915 resultados para Knowledge base maintenance
Resumo:
El sistema de fangs activats és el tractament biològic més àmpliament utilitzat arreu del món per la depuració d'aigües residuals. El seu funcionament depèn de la correcta operació tant del reactor biològic com del decantador secundari. Quan la fase de sedimentació no es realitza correctament, la biomassa no decantada s'escapa amb l'efluent causant un impacte sobre el medi receptor. Els problemes de separació de sòlids, són actualment una de les principals causes d'ineficiència en l'operació dels sistemes de fangs activats arreu del món. Inclouen: bulking filamentós, bulking viscós, escumes biològiques, creixement dispers, flòcul pin-point i desnitrificació incontrolada. L'origen dels problemes de separació generalment es troba en un desequilibri entre les principals comunitats de microorganismes implicades en la sedimentació de la biomassa: els bacteris formadors de flòcul i els bacteris filamentosos. Degut a aquest origen microbiològic, la seva identificació i control no és una tasca fàcil pels caps de planta. Els Sistemes de Suport a la Presa de Decisions basats en el coneixement (KBDSS) són un grup d'eines informàtiques caracteritzades per la seva capacitat de representar coneixement heurístic i tractar grans quantitats de dades. L'objectiu de la present tesi és el desenvolupament i validació d'un KBDSS específicament dissenyat per donar suport als caps de planta en el control dels problemes de separació de sòlids d'orígen microbiològic en els sistemes de fangs activats. Per aconseguir aquest objectiu principal, el KBDSS ha de presentar les següents característiques: (1) la implementació del sistema ha de ser viable i realista per garantir el seu correcte funcionament; (2) el raonament del sistema ha de ser dinàmic i evolutiu per adaptar-se a les necessitats del domini al qual es vol aplicar i (3) el raonament del sistema ha de ser intel·ligent. En primer lloc, a fi de garantir la viabilitat del sistema, s'ha realitzat un estudi a petita escala (Catalunya) que ha permès determinar tant les variables més utilitzades per a la diagnosi i monitorització dels problemes i els mètodes de control més viables, com la detecció de les principals limitacions que el sistema hauria de resoldre. Els resultats d'anteriors aplicacions han demostrat que la principal limitació en el desenvolupament de KBDSSs és l'estructura de la base de coneixement (KB), on es representa tot el coneixement adquirit sobre el domini, juntament amb els processos de raonament a seguir. En el nostre cas, tenint en compte la dinàmica del domini, aquestes limitacions es podrien veure incrementades si aquest disseny no fos òptim. En aquest sentit, s'ha proposat el Domino Model com a eina per dissenyar conceptualment el sistema. Finalment, segons el darrer objectiu referent al seguiment d'un raonament intel·ligent, l'ús d'un Sistema Expert (basat en coneixement expert) i l'ús d'un Sistema de Raonament Basat en Casos (basat en l'experiència) han estat integrats com els principals sistemes intel·ligents encarregats de dur a terme el raonament del KBDSS. Als capítols 5 i 6 respectivament, es presenten el desenvolupament del Sistema Expert dinàmic (ES) i del Sistema de Raonament Basat en Casos temporal, anomenat Sistema de Raonament Basat en Episodis (EBRS). A continuació, al capítol 7, es presenten detalls de la implementació del sistema global (KBDSS) en l'entorn G2. Seguidament, al capítol 8, es mostren els resultats obtinguts durant els 11 mesos de validació del sistema, on aspectes com la precisió, capacitat i utilitat del sistema han estat validats tant experimentalment (prèviament a la implementació) com a partir de la seva implementació real a l'EDAR de Girona. Finalment, al capítol 9 s'enumeren les principals conclusions derivades de la present tesi.
Resumo:
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.
