Reading for Professional Purposes

‘Reading for Professional Purposes’ is intended for the students who study the English of Economic Cybernetics for their professional needs. It integrates and develops the students’ linguistic competence in business reading and writing."Професійно орієнтоване читання" призначене для студентів, які вивчають англійську мову для економічної кібернетики. Посібник інтегрує та розвиває лінгвістичну компетенцію студентів у діловому читанні та письмі

Reading for Professional Purposes

‘Reading for Professional Purposes’ is intended for the students who study the English of Economic Cybernetics for their professional needs. It integrates and develops the students’ linguistic competence in business reading and writing."Професійно орієнтоване читання" призначене для студентів, які вивчають англійську мову для економічної кібернетики. Посібник інтегрує та розвиває лінгвістичну компетенцію студентів у діловому читанні та письмі

Practical English Course for Engineering Students

Представляет собой систематизированный практический курс английского языка, целью которого является совершенствование навыков, а также развитие умений чтения и понимания англоязычной научно-технической литературы во взаимосвязи с другими видами речевой деятельности: говорением, аудированием и письмом. Состоит из четырех модулей: Electronics; Telecommunications; Information Technologies; Artificial Intelligence. Разработанная на основе модульного подхода структура, организация и изложение учебного материала позволяют использовать пособие как для аудиторной, так и для самостоятельной работы. Предназначено для студентов I ступени высшего образования, изучающих учебную дисциплину «Иностранный язык». Может быть полезно широкому кругу читателей, желающих совершенствовать навыки и развивать умения чтения и понимания англоязычной научно-технической литературы

Extracting clinical knowledge from electronic medical records

As the adoption of Electronic Medical Records (EMRs) rises in the healthcare institutions, these resources’ importance increases due to all clinical information they contain about patients. However, the unstructured information in the form of clinical narratives present in these records makes it hard to extract and structure useful clinical knowledge. This unstructured information limits the potential of the EMRs because the clinical information these records contain can be used to perform essential tasks inside healthcare institutions such as searching, summarization, decision support and statistical analysis, as well as be used to support management decisions or serve for research. These tasks can only be done if the unstructured clinical information from the narratives is appropriately extracted, structured and processed in clinical knowledge. Usually, this information extraction and structuration in clinical knowledge is performed manually by healthcare practitioners, which is not efficient and is error-prone. This research aims to propose a solution to this problem, by using Machine Translation (MT) from the Portuguese language to the English language, Natural Language Processing (NLP) and Information Extraction (IE) techniques. With the help of these techniques, the goal is to develop a prototype pipeline modular system that can extract clinical knowledge from unstructured clinical information contained in Portuguese EMRs, in an automated way, in order to help EMRs to fulfil their potential and consequently help the Portuguese hospital involved in this research. This research also intends to show that this generic prototype system and approach can potentially be applied to other hospitals, even if they don’t use the Portuguese language.Com a adopção cada vez maior das instituições de saúde face aos Processos Clínicos Electrónicos (PCE), estes documentos ganham cada vez mais importância em contexto clínico, devido a toda a informação clínica que contêm relativamente aos pacientes. No entanto, a informação não estruturada na forma de narrativas clínicas presente nestes documentos electrónicos, faz com que seja difícil extrair e estruturar deles conhecimento clínico. Esta informação não estruturada limita o potencial dos PCE, uma vez que essa mesma informação, caso seja extraída e estruturada devidamente, pode servir para que as instituições de saúde possam efectuar actividades importantes com maior eficiência e sucesso, como por exemplo actividades de pesquisa, sumarização, apoio à decisão, análises estatísticas, suporte a decisões de gestão e de investigação. Este tipo de actividades apenas podem ser feitas com sucesso caso a informação clínica não estruturada presente nos PCE seja devidamente extraída, estruturada e processada em conhecimento clínico. Habitualmente, esta extração é realizada manualmente pelos profissionais médicos, o que não é eficiente e é susceptível a erros. Esta dissertação pretende então propôr uma solução para este problema, ao utilizar técnicas de Tradução Automática (TA) da língua portuguesa para a língua inglesa, Processamento de Linguagem Natural (PLN) e Extração de Informação (EI). O objectivo é desenvolver um sistema protótipo de módulos em série que utilize estas técnicas, possibilitando a extração de conhecimento clínico, de uma forma automática, de informação clínica não estruturada presente nos PCE de um hospital português. O principal objetivo é ajudar os PCE a atingirem todo o seu potencial em termos de conhecimento clínico que contêm e consequentemente ajudar o hospital português em questão envolvido nesta dissertação, demonstrando também que este sistema protótipo e esta abordagem podem potencialmente ser aplicados a outros hospitais, mesmo que não sejam de língua portuguesa

