Knowledge modelling of emerging technologies for sustainable building development

In the quest for improved performance of buildings and mitigation of climate change, governments are encouraging the use of innovative sustainable building technologies. Consequently, there is now a large amount of information and knowledge on sustainable building technologies over the web. However, internet searches often overwhelm practitioners with millions of pages that they browse to identify suitable innovations to use on their projects. It has been widely acknowledged that the solution to this problem is the use of a machine-understandable language with rich semantics - the semantic web technology. This research investigates the extent to which semantic web technologies can be exploited to represent knowledge about sustainable building technologies, and to facilitate system decision-making in recommending appropriate choices for use in different situations. To achieve this aim, an exploratory study on sustainable building and semantic web technologies was conducted. This led to the use of two most popular knowledge engineering methodologies - the CommonKADS and "Ontology Development 101" in modelling knowledge about sustainable building technology and PV -system domains. A prototype system - Photo Voltaic Technology ONtology System (PV -TONS) - that employed sustainable building technology and PV -system domain knowledge models was developed and validated with a case study. While the sustainable building technology ontology and PV -TONS can both be used as generic knowledge models, PV -TONS is extended to include applications for the design and selection of PV -systems and components. Although its focus was on PV -systems, the application of semantic web technologies can be extended to cover other areas of sustainable building technologies. The major challenges encountered in this study are two-fold. First, many semantic web technologies are still under development and very unstable, thus hindering their full exploitation. Second, the lack of learning resources in this field steepen the learning curve and is a potential set-back in using semantic web technologies

A Goal-Directed and Policy-Based Approach to System Management

This thesis presents a domain-independent approach to dynamic system management using goals and policies. A goal is a general, high-level aim a system must continually work toward achieving. A policy is a statement of how a system should behave for a given set of detectable events and conditions. Combined, goals may be realised through the selection and execution of policies that contribute to their aims. In this manner, a system may be managed using a goal-directed, policy-based approach. The approach is a collection of related techniques and tools: a policy language and policy system, goal definition and refinement via policy selection, and conflict filtering among policies. Central to these themes, ontologies are used to model application domains, and incorporate domain knowledge within the system. The ACCENT policy system (Advanced Component Control Enhancing Network Technologies, http://www.cs.stir.ac.uk/accent) is used as a base for the approach, while goals and policies are defined using an extension of APPEL (Adaptable and Programmable Policy Environment and Language, http://www.cs.stir.ac.uk/appel). The approach differs from existing work in that it reduces system state, goals and policies to a numerical rather than logical form. This is more user-friendly as the goal domain may be expressed without any knowledge of formal methods. All developed techniques and tools are entirely domain-independent, allowing for reuse with other event-driven systems. The ability to express a system aim as a goal provides more powerful and proactive high-level management than was previously possible using policies alone. The approach is demonstrated and evaluated within this thesis for the domains of Internet telephony and sensor network/wind turbine management

Java API-Aware Code Generation Engine: A Prototype

Software reuse enhances a programmer\u27s productivity and reduces programming errors. Improving software reuse through libraries and frameworks is a vast problem area. This thesis offers an approach to solve two sub-problems within the problem area- to identify the right library components, and to offer code snippets that use the components correctly. The Java API-Aware Code Generation Engine, or JAGE for short, is a prototype system that demonstrates the feasibility of generating semantically valid code snippets consisting of method calls to classes in the J2SDK library. Developers often search for sample code snippets that describe how to use the library. This thesis describes the design and implementation of JAGE, which allows software developers to use an English sentence to generate helpful code snippets in Java. This thesis also discusses the related concepts in natural-language processing including ontology, Wordnet, and object-orientation in the area of automatic code snippet generation

Source authoring for multilingual generation of personalised object descriptions

We present the source authoring facilities of a natural language generation system that produces personalised descriptions of objects in multiple natural languages starting from language-independent symbolic information in ontologies and databases as well as pieces of canned text. The system has been tested in applications ranging from museum exhibitions to presentations of computer equipment for sale. We discuss the architecture of the overall system, the resources that the authors manipulate, the functionality of the authoring facilities, the system's personalisation mechanisms, and how they relate to source authoring. A usability evaluation of the authoring facilities is also presented, followed by more recent work on reusing information extracted from existing databases and documents, and supporting the owl ontology specification language

A multiagent architecture for semantic query access to legacy relational databases.

