”Ich bin alles anderes als ein Freund von Prostitution.” Eine linguistische Analyse über Selbst- und Fremddefinition in einem Diskussionsforum

Tämä sivuainetutkielma tarkastelee, miten keskustelufoorumin käyttäjät tunnistavat ja määrittelevät erilaisia sosiaalisia viiteryhmiä erimielisyystilanteissa. Työ pohjautuu sosiaalipsykologisiin käsitteisiin omasta ja vieraista viiteryhmistä, jotka voidaan ilmaista eksplisiittisesti tai implisiittisesti. Viiteryhmiin viittausta analysoitiin keskustelunanalyyttisen konseptin jäsenkategoria avulla. Tarkasteltavana oli saksalaisen naistenlehden Brigitte Community -keskustelupalstalta löytyvän keskusteluketjun 50 ensimmäistä viestiä. Keskustelunaiheena oli vastakkainasettelu kumppaninen salaisen rakastajan ja kumppanin salaisen bordellissa käymisen välillä. Tämän sivuaineen tutkielman taustalla vaikuttavat useammat teoreettiset lähtökohdat, jotka yhdistettiin ja joita muokattiin aineistoon sopivaksi. Jotta eri viiteryhmien määritelmiä pystyttiin analysoimaan keskustelunanalyyttisin keinoin, piti huomioida sellaiset perinteiset käsitteet, kuin vuoroparit ja keskustelun rakenne. Vuoropareja käsiteltiin näkökulmasta, jonka mukaan asynkronisessa tietokonevälitteisessä viestinnässä vallitsee illuusio vuoropareista. Keskustelun katsottiin koostuvan kokonaisuutena lomittaisista ja toisiinsa nivoutuneista keskustelukentistä. Analyysiin sisällytettiin kenttiä, jotka koostuivat vähintään kolmesta vuorosta ja muodostivat selkeän erimielisyyden. Erimielisyyden määrittely pohjautuu Muntiglin ja Turnbullin (1998) malliin. Tulokset osoittivat, että asynkronisen median käyttäjillä on monimuotoisia keinoja määritellä sekä oma että vieras viiteryhmä. Oman viiteryhmän määrittelyssä ilmeni ainoastaan harvoja esimerkkejä monitahoisemmista rakenteista, mutta vieraiden viiteryhmien määrittelyssä mahdollisuudet olivat moninaisemmat. Tulokset vihjaavat, että toisinaan erimielisyydet saattavat johtua vieraiden viiteryhmien eriävistä määritelmistä eriävien omien viiteryhmien sijaan.

Value creation in intelligent packaging value chains

The goal of this thesis is to look for and point out problems and bottlenecks related to value chains and networks in initiation and implementation of intelligent packaging. The research is based on interviews in different case companies and is qualitative by nature. The interview results are examined through a framework built upon relevant theory, with the aim to present a useful recommendation for a supplier company for advancing intelligent packaging business. The perspective that is attained through the research questions demonstrates the potential customer companies’ views of possibilities and problems. The key results suggest that intellectual property of relevant products is in an important position from the customers’ perspective. If the supplier does not own a product technology, a sufficiently large company can consider working as an integrator in a network where smaller companies make use of a compiled offering from other smaller actors. The foundation for these networks and company relationships is value creation, which has to be based on profound customer knowledge and research. The framework that is created for this study builds upon earlier research to provide a model that better serves intelligent packaging implementation and includes the notion of importance of value proposition and continuous value co-creation.

新增補李卓吾註釋素翁雜字併刊延賓帖式Xin zeng bu li zhuo wu zhu shi su weng za zi bing kan yan bin tie shi ; alias : 增補素翁指掌雜著全集Zeng bu su weng zhi zhang za zhu quan ji.

Manuel encyclopédique pour l'éducation.Composé par Chen Bin gong et annoté par Wang Bai gu ; explications de Li Zhuo wu († 1610). Ouvrage gravé par Wu Qi xiang (1628) ; comprenant : vie de Confucius, — en haut des pages, abrégé historique, en bas, vocabulaire méthodique, — renseignements divers, modèles de lettres, etc.2 + 32 + 6 feuillets.

Design, development and assessment of the Java Intelligent Tutoring System

The "Java Intelligent Tutoring System" (JITS) research project focused on designing, constructing, and determining the effectiveness of an Intelligent Tutoring System for beginner Java programming students at the postsecondary level. The participants in this research were students in the School of Applied Computing and Engineering Sciences at Sheridan College. This research involved consistently gathering input from students and instructors using JITS as it developed. The cyclic process involving designing, developing, testing, and refinement was used for the construction of JITS to ensure that it adequately meets the needs of students and instructors. The second objective in this dissertation determined the effectiveness of learning within this environment. The main findings indicate that JITS is a richly interactive ITS that engages students on Java programming problems. JITS is equipped with a sophisticated personalized feedback mechanism that models and supports each student in his/her learning style. The assessment component involved 2 main quantitative experiments to determine the effectiveness of JITS in terms of student performance. In both experiments it was determined that a statistically significant difference was achieved between the control group and the experimental group (i.e., JITS group). The main effect for Test (i.e., pre- and postiest), F( l , 35) == 119.43,p < .001, was qualified by a Test by Group interaction, F( l , 35) == 4.98,p < .05, and a Test by Time interaction, F( l , 35) == 43.82, p < .001. Similar findings were found for the second experiment; Test by Group interaction revealed F( 1 , 92) == 5.36, p < .025. In both experiments the JITS groups outperformed the corresponding control groups at posttest.

