Improving clustering with metabolic pathway data

Background: It is a common practice in bioinformatics to validate each group returned by a clustering algorithm through manual analysis, according to a-priori biological knowledge. This procedure helps finding functionally related patterns to propose hypotheses for their behavior and the biological processes involved. Therefore, this knowledge is used only as a second step, after data are just clustered according to their expression patterns. Thus, it could be very useful to be able to improve the clustering of biological data by incorporating prior knowledge into the cluster formation itself, in order to enhance the biological value of the clusters. Results: A novel training algorithm for clustering is presented, which evaluates the biological internal connections of the data points while the clusters are being formed. Within this training algorithm, the calculation of distances among data points and neurons centroids includes a new term based on information from well-known metabolic pathways. The standard self-organizing map (SOM) training versus the biologically-inspired SOM (bSOM) training were tested with two real data sets of transcripts and metabolites from Solanum lycopersicum and Arabidopsis thaliana species. Classical data mining validation measures were used to evaluate the clustering solutions obtained by both algorithms. Moreover, a new measure that takes into account the biological connectivity of the clusters was applied. The results of bSOM show important improvements in the convergence and performance for the proposed clustering method in comparison to standard SOM training, in particular, from the application point of view. Conclusions: Analyses of the clusters obtained with bSOM indicate that including biological information during training can certainly increase the biological value of the clusters found with the proposed method. It is worth to highlight that this fact has effectively improved the results, which can simplify their further analysis.Fil: Milone, Diego Humberto. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Santa Fe. Instituto de Investigación en Señales, Sistemas e Inteligencia Computacional. Universidad Nacional del Litoral. Facultad de Ingeniería y Ciencias Hídricas. Instituto de Investigación en Señales, Sistemas e Inteligencia Computacional; ArgentinaFil: Stegmayer, Georgina. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Santa Fe. Instituto de Investigación en Señales, Sistemas e Inteligencia Computacional. Universidad Nacional del Litoral. Facultad de Ingeniería y Ciencias Hídricas. Instituto de Investigación en Señales, Sistemas e Inteligencia Computacional; ArgentinaFil: Lopez, Mariana Gabriela. Instituto Nacional de Tecnología Agropecuaria. Centro de Investigación en Ciencias Veterinarias y Agronómicas. Instituto de Biotecnología; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas; ArgentinaFil: Kamenetzky, Laura. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina. Instituto Nacional de Tecnología Agropecuaria. Centro de Investigación en Ciencias Veterinarias y Agronómicas. Instituto de Biotecnología; ArgentinaFil: Carrari, Fernando Oscar. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina. Instituto Nacional de Tecnología Agropecuaria. Centro de Investigación en Ciencias Veterinarias y Agronómicas. Instituto de Biotecnología; Argentin

The Crowded Page

The Crowded Page is an Internet-based humanities computing project whose goal is to create data-mining and visualization tools that will allow researchers to map out the intricate connections between the members of artistic and literary communities. In most accounts of literary and art history, a work of art or literature is said to be the product of a single creative mind. In an effort to make visible what is often obscured in traditional histories of art and literature, The Crowded Page seeks to take advantage of the unique capabilities of the digital medium to foreground the ways in which a complex network of friends, editors, neighbors, lovers, and fellow artists and writers informs the creative process