This thesis proposes a novel approach to accessing information stored in legacy relational databases (RDB), based on Semantic Web and multiagent systems technologies. It introduces an architectural model of the Semantic Report Generation System (SRGS), designed to address the rising demand for flexible access to information in decision support systems. SRGS is composed of server Database Subsystems (DBS) and client User Subsystems (US). In a DBS, an agent interacts with the administrator to build a reference ontology from the RDB schema, which enables semantic queries without modifying the database. In a US, the decision-making user accesses the system through a simplified natural language interface, using customized extensions to the reference ontology that was imported from DBS an agent helps build the custom ontology, and facilitates query formulation and report generation. The proposed approach is illustrated by several scenarios that highlight the key behavioral aspects of accessing information and developing ontologies. --P. ii.The original print copy of this thesis may be available here: http://wizard.unbc.ca/record=b178456

Automatically selecting patients for clinical trials with justifications

Clinical trials are human research studies that are used to evaluate the effectiveness of a surgical, medical, or behavioral intervention. They have been widely used by researchers to determine whether a new treatment, such as a new medication, is safe and effective in humans. A clinical trial is frequently performed to determine whether a new treatment is more successful than the current treatment or has less harmful side effects. However, clinical trials have a high failure rate. One method applied is to find patients based on patient records. Unfortunately, this is a difficult process. This is because this process is typically performed manually, making it time-consuming and error-prone. Consequently, clinical trial deadlines are often missed, and studies do not move forward. Time can be a determining factor for success. Therefore, it would be advantageous to have automatic support in this process. Since it is also important to be able to validate whether the patients were selected correctly for the trial, avoiding eventual health problems, it would be important to have a mechanism to present justifications for the selected patients. In this dissertation, we present one possible solution to solve the problem of patient selection for clinical trials. We developed the necessary algorithms and created a simple and intuitive web application that features the selection of patients for clinical trials automatically. This was achieved by combining knowledge expressed in different formalisms. We integrated medical knowledge using ontologies, with criteria that were expressed using nonmonotonic rules. To address the validation procedure automatically, we developed a mechanism that generates the justifications for each selection together with the results of the patients who were selected. In the end, it is expected that a user can easily enter a set of trial criteria, and the application will generate the results of the selected patients and their respective justifications, based on the criteria inserted, medical information and a database of patient information.Os ensaios clínicos são estudos de pesquisa em humanos, utilizados para avaliar a eficácia de uma intervenção cirúrgica, médica ou comportamental. Estes estudos, têm sido amplamente utilizados pelos investigadores para determinar se um novo tratamento, como é o caso de um novo medicamento, é seguro e eficaz em humanos. Um ensaio clínico é realizado frequentemente, para determinar se um novo tratamento tem mais sucesso do que o tratamento atual ou se tem menos efeitos colaterais prejudiciais. No entanto, os ensaios clínicos têm uma taxa de insucesso alta. Um método aplicado é encontrar pacientes com base em registos. Infelizmente, este é um processo difícil. Isto deve-se ao facto deste processo ser normalmente realizado à mão, o que o torna demorado e propenso a erros. Consequentemente, o prazo dos ensaios clínicos é muitas vezes ultrapassado e os estudos acabam por não avançar. O tempo pode ser por vezes um fator determinante para o sucesso. Seria então vantajoso ter algum apoio automático neste processo. Visto que também seria importante validar se os pacientes foram selecionados corretamente para o ensaio, evitando até eventuais problemas de saúde, seria importante ter um mecanismo que apresente justificações para os pacientes selecionados. Nesta dissertação, apresentamos uma possível solução para resolver o problema da seleção de pacientes para ensaios clínicos, através da criação de uma aplicação web, intuitiva e fácil de utilizar, que apresenta a seleção de pacientes para ensaios clínicos de forma automática. Isto foi alcançado através da combinação de conhecimento expresso em diferentes formalismos. Integrámos o conhecimento médico usando ontologias, com os critérios que serão expressos usando regras não monotónicas. Para tratar do processo de validação, desenvolvemos um mecanismo que gera justificações para cada seleção juntamente com os resultados dos pacientes selecionados. No final, é esperado que o utilizador consiga inserir facilmente um conjunto de critérios de seleção, e a aplicação irá gerar os resultados dos pacientes selecionados e as respetivas justificações, com base nos critérios inseridos, informações médicas e uma base de dados com informações dos pacientes

Ontology-based services for agents interoperability

Tese de doutoramento. Engenharia Electrotécnica e de Computadores. 2006. Faculdade de Engenharia. Universidade do Port

A Sensor Ontology For The Domain Of Firefighting Robots

Fires create thousands of dollars in damage and thousands of deaths each year. Firefighters risk their lives everyday and are often killed in action. Firefighting robots may be able to reduce the loss of lives and damage due to fires. Robots are often used for redundant tasks that require the consistency and efficiency of a machine. They are especially optimal for tasks that require strength that exceeds that of a typical human being or for environments that are hazardous to people. Robots\u27 metallic exteriors are far more durable and easier to replace than flesh and blood, thus they are ideal for fighting fire that may be unreachable or too dangerous for humaning beings. Firefighting robots are most often shaped like tanks and are equipped with fire extinguishers, sensors, and cameras. The robots are typically operated via remote control and lack autonomy. Because of the volatile nature of fires, it is difficult for software engineers to create algorithms to make firefighting robots more autonomous. Ontologies are commonly used for sharing domain information and structuring and analyzing data. This study proposes using an ontology that is designed specifically for a firefighting robot programmed to rescue a human in danger in order to make a decision making algorithm. The methodology uses ontological tools to build the ontology. A decision-making algorithm is created using the information that is stored in the ontology. The study is evaluated on the accuracy rate of making the correct decision. It is also evaluated on if the decision-making algorithm performs significantly better than decisions chosen at random