performance da solução criada e sua adaptação ao sistema existente.

Adding SOS Core & transactional profiles support to a web thin client

Dissertation submitted in partial fulfillment of the requirements for the Degree of Master of Science in Geospatial Technologies.

Aplicació web de notícies

Aquesta memòria tracta sobre el procediment de creació d’una aplicació web de notícies. Està dividida en 3 zones, una on usuaris amb permisos d’administració poden penjar notícies per ser visualitzades per tothom, una altra que s’hi accedeix si s’és usuari registrat i permet visualitzar noticies d’altres servidors mitjançant el format de dades RSS, i un tercer apartat de gestió administrativa, incorporar noves notícies, modificar-ne de presents o introduir noves pàgines web que continguin notícies. Els usuaris registrats podran seleccionar el diaris dels quals rebran informació, així com especificar quines temàtiques prefereixen en la cerca de notícies.

Filtre de pàgines web

Aquest projecte es fonamenta en l'estudi del protocol HTTP, el qual funciona amb l'estàndard client-servidor, la seva estructura, funcionament, l'explicació d'un exemple i el tipus de dades que treballen les peticions i respostes, i la seva aplicació en el cas dels servidors intermediaris (

Aplicació web pel restaurant Gat Blau

Obtenir una aplicació web útil per al restaurant, que permetés als seus gestors mantenir el contingut des d'una interfície senzilla. L'aplicació havia de ser flexible i havia de seguir criteris de disseny que la fessin escalable i ens permetessin ampliar-la posteriorment.