Towards multilingual domain module acquisition

Máster y Doctorado en Sistemas Informáticos Avanzados, Informatika Fakultatea - Facultad de InformáticaDOM-Sortze is a framework for Semi-Automatic development of Domain Modules, i.e., the pedagogical representation of the domain to be learnt. DOM-Sortze generates Domain Modules for Technology Supported Learning Systems using Natural Language Processing Techniques, Ontologies and Heuristic Reasoning. The framework has been already used over textbooks in Basque language. This work presents the extension that adds English support to the framework, which is achieved with the modification of ErauzOnt. This is the tool that enables the acquisition of learning resources, definitions, examples, exercises, etc. used in the learning process. Moreover, some tests have been made to evaluate the performance of the tool with this new language. Principles of Object-Oriented Programming textbook for Object-Oriented Programming university subject is used for evaluation purposes. The results of this tests show that DOM-Sortze is not tight to a particular domain neither language

ISR@bucknell

isr@bucknell was a newsletter published by Bucknell University\u27s Information Services and Resources department (later Library and Information Technology). The publication served the community by providing software, project, and service updates. Regular features included a letter from the Associate Vice President for Information Services and Resources, the Ask ISR column, and featured ISR web pages. This issue includes the following articles: Check Us Out, Meet the ISR Staff, Finding Our Voice, Getting Beyond the Mainstream, Departmental Cellular Loaners, New Member of Client Services, Government Information on the Web, Virus Update, Voice Mail on the Web, Have You Heard? Turnitin, ERes v4, Revealing Alerts, Wandering Our Web Site

Constructive Ontology Engineering

The proliferation of the Semantic Web depends on ontologies for knowledge sharing, semantic annotation, data fusion, and descriptions of data for machine interpretation. However, ontologies are difficult to create and maintain. In addition, their structure and content may vary depending on the application and domain. Several methods described in literature have been used in creating ontologies from various data sources such as structured data in databases or unstructured text found in text documents or HTML documents. Various data mining techniques, natural language processing methods, syntactical analysis, machine learning methods, and other techniques have been used in building ontologies with automated and semi-automated processes. Due to the vast amount of unstructured text and its continued proliferation, the problem of constructing ontologies from text has attracted considerable attention for research. However, the constructed ontologies may be noisy, with missing and incorrect knowledge. Thus ontology construction continues to be a challenging research problem. The goal of this research is to investigate a new method for guiding a process of extracting and assembling candidate terms into domain specific concepts and relationships. The process is part of an overall semi automated system for creating ontologies from unstructured text sources and is driven by the user’s goals in an incremental process. The system applies natural language processing techniques and uses a series of syntactical analysis tools for extracting grammatical relations from a list of text terms representing the parts of speech of a sentence. The extraction process focuses on evaluating the subject predicate-object sequences of the text for potential concept-relation-concept triples to be built into an ontology. Users can guide the system by selecting seedling concept-relation-concept triples to assist building concepts from the extracted domain specific terms. As a result, the ontology building process develops into an incremental one that allows the user to interact with the system, to guide the development of an ontology, and to tailor the ontology for the user’s application needs. The main contribution of this work is the implementation and evaluation of a new semi- automated methodology for constructing domain specific ontologies from unstructured text corpus

Strategies of Translating Political Texts with Particular Reference to English and Italian

The difference between Italian and English language and the variation in their cultures make the process of translating a real challenge. Because of the inherent differences between Italian language and English language, a perfect translation is impossible. It is the nature of languages. So many words in Italian have nuances, connotations, even literary echoes which their closest equivalent words in English do not have. Thus, this paper aims at probing – by encountering the problems that a translator may encounter while translating political texts from Italian into English. For this purpose, we have chosen to translate  into English the following chapter from Roman Prodi's book entitled La Mia Visione Dei Fatti Cinque anni di governo in Europa. Throughout our paper, we have tried to demonstrate some translation problems that we have encountered while translating from Italian into English language. Our translation will enable us to explore the potential strategies to overcome the lexico-grammatical differences between Italian and English language and to illustrate the linguistic reasoning behind translation. On a second level, we will  discuss the various ways translator dealt with structural and lexical differences between the two languages English and Italian. Keywords: Translation, Italian, English, Strategie

English for Computing II

Навчальний посібник містить фахові тексти, лексичні та граматичні вправи комунікативного спрямування. Посібник також укомплектований аудіокурсом, що дає змогу використовувати автентичні записи зі спеціальності з метою формування навичок аудіювання. Призначається для студентів, що вивчають комп’ютерні науки