Resumo:
We are experiencing an explosion of knowledge with relevance to conserving biodiversity and protecting the environment necessary to sustain life on earth. Many science disciplines are involved in generating this ne, knowledge and real progress can be made when scientists collaborate across disciplines to generate both macro- and micro-environmental knowledge and then communicate and interact with specialists in sociology, economics and public policy. An important requirement is that the often complex scientific concepts and their voluminous supporting data are managed in such ways as to make them accessible across the many specializations involved. Horticultural science has much to contribute to the knowledge base for environmental conservation. While it seems that production horticulture has been slow to embrace knowledge and concepts that would reduce the heavy reliance on agricultural chemicals, the use of peat as a growing medium, and lead to more sustainable use of water and other resources, environmental horticulture is providing valuable opportunities to rescue or protect endangered species, educate the public about plants and plant science, and demonstrate environmental stewardship and sustainable production practices. Likewise, social horticulture is drawing, attention to the many contributions of horticultural foods and parks and gardens to human health and welfare. Overall, horticulture has a vital role to play in integrating, knowledge from other scientific, social, economic and political disciplines.
Resumo:
Belief Revision deals with the problem of adding new information to a knowledge base in a consistent way. Ontology Debugging, on the other hand, aims to find the axioms in a terminological knowledge base which caused the base to become inconsistent. In this article, we propose a belief revision approach in order to find and repair inconsistencies in ontologies represented in some description logic (DL). As the usual belief revision operators cannot be directly applied to DLs, we propose new operators that can be used with more general logics and show that, in particular, they can be applied to the logics underlying OWL-DL and Lite.
Resumo:
The knowledge management has received major attention from product designers because many of the activities within this process have to be creative and, therefore, they depend basically on the knowledge of the people who are involved in the process. Moreover, Product Development Process (PDP) is one of the activities in which knowledge management manifests in the most critical form once it had the intense application of the knowledge. As a consequence, this thesis analyzes the knowledge management aiming to improve the PDP and it also proposes a theoretical model of knowledge management. This model uses five steps (creation, maintenance, dissemination, utilization and discard) through the verification of the occurrence of four types of knowledge conversion (socialization, externalization, combination and internalization) that it will improve the knowledge management in this process. The intellectual capital in Small and Medium Enterprises (SMEs) managed efficiently and with the participation of all employees has become the mechanism of the creation and transference processes of knowledge, supporting and, consequently, improving the PDP. The expected results are an effective and efficient application of the proposed model for the creation of the knowledge base within an organization (organizational memory) aiming a better performance of the PDP. In this way, it was carried out an extensive analysis of the knowledge management (instrument of qualitative and subjective evaluation) within the Design department of a Brazilian company (SEBRAE/RN). This analysis aimed to know the state-of-the-art of the Design department regarding the use of knowledge management. This step was important in order to evaluate in the level of the evolution of the department related to the practical use of knowledge management before implementing the proposed theoretical model and its methodology. At the end of this work, based on the results of the diagnosis, a knowledge management system is suggested to facilitate the knowledge sharing within the organization, in order words, the Design department
Resumo:
The knowledge management has received major attention from product designers because many of the activities within this process have to be creative and, therefore, they depend basically on the knowledge of the people who are involved in the process. Moreover, Product Development Process (PDP) is one of the activities in which knowledge management manifests in the most critical form once it had the intense application of the knowledge. As a consequence, this thesis analyzes the knowledge management aiming to improve the PDP and it also proposes a theoretical model of knowledge management. This model uses five steps (creation, maintenance, dissemination, utilization and discard) through the verification of the occurrence of four types of knowledge conversion (socialization, externalization, combination and internalization) that it will improve the knowledge management in this process. The intellectual capital in Small and Medium Enterprises (SMEs) managed efficiently and with the participation of all employees has become the mechanism of the creation and transference processes of knowledge, supporting and, consequently, improving the PDP. The expected results are an effective and efficient application of the proposed model for the creation of the knowledge base within an organization (organizational memory) aiming a better performance of the PDP. In this way, it was carried out an extensive analysis of the knowledge management (instrument of qualitative and subjective evaluation) within the Design department of a Brazilian company (SEBRAE/RN). This analysis aimed to know the state-of-the-art of the Design department regarding the use of knowledge management. This step was important in order to evaluate in the level of the evolution of the department related to the practical use of knowledge management before implementing the proposed theoretical model and its methodology. At the end of this work, based on the results of the diagnosis, a knowledge management system is suggested to facilitate the knowledge sharing within the organization, in order words, the Design department
Resumo:
Family preservation has been criticized for implementing programs that are not theoretically founded. One result of this circumstance is a lack of information regarding processes and outcomes of family preservation services. The knowledge base of family preservation is thus rather limited at present and will remain limited unless theory is consistently integrated within individual programs. A model for conceptualizing how theoretical consistency may be implemented within programs is presented and applied to family preservation. It is also necessary for programs to establish theoretical consistency before theoretical diversity, both within individual and across multiple programs, in order to advance the field in meaningful ways. A developmental cycle of knowledge generation is presented and applied to family preservation.