低資源言語としてのベンガル語に対するオントロジーに基づく機械翻訳

In this research we propose ontology based Machine Translation with the help of WordNetand UNL Ontology. Example-Based Machine Translation (EBMT) for low resource language,like Bengali, has low-coverage issues. Due to the lack of parallel corpus, it has highprobability of handling unknown words. We have implemented an EBMT system for lowresourcelanguage pair. The EBMT architecture use chunk-string templates (CSTs) andunknown word translation mechanism. CSTs consist of a chunk in source-language, a stringin target-language, and word alignment information. CSTs are prepared automatically fromaligned parallel corpus and WordNet by using English chunker. For unknown wordtranslation, we used WordNet hypernym tree and English-Bengali dictionary. Proposedsystem first tries to find semantically related English words from WordNet for the unknownword. From these related words, we choose the semantically closest related word whoseBangla translation exists in English-Bangla dictionary. If no Bangla translation exists, thesystem uses IPA-based-transliteration. For proper nouns, the system uses Akkhortransliteration mechanism. CSTs improved the wide-coverage by 57 points and quality by48.81 points in human evaluation. Currently 64.29% of the test-set translations by the systemwere acceptable. The combined solutions of CSTs and unknown words generated 67.85%acceptable translations from the test-set. Unknown words mechanism improved translationquality by 3.56 points in human evaluation. This research also proposed the way to autogenerate the explanation of each concept using the semantic backgrounds provided by UNLOntology. These explanations are useful for improving translation quality of unknown words.Ontology Based Machine Translation for Bengali as Low-resource Language.本研究では、WordNet と UNL オントロジーを用いた、オントロジーに基づく機械翻訳を提案する。ベンガル語のような低資源言語 (low-resource language)に対しては、具体例に基づく機械翻訳 (EBMT)は、あまり有効ではない。パラレル・コーパスの欠如のために、多数の未知語を扱わなければならなくなるためである。我々は、低資源言語間の EBMT システムを実装した。実装したEBMT アーキテクチャでは、chunk-string templates (CSTs)と、未知語翻訳メカニズムを用いている。CST は、起点言語のチャンク、目的言語の文字列と、単語アラメント情報から成る。CST は、英語チャンカーを用いて、アラインメント済みのパラレル・コーパスとWordNet から、自動的に生成される。最初に、起点言語のチャンクが OpenNLP チャンカーを用いて自動生成される。そして、初期CST が、各起点言語のチャンクに対して生成され、すべての目的文に対するCSTアラインメントがパラレル・コーパスを用いて生成される。その後、システムは、単語アラインメント情報を用いて、CSTの組合せを生成する。最後に、WordNet を用いて、広い適用範囲を得るためにCST を一般化する。未知語翻訳に対しては、WordNet hypernym treeと、英語・ベンガル語辞書を用いる。提案システムは、最初に、未知語に対して、WordNet から意味的に関連した英単語を発見しようと試みる。これらの関連語から、英語・ベンガル語辞書にベンガル語の翻訳が存在する、意味的に最も近い語を選ぶ。もし、ベンガル語の翻訳が存在しなければ、システムはIPA-based翻訳を行う。固有名詞に対しては、システムは、Akkhor 翻訳メカニズムを用いる。CST は57 ポイントの広い適用範囲を持つように改善され、その際の人間による訳文の評価も 48.81 ポイントを得た。現在、システムのよって、64.29%のテストケースの翻訳が行える。未知語メカニズムは、人間に評価において 3.56 ポイント、翻訳の質を改善した。CST と未知語の組合せよる解法は、テストケースにおいて、67.85%の許容可能な翻訳を生成した。また、本研究では、UNL オントロジーが提供するsemantic background を用いて、各概念に対する説明を自動生成する方法も提案した。このシステムに対する入力は、１つのユニバーサル・ワード(UN)であり、システムの出力はその UN の英語や日本語による説明文である。与えられたUN に対して、システムは、最初に、SemanticWordMap を発見するが、それは、１つの特定のUN に対する、UNL オントロジーからのすべての直接的、間接的参照関係を含む。したがって、このステップの入力は、１つのUN であり、出力はWordMapグラフである。次のステップで、変換規則を用いて、WordMap グラフをUNL に変換する。この変換規則は、ユーザの要求に応じて、“From UWs only”や “From UNL Ontology”と指定できる。したがって、このステップの入力はWordMap グラフであり、出力はUNL表現である。最終ステップでは、UNL DeConverter を用いてUNL 表現を変換し、自然言語を用いて記述する。これらの表現は、未知語に対する翻訳の質の向上に有効であることがわかった。電気通信大学201

A framework for semantic checking of information systems

Dissertação para obtenção do Grau de Mestre em Engenharia Electrotécnica e de ComputadoresIn this day and age, enterprises often find that their business benefits greatly if they collaborate with others in order to be more competitive and productive. However these collaborations often come with some costs since the worldwide diversity of communities has led to the development of various knowledge representation elements, namely ontologies that, in most cases, are not semantically equivalent. Consequently, even though some enterprises may operate in the same domain, they can have different representations of that same knowledge. However, even after solving this issue and establishing a semantic alignment with other systems, they do not remain unchanged. Subsequently, a regular check of its semantic alignment is needed. To aid in the resolution of this semantic interoperability problem, the author proposes a framework that intends to provide generic solutions and a mean to validate the semantic consistency of ontologies in various scenarios, thus maintaining the interoperability state between the enrolled systems

RFID Technology in Intelligent Tracking Systems in Construction Waste Logistics Using Optimisation Techniques

