Magistriniame darbe nagrinėjamas pakartotinis informacijos ir žinių panaudojimas IT pagalbos tarnybose. Trumpai apžvelgti svarbiausi tokio tipo organizacijų veiklos principai, kurie standartizuojami taikant ITIL metodologiją. Darbo tikslas – sukurti IT trikčių registravimo sistemą, kuri panaudodama sukauptą informaciją apie praeityje įvykusias IT triktis spręstų dabartines problemas. Siekiant šio tikslo pasirinkta taikyti neraiškiąją logiką ir atveju paremtą samprotavimą. Darbe pateikiama neraiškiosios logikos ir atveju paremto samprotavimo teorinė apžvalga ir praktinės pritaikymo galimybės, apžvelgiamos intelektualios IT trikčių registravimo sistemos. Atlikus tyrimą ir įvertinus anksčiau sukurtas intelektualias IT trikčių registravimo sistemas, formuojamas naujosios modelis. Nauja sistema, pritaikiusi atveju paremtą samprotavimą ir neraiškiąją logiką, pateikia galimus IT trikčių sprendimus jos naudotojui, tai yra IT pagalbos tarnybos darbuotojui. Sistema yra nepriklausoma nuo kalbos, nes atskirų atvejų paieška vykdoma taikant neraiškiąją logiką. Darbą sudaro 4 dalys: įvadas, IT organizacijos pagal ITIL samprata, teorinė neraiškiosios logikos ir atveju paremto samprotavimo apžvalga, praktinis neraiškiosios logikos pritaikymas IT trikčių registravime bei išvados ir siūlymai, literatūros sąrašas. Darbo apimtis – 75 p. teksto be priedų, 26 iliustr., 5 lent., 60 bibliografiniai šaltiniai. Atskirai pridedami darbo priedai. / The final Master thesis analyses the reuse of information and knowledge in IT helpdesk organizations. Briefly are discussed most important activities of such companies, that are standardized according ITIL. The main goal of the Master thesis is development of IT help-desk ticketing tool, which would reuse past information and knowledge in order to resolve current problems. Adaptation of fuzzy logic and case based reasoning is chosen to accomplish this goal. The second part of work contains theoretical information about fuzzy logic and cased based reasoning, practical application of these sciences; also discusses intelligent IT help-desk incident ticketing systems. After the research of scientific articles about intelligent IT help-desk systems and application of fuzzy logic and case based reasoning, the new model of IT trouble tickets system is created. The new system suggests possible solutions of an IT incident. The solution is found among previous incidents using fuzzy logic. Volume of the thesis – 75 p. of text without appendices, 26 figures, 5 tables, 60 bibliographic sources.

Companies struggle against complex and dynamic conditions in order to survive in their business settings. Being in the knowledge era, learning has been accepted as one of the main sources of sustainable competitive advantage. Organizational learning (OL) is a set of activities to obtain organizational memory (OM) by acquiring, sharing, interpreting, integrating and institutionalizing knowledge. OM is exploited by the companies in strategic decision-making process, which makes OL a critical concept. The major objective of this study is to explore how construction companies create OM and how they exploit this asset in strategic decision-making process. In this context, an interview study is conducted with eight large Turkish construction companies and OM perceptions of each company are presented as case studies. This survey revealed the strengths and weaknesses in terms of OL competence. One of the key outputs is that companies are successful at acquiring and storing knowledge but they are not familiar with decision support systems (DSSs) that benefit from OM. Such systems enable OL by assisting decision makers in processing, assessing, integrating and organizing knowledge. To meet the requirements of the industry, a DSS is proposed to aid construction companies in international market entry decisions. This tool is generated under a software package by adopting case-based reasoning (CBR) as the problem solving approach, which finds solutions to new problems based on the past experiences. The model is developed by the acquisition of past real international project data as input information. The model produces two outputs that are indicators of attractiveness of a project and competitiveness of a company, which are the key decision criteria in international market entry problem.