Modélisation des réactions émotionnelles dans un système tutoriel intelligent

Thèse numérisée par la Division de la gestion de documents et des archives de l'Université de Montréal

Effet des actions pédagogiques sur l'état émotionnel de l'apprenant dans un système tutoriel intelligent

Mémoire numérisé par la Division de la gestion de documents et des archives de l'Université de Montréal

Amorçage cognitif pour amélioration de l’acquisition de la connaissance dans un système tutoriel intelligent

Cette thèse vise à définir une nouvelle méthode d’enseignement pour les systèmes tutoriels intelligents dans le but d’améliorer l’acquisition des connaissances. L’apprentissage est un phénomène complexe faisant intervenir des mécanismes émotionnels et cognitifs de nature consciente et inconsciente. Nous nous intéressons à mieux comprendre les mécanismes inconscients du raisonnement lors de l’acquisition des connaissances. L’importance de ces processus inconscients pour le raisonnement est bien documentée en neurosciences, mais demeure encore largement inexplorée dans notre domaine de recherche. Dans cette thèse, nous proposons la mise en place d’une nouvelle approche pédagogique dans le domaine de l’éducation implémentant une taxonomie neuroscientifique de la perception humaine. Nous montrons que cette nouvelle approche agit sur le raisonnement et, à tour de rôle, améliore l’apprentissage général et l’induction de la connaissance dans un environnement de résolution de problème. Dans une première partie, nous présentons l’implémentation de notre nouvelle méthode dans un système tutoriel visant à améliorer le raisonnement pour un meilleur apprentissage. De plus, compte tenu de l’importance des mécanismes émotionnels dans l’apprentissage, nous avons également procédé dans cette partie à la mesure des émotions par des capteurs physiologiques. L’efficacité de notre méthode pour l’apprentissage et son impact positif observé sur les émotions a été validée sur trente et un participants. Dans une seconde partie, nous allons plus loin dans notre recherche en adaptant notre méthode visant à améliorer le raisonnement pour une meilleure induction de la connaissance. L’induction est un type de raisonnement qui permet de construire des règles générales à partir d’exemples spécifiques ou de faits particuliers. Afin de mieux comprendre l’impact de notre méthode sur les processus cognitifs impliqués dans ce type de raisonnement, nous avons eu recours à des capteurs cérébraux pour mesurer l’activité du cerveau des utilisateurs. La validation de notre approche réalisée sur quarante-trois volontaires montre l’efficacité de notre méthode pour l’induction de la connaissance et la viabilité de mesurer le raisonnement par des mesures cérébrales suite à l’application appropriée d’algorithmes de traitement de signal. Suite à ces deux parties, nous clorons la thèse par une discussion applicative en décrivant la mise en place d’un nouveau système tutoriel intelligent intégrant les résultats de nos travaux.

Intelligent Use of Emotions in Personal Selling: A Study into the Effect of Emotional Intelligence on the Performance of Sales Executives

School of Management Studies, Cochin University of Science and Technology

Intelligent Agent-based Multilingual Information Retrieval System

The goal of this work is to develop an Open Agent Architecture for Multilingual information retrieval from Relational Database. The query for information retrieval can be given in plain Hindi or Malayalam; two prominent regional languages of India. The system supports distributed processing of user requests through collaborating agents. Natural language processing techniques are used for meaning extraction from the plain query and information is given back to the user in his/ her native language. The system architecture is designed in a structured way so that it can be adapted to other regional languages of India

Intelligent structuring and reducing of association rules with formal concept analysis

Association rules are used to investigate large databases. The analyst is usually confronted with large lists of such rules and has to find the most relevant ones for his purpose. Based on results about knowledge representation within the theoretical framework of Formal Concept Analysis, we present relatively small bases for association rules from which all rules can be deduced. We also provide algorithms for their calculation.

The Architect's Collaborator: Toward Intelligent Tools for Conceptual Design

In early stages of architectural design, as in other design domains, the language used is often very abstract. In architectural design, for example, architects and their clients use experiential terms such as "private" or "open" to describe spaces. If we are to build programs that can help designers during this early-stage design, we must give those programs the capability to deal with concepts on the level of such abstractions. The work reported in this thesis sought to do that, focusing on two key questions: How are abstract terms such as "private" and "open" translated into physical form? How might one build a tool to assist designers with this process? The Architect's Collaborator (TAC) was built to explore these issues. It is a design assistant that supports iterative design refinement, and that represents and reasons about how experiential qualities are manifested in physical form. Given a starting design and a set of design goals, TAC explores the space of possible designs in search of solutions that satisfy the goals. It employs a strategy we've called dependency-directed redesign: it evaluates a design with respect to a set of goals, then uses an explanation of the evaluation to guide proposal and refinement of repair suggestions; it then carries out the repair suggestions to create new designs. A series of experiments was run to study TAC's behavior. Issues of control structure, goal set size, goal order, and modification operator capabilities were explored. In addition, TAC's use as a design assistant was studied in an experiment using a house in the process of being redesigned. TAC's use as an analysis tool was studied in an experiment using Frank Lloyd Wright's Prairie houses.

Information Dissemination and Aggregation in Asset Markets with Simple Intelligent Traders

Various studies of asset markets have shown that traders are capable of learning and transmitting information through prices in many situations. In this paper we replace human traders with intelligent software agents in a series of simulated markets. Using these simple learning agents, we are able to replicate several features of the experiments with human subjects, regarding (1) dissemination of information from informed to uninformed traders, and (2) aggregation of information spread over different traders.