Construction waste disposal is an urgent issue for protecting our environment. This paper proposes a waste management system and illustrates the work process using plasterboard waste as an example, which creates a hazardous gas when land filled with household waste, and for which the recycling rate is less than 10% in the UK. The proposed system integrates RFID technology, Rule-Based Reasoning, Ant Colony optimization and knowledge technology for auditing and tracking plasterboard waste, guiding the operation staff, arranging vehicles, schedule planning, and also provides evidence to verify its disposal. It h relies on RFID equipment for collecting logistical data and uses digital imaging equipment to give further evidence; the reasoning core in the third layer is responsible for generating schedules and route plans and guidance, and the last layer delivers the result to inform users. The paper firstly introduces the current plasterboard disposal situation and addresses the logistical problem that is now the main barrier to a higher recycling rate, followed by discussion of the proposed system in terms of both system level structure and process structure. And finally, an example scenario will be given to illustrate the system’s utilization

LearnFCA: A Fuzzy FCA and Probability Based Approach for Learning and Classification

Formal concept analysis(FCA) is a mathematical theory based on lattice and order theory used for data analysis and knowledge representation. Over the past several years, many of its extensions have been proposed and applied in several domains including data mining, machine learning, knowledge management, semantic web, software development, chemistry ,biology, medicine, data analytics, biology and ontology engineering. This thesis reviews the state-of-the-art of theory of Formal Concept Analysis(FCA) and its various extensions that have been developed and well-studied in the past several years. We discuss their historical roots, reproduce the original definitions and derivations with illustrative examples. Further, we provide a literature review of it’s applications and various approaches adopted by researchers in the areas of dataanalysis, knowledge management with emphasis to data-learning and classification problems. We propose LearnFCA, a novel approach based on FuzzyFCA and probability theory for learning and classification problems. LearnFCA uses an enhanced version of FuzzyLattice which has been developed to store class labels and probability vectors and has the capability to be used for classifying instances with encoded and unlabelled features. We evaluate LearnFCA on encodings from three datasets - mnist, omniglot and cancer images with interesting results and varying degrees of success. Adviser: Dr Jitender Deogu

A process-based control for evolvable production systems

Dissertação apresentada na Faculdade de Ciências e Tecnologia da Universidade Nova de Lisboa para a obtenção do grau de Mestre em Engenharia Electrotécnica e de ComputadoresNowadays, companies in a challenging environment are compelled to adapt to the rapid changes in the manufacturing business. The search for new processes to create products with short life-cycles at low cost, while keeping the same levels of productivity and quality is greater than ever. This has generated the need to create even more agile manufacturing systems, which could easily adapt to the market changes at a low cost. Advances in information technologies have allowed manufacturing systems to achieve new levels of agility, opening the doors to new approaches. These same advances helped companies in several sectors other than manufacturing to gain e ectiveness through the synchronization of the processes of their several departments by using Business Process Management tools. This thesis proposes a system that reacts and adapts itself to di erent production orders by means of recon guration. To reach this goal, the concept of Business Process Management was used. This concept, already used in many companies, allows them to model their inner behaviours with processes that can be changed according to their needs. A manufacturing system using this may become equally agile and alter its functioning in accordance with the needs of other departments of the same company. To create the system presented in this thesis it was used a multi-agent architecture based on process execution. Each agent contains a knowledge base, used by its processes,that stores internal or external information. This system may be used not only in the manufacturing shop oor, but also in any other areas within a company. This thesis also presents an application of the system to the shop oor, based on the Evolvable Production Systems concept, in which each agent represents a manufacturing resource that o ers a given set of services useful to the production process. The resources,by means of the agents, may aggregate among themselves to execute services together. Keywords: Manufacturing system, multi-agent system, ontology, process, BPM, EPS

Creating the Future: the Joint ESA-NASA Multi-Mission Algorithm and Analysis Platform's Data Ecosystem

No abstract availabl

Método de construção de ontologias multilingues com associação de conceitos a objetos em espaço 3D