La recerca presentada en aquesta dissertació glossa sobre transformacions de tempo de gravacions monofòniques de saxo jazz preservant l'expressivitat musical. Es una contribució al processament d'audio basat en el contingut, un camp de recerca que ha emergit recentment com a resposta a la necessitat creixent de gestionar intel·ligentment la creixent quantitat d'informació digital multimedia disponible actualment. S'ha investigat com una execució musical, tocada a un tempo concret, es pot reproduir automàticament a un altre tempo mantenint l'expressivitat. Aquest problema no es pot reduir a aplicar una transformació uniforme a totes les notes de la melodia, operació que degradaria la qualitat de l'execució. Proposem un sistema de raonament basat en casos per a transformacions de tempo preservant l'expressivitat. La validació del sistema mostra un comportament superior a la transformació uniforme. A m'es, s'han fet contribucions a l'anàlisi de gravacions expressives, CBR, recuperació de melodies i metodologires d'evaluació de models d'expressivitat. / The research presented in this dissertation focuses on expressivity-aware tempo transformations of monophonic audio recordings of saxophone jazz performances. It is a contribution to content-based audio processing, a field of technology that has recently emerged as an answer to the increased need to deal intelligently with the evergrowing amount of digital multimedia information available nowadays. We have investigated the problem of how a musical performance played at a particular tempo can be rendered automatically at another tempo, while preserving naturally sounding expressivity. This problem cannot be reduced to just applying a uniform transformation to all notes of the melody, since it often degrades the musical quality of the performance. We present a case-based reasoning system for expressivity aware tempo transformations. A validation of the system showed superior results compared to uniform transformation. Furthermore, contributions have been made to expressive performance analysis, CBR, melody retrieval, and evaluation methodologies of expressive models.

Thesis (Ph.D.)--Stanford University, 1992. / Includes bibliographical references (leaves 236-249).

L'objet de cette thèse est de développer une approche d’aide à la constitution et aux choix des équipes multidisciplinaires. Deux méthodologies ont été développées afin d’apporter une contribution au le domaine du management des équipes d’une manière générale et aux systèmes hospitaliers particulièrement. Nous nous sommes intéressés dans la conception de ces méthodologies aux méthodes d’aide à la décision multicritère et aux méthodes cognitives. La première méthodologie TBS 1, se base sur les expériences des opérations passées afin de fournir l’équipe adéquate pour une nouvelle opération. Nous développons une hybridation entre un outil d’aide à la décision multicritères AHP et une méthode cognitive RàPC. Dans une deuxième méthodologie TBS 2, nous combinons deux méthodes d’aide à la décision multicritères AHP et ELECTRE afin de proposer aux responsables la meilleure équipe et les liens avec les autres équipes. Pour valider ces deux démarches, nous les avons expérimentées en bloc opératoire de CHU Habib Bourguiba. Bien qu’un certain nombre de limites ait pu être mis en évidence, les retours terrain nous amènent à penser que l’intérêt des deux démarches d’aide à la constitution et au choix des équipes dans le bloc opératoire semble validé. / The subject of this thesis is to develop a support approach to the constitution and to the choices of the multidisciplinary teams. Two methodologies have been developed in order to provide a contribution to the domain of the team management in a general manner and to the hospital systems particularly. We are interested in the conception of these methodologies in the support method to the multi-criterion decision and to the cognitive methods.The first methodology TBS 1, is based on the experiences of the past operations in order to supply the adequate team for a new operation. We develop hybridization between the support tool to the multi-criterion decision AHP and a cognitive method CBR. In a second methodology TBS 2, we combine two support methods to the multi-criterion decision AHP and ELECTRE in order to suggest to the persons in charge the best team and the links with the other teams.In order to approve these two approaches, we have experimented them in the operating theatre of CHU Habib Bourguiba. Even though certain number of limits could be highlighted, the operation issues lead us to think that the interest of the two support approaches to the constitution and to the choices of the teams in the operating theatre seems to be approved.

Attempts to bridge the digital divide between urban and rural Information and Communications Technology (ICT) users have led to the deployment of ICT platforms in remote rural areas. This puts an increased demand for skilled support in rural ICT platforms to assist users in resolving technical problems that they face on a daily basis. A web based help desk system is developed and implemented to allow knowledge sharing and collaboration amongst users and experts as a way of ensuring the technical sustainability of the Siyakhula Living Lab, a remote rural based Information and Communications Technology (ICT4D) intervention. The research describes the use of Transactional and Innovation & Creative knowledge management strategies and their associated applications such as case-based reasoning (CBR) methods and collaborative knowledge approaches to develop a help desk support system for a geographically distributed multipurpose ICT centre in Dwesa, a rural remote area in the Eastern Cape Province, South Africa. The system implemented in this study has been validated for functional adequacy and usability within the Siyakhula Living Lab. The results of the evaluation are presented in this thesis to provide the initial validation of the effectiveness of the help desk system. Keywords: ICT4D, ICT, Case-Based Reasoning; Collaborative Knowledge, Technical Sustainability, Help Desk Systems, Siyakhula Living Lab Forums, Issue Tracking, Rural Users, South Africa