Resumo:
Our research project develops an intranet search engine with concept- browsing functionality, where the user is able to navigate the conceptual level in an interactive, automatically generated knowledge map. This knowledge map visualizes tacit, implicit knowledge, extracted from the intranet, as a network of semantic concepts. Inductive and deductive methods are combined; a text ana- lytics engine extracts knowledge structures from data inductively, and the en- terprise ontology provides a backbone structure to the process deductively. In addition to performing conventional keyword search, the user can browse the semantic network of concepts and associations to find documents and data rec- ords. Also, the user can expand and edit the knowledge network directly. As a vision, we propose a knowledge-management system that provides concept- browsing, based on a knowledge warehouse layer on top of a heterogeneous knowledge base with various systems interfaces. Such a concept browser will empower knowledge workers to interact with knowledge structures.
Resumo:
Native trees and shrubs are essential components of rural landscapes in the semi-arid inner-Andean valleys of Bolivia. They can be found as hedges and bushes in various agroecosystems such as terrace walls, slopes, field boundaries and fallow land. Their distribution and floristic composition are the result of dynamic spatial and temporal interactions between local farmers and the environment. Local uses of natural resources and biodiversity reflect the constantly evolving Andean culture, which can be generally characterised as an intertwining of the human, natural, and spiritual worlds. The aim of the present ethnobotanical study was to analyse the dynamics of traditional ecological knowledge, to ascertain local farmers’ perceptions and uses of native woody species in Andean communities and to associate the results with local conservation activities for the trees and shrubs concerned. Our case study was carried out within two communities of the Tunari National Park (Dept. Cochabamba) in Bolivia. For data collection, research methods from social science (semi-structured interviews, participative observation, participatory mapping) as well as vegetation surveys were combined. Local actors included women and men of all ages as well as families from different social categories and altitudinal levels of permanent residence. Our study indicates that, due to a multitude of socio-economic pressures (e.g. migration of young people) as well as changes in use of biodiversity (e.g. replacement of native by exotic introduced species), the traditional ecological knowledge base of native trees and shrubs and their respective uses has become diminished over time. In many cases it has led to a decline in people’s awareness of native species and as a consequence their practical, emotional and spiritual relationships with them have been lost. However, results also show that applied traditional ecological knowledge has led to local conservation strategies, which have succeeded in protecting those tree and shrub species which are most widely regarded for their multifunctional, constant and exclusive uses (e.g. Schinus molle, Prosopis laevigata, Baccharis dracunculifolia). The presentation will discuss the question if and how applied traditional ecological knowledge positively contributes to local initiatives of sustainable use and conservation of biodiversity in rural areas.
Resumo:
The paper presents the results of a multi-year baseline study project in which 10 sectors ranging from agriculture to natural hazards were assessed by a transdisciplinary Swiss–Tajik research team. This knowledge base was enhanced in a development strategy workshop that brought together stakeholders from the local to the international levels. The methodology applied was found appropriate to initiate a broad reflection and negotiation process among various stakeholder groups, leading to a joint identification of possible measures to be taken. Knowledge—and its enhancement through the involvement of all stakeholder levels— appeared to be an effective carrier of innovation and changes of attitudes, thus containing the potential to effectively contribute to sustainable development in marginalized and resource-poor mountain areas.