Tese (doutorado) - Universidade Federal de Santa Catarina, Centro Tecnológico, Programa de Pós-Graduação em Engenharia e Gestão do ConhecimentoCom o crescimento no volume de documentos disponíveis na Web, são necessários métodos para gerenciar o conhecimento disponível nesses documentos. Entre os métodos de gestão, destaca-se a construção e aplicação de ontologias. Torna-se então necessária a aplicação de um meio descritivo mais universal para a apresentação de um conceito e de suas relações semânticas, um meio que seja compreensível por qualquer pessoa, em qualquer idioma. Torna-se necessário também o reuso de duas tecnologias já existentes, na tentativa de universalização de conceitos e relações semânticas: a Universal Networking Language (UNL) e a Unified Modeling Language (UML). Portanto, o objetivo deste trabalho é desenvolver um método de construção e representação visual de ontologia multilingue e modelar um editor usando recursos gráficos em espaços 2D e 3D. A proposta da tese consiste em uma metodologia de construção de ontologias composta de palavras universais, associadas a objetos no espaço 3D, possibilitando a conversão entre instâncias de ontologias em vários idiomas. Para a validação desta tese, foram programados três sistemas gráficos compartilhados de construção de ontologias multilíngües, na forma de redes de relacionamento e envoltórias, utilizando os conceitos de Palavras Universais do projeto UNL como ponte para equivalência entre os conceitos dessas ontologias, e usando critérios de usabilidade durante a construção do editor. Este trabalho utilizou a pesquisa qualitativa como abordagem para análise e interpretação dos dados. As fontes de informações desta pesquisa foram obtidas por intermédio da pesquisa bibliográfica, em que os dados estão disponíveis em livros, publicações e periódicos. Quanto aos objetivos, esta pesquisa caracterizou-se como descritiva. A proposta é seguida de um projeto e programação de um aplicativo de construção de ontologias. Posteriormente, para fins de melhoramento no uso deste aplicativo, são levantados os critérios de usabilidade de software. Após o levantamento, três aplicativos de construção de ontologias são comparados com o uso desses critérios, por meio de entrevistas com usuários: a) O primeiro aplicativo apresenta ontologias com conceitos associados a objetos no espaço 3D, na forma de redes de relacionamento e envoltórias; b) Um aplicativo que apresenta ontologias como redes de relacionamento e envoltórias no espaço 2D; c) Um aplicativo que apresenta ontologias construídas na forma de listas indentadas, formulários e tabelas. Após a comparação dessas ferramentas, foram apontadas vantagens e desvantagens no uso de cada um dos três modelos de editores. Em seguida, foram levantados os relatos científicos anteriores referentes a comparações entre visões de ontologias, comparando opiniões concordantes e discordantes dos autores. Concluiu-se que os resultados foram bem-sucedidos na representação de conceitos multilíngües associados a objetos, representados tanto no espaço 2D quanto no espaço 3D. Foram observados também resultados bem sucedidos nos modelos matemáticos e estruturais que fundamentaram as aplicações de construção de ontologias.With the growing volume of documents on world wide web, it may be necessary methods for management of the available knowledge on these documents. Among these management methods, it is highlighted the ontology construction and application. So, it became needed the application of a more universal descriptive media for the presentation of a given concepts and its semantic relations, some mean which can be comprehensible by any people, in any language. It also became necessary the reuse of two technologies already existent, on the attempt for universalization of concepts and semantic relations: the Universal Networking Language (UNL) and the Unified Modeling Language (UML). So, the objective of this work is the development of a method for construction and visual representation of multilingual ontologies, and the modeling of an editor, using graphic resources on 2D and 3D spaces. The proposal of this doctoral thesis is about a methodology for ontology construction, composed by universal words, associated to objects in a 3D space, turning possible the conversion of ontologies among different languages. For the validation of this thesis, it has been programmed three shared graphic system for construction of multilingual ontology instances, in the form of relationship networks, and envelopes, using the concepts of UNL´s Universal Words, as a bridge for the equivalency between these ontologies´ concepts, using usability criteria to optimize the construction of these three editors. This work used qualitative research as the approach for data analysis and interpretation. The sources for information were obtained by means of bibliographic research, where information was available in books, publications and periodic. For the objectives, this research has been characterized as a descriptive one. The proposal is followed by a project and programming of an application for ontology construction. After that, for optimization purposes, it there has been surveyed some software usability criteria. After the survey, three application for ontology construction were compared, using these criteria, by means of user interview: a) The first application presents ontology instances with concepts associated to objects on 3D space, on the form of relationship networks and envelopes; b) An application which presents ontology instances as relationship networks and envelopes on 2D space; c) An application which presents ontology instances on the form of indented lists, forms and tables. After the comparison among these three tools, it was pointed advantages and disadvantages on the use of any of the three ontology editor models. After that, it was surveyed anterior scientific reports about previous comparisons among ontology visualizations, comparing concordant and discordant opinions between authors. It was concluded that the results were well-succeeded on the representation of multilingual concepts associated to objects, represented on 2D and 3D spaces. It was observed also well succeeded results on the mathematical and structural models which grounded the applications for ontology construction

BrainMap – A Navigation Support System in a Tourism Case Study

Part 5: Computational SystemsInternational audiencePresently, the amount of documents in corporations can make searching and browsing for a specific topic or information a very hard task. Therefore, it is important to develop tools to ease the retrieval of specific information and to support the exploration by users on corporate intranets (composed of several hundreds of gigabytes of documents). Although not explicitly identified, many of these documents are related among themselves (directly or implicitly). In this paper we discuss a navigation support system to explore graphs applied to document correlations, using a tourism case study