Uma questão que se apresenta relevante, nesta tese, é que na maioria das vezes, o estudante, principalmente, o novato, demonstra grande dificuldade na aprendizagem baseada na resolução de problemas. Portanto, este precisa de monitoração, isto exige um apoio de entidades ou pessoas mais experientes. Percebe-se que, muitas vezes, por falta de domínio na área do conhecimento tratada, o estudante não analisa minuciosamente os dados do problema para poder conduzir objetivamente cada etapa de solução. Várias habilidades cognitivas são exigidas durante o processo de resolução de problemas, como por exemplo, codificação, comparação e combinação, componentes cognitivos significativos detectados em estudantes talentosos. A aprendizagem por meio do processo de resolução de problemas num ambiente online pode ampliar o pensamento crítico e aprimorar a tomada de decisão. Nesta pesquisa, foi criado um agente conversacional chamado Blaze, com o intuito de apoiar o estudante durante a aprendizagem autorregulada baseada na resolução de problemas. O agente foi desenvolvido com a linguagem de marcação AIML (Artificial Intelligence Markup Language), tendo sua base de conhecimento construída por meio da elicitação e representação dos processos cognitivos dos estudantes talentosos, alunos medalhistas da Olimpíada Brasileira de Matemática das Escolas Públicas. Utilizou-se a técnica de Raciocínio Baseado em Casos para permitir a recuperação e reutilização de experiências passadas dos estudantes talentosos. Foram realizados tantos experimentos com outros estudantes de graus de escolaridades distintos (2ª série do ensino médio, Licenciatura em Ciências e Licenciatura em Matemática) com o objetivo de investigar o engajamento e o aprimoramento das habilidades cognitivas destes durante a resolução dos problemas com a assistência do agente conversacional Blaze. Nestes experimentos, alguns estudantes interagiram com o agente Blaze durante o processo de resolução de problemas matemáticos, enquanto outros trabalharam sozinhos na resolução dos mesmos problemas. Os resultados obtidos nos experimentos permitiram verificar que o apoio do agente conversacional Blaze, no contexto de uma aprendizagem autorregulada durante a resolução de problemas, contribuiu qualitativamente para o aprimoramento de diversas habilidades cognitivas, como por exemplo, pensamento crítico, pensamento criativo, raciocínio lógico, bem como, permitiu o uso da metacognição. / A relevant issue raised in this paper is that most times students, especially inexperienced ones, show great difficulty for learning based on problem solving. Therefore, such students need to be monitored, which requires support from entities or more experienced people. Many times we see that due to students’ lack of mastery of the field of knowledge addressed, they fail to thoroughly analyze the problem data so as to objectively handle each stage of the solution. Several cognitive skills are required during the problem-solving process, such as coding, and comparison and combination, significant cognitive components detected in talented students. Learning by means of a problem-solving process in an online environment is capable of expanding critical thinking and improving students’ decision-making skills. In this research, a conversational agent we call Blaze was created in an effort to help students during their self-regulated, problem solving-based learning. The agent was developed via the AIML (Artificial Intelligence Markup Language), and its knowledge base was put together by means of eliciting and representing the cognitive processes of talented students, students who had won medals at the Brazilian Public School Mathematics Olympic Games. We used the Case-Based Reasoning technique to enable us to recover and reuse the talented students’ past experiences. Some other experiments were carried out with other students from various schooling levels (high school sophomores, and Science and Math undergrads) in order to look into those students’ engagement and improvement of their cognitive skills as they solved problems assisted by the Blaze conversational agent. In those experiments, some students interacted with the Blaze agent during the math problem-solving process, while other students worked alone on solving the same problems. The results obtained from the experiments allowed us to find that the support from the Blaze conversational agent, in the context of self-regulated learning during problem-solving, qualitatively helped the students improve their several cognitive skills, such as critical thinking, creative thinking, and logic reasoning, besides enabling the use of meta-cognition.