Resumo:
Folksonomies emerge as the result of the free tagging activity of a large number of users over a variety of resources. They can be considered as valuable sources from which it is possible to obtain emerging vocabularies that can be leveraged in knowledge extraction tasks. However, when it comes to understanding the meaning of tags in folksonomies, several problems mainly related to the appearance of synonymous and ambiguous tags arise, specifically in the context of multilinguality. The authors aim to turn folksonomies into knowledge structures where tag meanings are identified, and relations between them are asserted. For such purpose, they use DBpedia as a general knowledge base from which they leverage its multilingual capabilities.
Resumo:
In the last decades, neuropsychological theories tend to consider cognitive functions as a result of the whole brainwork and not as individual local areas of its cortex. Studies based on neuroimaging techniques have increased in the last years, promoting an exponential growth of the body of knowledge about relations between cognitive functions and brain structures [1]. However, so fast evolution make complicated to integrate them in verifiable theories and, even more, translated in to cognitive rehabilitation. The aim of this research work is to develop a cognitive process-modeling tool. The purpose of this system is, in the first term, to represent multidimensional data, from structural and functional connectivity, neuroimaging, data from lesion studies and derived data from clinical intervention [2][3]. This will allow to identify consolidated knowledge, hypothesis, experimental designs, new data from ongoing studies and emerging results from clinical interventions. In the second term, we pursuit to use Artificial Intelligence to assist in decision making allowing to advance towards evidence based and personalized treatments in cognitive rehabilitation. This work presents the knowledge base design of the knowledge representation tool. It is compound of two different taxonomies (structure and function) and a set of tags linking both taxonomies at different levels of structural and functional organization. The remainder of the abstract is organized as follows: Section 2 presents the web application used for gathering necessary information for generating the knowledge base, Section 3 describes knowledge base structure and finally Section 4 expounds reached conclusions.
Resumo:
This paper presents a method for identifying concepts in microposts and classifying them into a predefined set of categories. The method relies on the DBpedia knowledge base to identify the types of the concepts detected in the messages. For those concepts that are not classified in the ontology we infer their types via the ontology properties which characterise the type.
Resumo:
Decision support systems (DSS) support business or organizational decision-making activities, which require the access to information that is internally stored in databases or data warehouses, and externally in the Web accessed by Information Retrieval (IR) or Question Answering (QA) systems. Graphical interfaces to query these sources of information ease to constrain dynamically query formulation based on user selections, but they present a lack of flexibility in query formulation, since the expressivity power is reduced to the user interface design. Natural language interfaces (NLI) are expected as the optimal solution. However, especially for non-expert users, a real natural communication is the most difficult to realize effectively. In this paper, we propose an NLI that improves the interaction between the user and the DSS by means of referencing previous questions or their answers (i.e. anaphora such as the pronoun reference in “What traits are affected by them?”), or by eliding parts of the question (i.e. ellipsis such as “And to glume colour?” after the question “Tell me the QTLs related to awn colour in wheat”). Moreover, in order to overcome one of the main problems of NLIs about the difficulty to adapt an NLI to a new domain, our proposal is based on ontologies that are obtained semi-automatically from a framework that allows the integration of internal and external, structured and unstructured information. Therefore, our proposal can interface with databases, data warehouses, QA and IR systems. Because of the high NL ambiguity of the resolution process, our proposal is presented as an authoring tool that helps the user to query efficiently in natural language. Finally, our proposal is tested on a DSS case scenario about Biotechnology and Agriculture, whose knowledge base is the CEREALAB database as internal structured data, and the Web (e.g. PubMed) as external unstructured information.
Resumo:
Thesis (Ph.D.)--University of Washington, 2016-06