The performance of data manipulation through a search engine in e-commerce systems using decision support systems can be considered a complex process due to lots of information and may grow exponentially, according to research performed by the user for acquisition of equipment electronics. The import information collected by the system may influence the time to answer during the course of the search engine in accordance with the user s request. This works proposes a hybrid approach using database and genetic algorithm based on abstract data types (GAADT), to reduce the data of database dimensionality and helpful in the selection of products / O desempenho da manipulação dos dados por um sistema de apoio à decisão, em um ambiente de comércio eletrônico, pode ser considerado um processo complexo devido à grande quantidade de informação proveniente do mecanismo de busca adotado para aquisição de equipamentos eletroeletrônicos. Este processo poderá aumentar exponencialmente no decorrer do tempo devido ao crescimento que influenciará no tempo de resposta da execução das tarefas do mecanismo de busca para o usuário. Este trabalho propõe uma abordagem híbrida utilizando banco de dados e algoritmo genético baseado em tipos abstratos de dados, denominado GAADT, para reduzir a dimensionalidade dos dados providos em uma base de conhecimento e auxiliar nas negociações da obtenção de produtos

Uma questão que se apresenta relevante, nesta tese, é que na maioria das vezes, o estudante, principalmente, o novato, demonstra grande dificuldade na aprendizagem baseada na resolução de problemas. Portanto, este precisa de monitoração, isto exige um apoio de entidades ou pessoas mais experientes. Percebe-se que, muitas vezes, por falta de domínio na área do conhecimento tratada, o estudante não analisa minuciosamente os dados do problema para poder conduzir objetivamente cada etapa de solução. Várias habilidades cognitivas são exigidas durante o processo de resolução de problemas, como por exemplo, codificação, comparação e combinação, componentes cognitivos significativos detectados em estudantes talentosos. A aprendizagem por meio do processo de resolução de problemas num ambiente online pode ampliar o pensamento crítico e aprimorar a tomada de decisão. Nesta pesquisa, foi criado um agente conversacional chamado Blaze, com o intuito de apoiar o estudante durante a aprendizagem autorregulada baseada na resolução de problemas. O agente foi desenvolvido com a linguagem de marcação AIML (Artificial Intelligence Markup Language), tendo sua base de conhecimento construída por meio da elicitação e representação dos processos cognitivos dos estudantes talentosos, alunos medalhistas da Olimpíada Brasileira de Matemática das Escolas Públicas. Utilizou-se a técnica de Raciocínio Baseado em Casos para permitir a recuperação e reutilização de experiências passadas dos estudantes talentosos. Foram realizados tantos experimentos com outros estudantes de graus de escolaridades distintos (2ª série do ensino médio, Licenciatura em Ciências e Licenciatura em Matemática) com o objetivo de investigar o engajamento e o aprimoramento das habilidades cognitivas destes durante a resolução dos problemas com a assistência do agente conversacional Blaze. Nestes experimentos, alguns estudantes interagiram com o agente Blaze durante o processo de resolução de problemas matemáticos, enquanto outros trabalharam sozinhos na resolução dos mesmos problemas. Os resultados obtidos nos experimentos permitiram verificar que o apoio do agente conversacional Blaze, no contexto de uma aprendizagem autorregulada durante a resolução de problemas, contribuiu qualitativamente para o aprimoramento de diversas habilidades cognitivas, como por exemplo, pensamento crítico, pensamento criativo, raciocínio lógico, bem como, permitiu o uso da metacognição. / A relevant issue raised in this paper is that most times students, especially inexperienced ones, show great difficulty for learning based on problem solving. Therefore, such students need to be monitored, which requires support from entities or more experienced people. Many times we see that due to students’ lack of mastery of the field of knowledge addressed, they fail to thoroughly analyze the problem data so as to objectively handle each stage of the solution. Several cognitive skills are required during the problem-solving process, such as coding, and comparison and combination, significant cognitive components detected in talented students. Learning by means of a problem-solving process in an online environment is capable of expanding critical thinking and improving students’ decision-making skills. In this research, a conversational agent we call Blaze was created in an effort to help students during their self-regulated, problem solving-based learning. The agent was developed via the AIML (Artificial Intelligence Markup Language), and its knowledge base was put together by means of eliciting and representing the cognitive processes of talented students, students who had won medals at the Brazilian Public School Mathematics Olympic Games. We used the Case-Based Reasoning technique to enable us to recover and reuse the talented students’ past experiences. Some other experiments were carried out with other students from various schooling levels (high school sophomores, and Science and Math undergrads) in order to look into those students’ engagement and improvement of their cognitive skills as they solved problems assisted by the Blaze conversational agent. In those experiments, some students interacted with the Blaze agent during the math problem-solving process, while other students worked alone on solving the same problems. The results obtained from the experiments allowed us to find that the support from the Blaze conversational agent, in the context of self-regulated learning during problem-solving, qualitatively helped the students improve their several cognitive skills, such as critical thinking, creative thinking, and logic reasoning, besides enabling the use of meta-cognition.

Uma questão que se apresenta relevante, nesta tese, é que na maioria das vezes, o estudante, principalmente, o novato, demonstra grande dificuldade na aprendizagem baseada na resolução de problemas. Portanto, este precisa de monitoração, isto exige um apoio de entidades ou pessoas mais experientes. Percebe-se que, muitas vezes, por falta de domínio na área do conhecimento tratada, o estudante não analisa minuciosamente os dados do problema para poder conduzir objetivamente cada etapa de solução. Várias habilidades cognitivas são exigidas durante o processo de resolução de problemas, como por exemplo, codificação, comparação e combinação, componentes cognitivos significativos detectados em estudantes talentosos. A aprendizagem por meio do processo de resolução de problemas num ambiente online pode ampliar o pensamento crítico e aprimorar a tomada de decisão. Nesta pesquisa, foi criado um agente conversacional chamado Blaze, com o intuito de apoiar o estudante durante a aprendizagem autorregulada baseada na resolução de problemas. O agente foi desenvolvido com a linguagem de marcação AIML (Artificial Intelligence Markup Language), tendo sua base de conhecimento construída por meio da elicitação e representação dos processos cognitivos dos estudantes talentosos, alunos medalhistas da Olimpíada Brasileira de Matemática das Escolas Públicas. Utilizou-se a técnica de Raciocínio Baseado em Casos para permitir a recuperação e reutilização de experiências passadas dos estudantes talentosos. Foram realizados tantos experimentos com outros estudantes de graus de escolaridades distintos (2ª série do ensino médio, Licenciatura em Ciências e Licenciatura em Matemática) com o objetivo de investigar o engajamento e o aprimoramento das habilidades cognitivas destes durante a resolução dos problemas com a assistência do agente conversacional Blaze. Nestes experimentos, alguns estudantes interagiram com o agente Blaze durante o processo de resolução de problemas matemáticos, enquanto outros trabalharam sozinhos na resolução dos mesmos problemas. Os resultados obtidos nos experimentos permitiram verificar que o apoio do agente conversacional Blaze, no contexto de uma aprendizagem autorregulada durante a resolução de problemas, contribuiu qualitativamente para o aprimoramento de diversas habilidades cognitivas, como por exemplo, pensamento crítico, pensamento criativo, raciocínio lógico, bem como, permitiu o uso da metacognição. / A relevant issue raised in this paper is that most times students, especially inexperienced ones, show great difficulty for learning based on problem solving. Therefore, such students need to be monitored, which requires support from entities or more experienced people. Many times we see that due to students’ lack of mastery of the field of knowledge addressed, they fail to thoroughly analyze the problem data so as to objectively handle each stage of the solution. Several cognitive skills are required during the problem-solving process, such as coding, and comparison and combination, significant cognitive components detected in talented students. Learning by means of a problem-solving process in an online environment is capable of expanding critical thinking and improving students’ decision-making skills. In this research, a conversational agent we call Blaze was created in an effort to help students during their self-regulated, problem solving-based learning. The agent was developed via the AIML (Artificial Intelligence Markup Language), and its knowledge base was put together by means of eliciting and representing the cognitive processes of talented students, students who had won medals at the Brazilian Public School Mathematics Olympic Games. We used the Case-Based Reasoning technique to enable us to recover and reuse the talented students’ past experiences. Some other experiments were carried out with other students from various schooling levels (high school sophomores, and Science and Math undergrads) in order to look into those students’ engagement and improvement of their cognitive skills as they solved problems assisted by the Blaze conversational agent. In those experiments, some students interacted with the Blaze agent during the math problem-solving process, while other students worked alone on solving the same problems. The results obtained from the experiments allowed us to find that the support from the Blaze conversational agent, in the context of self-regulated learning during problem-solving, qualitatively helped the students improve their several cognitive skills, such as critical thinking, creative thinking, and logic reasoning, besides enabling the use of meta-cognition.