Intelligent Internet Data Searching

In this thesis author approaches the problem of automated text classification, which is one of basic tasks for building Intelligent Internet Search Agent. The work discusses various approaches to solving sub-problems of automated text classification, such as feature extraction and machine learning on text sources. Author also describes her own multiword approach to feature extraction and pres-ents the results of testing this approach using linear discriminant analysis based classifier, and classifier combining unsupervised learning for etalon extraction with supervised learning using common backpropagation algorithm for multilevel perceptron.

The REporting of Studies Conducted Using Observational Routinely-Collected Health Data (RECORD) Statement: Methods for Arriving at Consensus and Developing Reporting Guidelines.

OBJECTIVE: Routinely collected health data, collected for administrative and clinical purposes, without specific a priori research questions, are increasingly used for observational, comparative effectiveness, health services research, and clinical trials. The rapid evolution and availability of routinely collected data for research has brought to light specific issues not addressed by existing reporting guidelines. The aim of the present project was to determine the priorities of stakeholders in order to guide the development of the REporting of studies Conducted using Observational Routinely-collected health Data (RECORD) statement. METHODS: Two modified electronic Delphi surveys were sent to stakeholders. The first determined themes deemed important to include in the RECORD statement, and was analyzed using qualitative methods. The second determined quantitative prioritization of the themes based on categorization of manuscript headings. The surveys were followed by a meeting of RECORD working committee, and re-engagement with stakeholders via an online commentary period. RESULTS: The qualitative survey (76 responses of 123 surveys sent) generated 10 overarching themes and 13 themes derived from existing STROBE categories. Highest-rated overall items for inclusion were: Disease/exposure identification algorithms; Characteristics of the population included in databases; and Characteristics of the data. In the quantitative survey (71 responses of 135 sent), the importance assigned to each of the compiled themes varied depending on the manuscript section to which they were assigned. Following the working committee meeting, online ranking by stakeholders provided feedback and resulted in revision of the final checklist. CONCLUSIONS: The RECORD statement incorporated the suggestions provided by a large, diverse group of stakeholders to create a reporting checklist specific to observational research using routinely collected health data. Our findings point to unique aspects of studies conducted with routinely collected health data and the perceived need for better reporting of methodological issues.

ACACIA: an agent-based program for simulating behavior to reach long-term goals

We present ACACIA, an agent-based program implemented in Java StarLogo 2.0 that simulates a two-dimensional microworld populated by agents, obstacles and goals. Our program simulates how agents can reach long-term goals by following sensorial-motor couplings (SMCs) that control how the agents interact with their environment and other agents through a process of local categorization. Thus, while acting in accordance with this set of SMCs, the agents reach their goals through the emergence of global behaviors. This agent-based simulation program would allow us to understand some psychological processes such as planning behavior from the point of view that the complexity of these processes is the result of agent-environment interaction.

Cost allocation of corporate IT-services

Cost allocation is an inescapable problem in nearly every organization and in nearly every facet of accounting. Within large corporations there are several different types of units, like profit-making business units and non-profit service units. In order to evaluate the performance of the business units and to fund the operations of service units, the expenses of service production need to be allocated to the business units benefiting from the services.The objective of this thesis was to find good and fair allocating factors for the costs of corporate wide IT services. In order to reach this objective, the cost allocation process was studied in general and an overview of cost structure was established. All possible cost driver candidates were mapped and their good and bad properties were weighed. The cost allocation problem was handled separately according to organizational division of corporate IT department: infrastructure, administrative systems, sales system and e-business. The emphasis was on two largest cost groups: infrastructure costs and sales system costs. As a result of the study an allocation model is presented. It contains categorization of the costs, selected cost drivers and cost distributions for the current year.

Voimalaitoskattilan pyörivän regeneratiivisen ilman esilämmittimen suorituskyky ja mitoitus

Diplomityön tarkoituksena oli kehittää laskentaohjelma pyörivälle regeneratiiviselle lämmönsiirtimelle. Työ tehtiin Foster Wheeler Energia Oy:n Varkauden toimipisteessä. Työn ensimmäisessä osuudessa tutkittiin kirjallisuuden avulla regeneraattoreihin liittyvää teoriaa. Tämä osuus sisältää regeneratiivisen lämmönsiirron perusteita, regeneraattoreiden luokittelua, sektorijakoja, vuotoja, lämpöpintojen geometriaa ja likaantumista. Soveltavassa osassa tehtiin laskentaohjelma, jonka avulla voidaan laskea pyörivän regeneraattorin mitoitus- ja suorituskykylaskuja. Lisäksi ohjelman avulla voidaan laskea regeneraattorin lämpötilaprofiili.

The Dynamic Customer Portfolio Method in Customer Relationship Management

Tutkielman tavoitteena on määritellä keskeiset ja sopivat asiakasportfoliomallit ja asiakasmatriisit asiakassuhteen määrittämiseen. Tutkimus keskittyy asiakassuhteen arvottamiseen ja avainasiakkaiden määrittämiseen kohdeyrityksessä. Keskeisimmät ja sopivimmat asiakasportfliomallit huomioidaan asiakkaiden arvioinnissa. Tutkielman teoriaosassa esitellään tunnetuimmat ja käytetyimmät asiakasportfoliomallit ja matriisit alan kirjallisuuden perusteella. Tämän lisäksi asiakasportfoliomalleihin yhdistetään näkökulmia suhdemarkkinoinnin, asiakkuuksien johtamisen ja tuoteportfolioiden teorioista. Keskeisimmät kirjallisuuden lähteet ovat johtamisen ja markkinoinnin alalta. Tutkielman empiriaosassa esitellään kohdeyritys ja sen tämän hetkinen asiakassuhteiden johtamiskäytäntö. Lisäksi tehdään parannusehdotuksia kohdeyrityksen nykyiseen asiakassuhteiden arvottamismenetelmään jotta asiakassuhteiden arvon laskeminen vastaisi mahdollisimman hyvin kohdeyrityksen nykyisiä tarpeita. Asiakassuhteen arvon määrittämiseksi käytetään myös fokusryhmähaastattelua. Avainasiakkaat määritellään ja tilannetta havainnollistetaan sijoittamalla avainasiakkaat asiakasportfolioon.

MRO-tuotteiden hankintaprosessin tehostaminen toimittajayhteistyön avulla

Tutkimuksen tavoitteena oli selvittää MRO-tuotteiden hankinnassa käytettäviä liiketoimintasuhdemuotoja sekä huomioitavia asioita siirryttäessä kohti yhteistyötä toimittajan kanssa. Tutkimus toteutettiin kvalitatiivisena case-tutkimuksena, jossa aineiston kokoaminen pohjautui haastatteluihin, sisäisiin dokumentaatioihin sekä osallistuvaan havainnointiin. Analysointi tapahtui teoreettisen tuoteluokittelun pohjalta sekä luokitteluryhmien tarkastelulla käytännössä. Tutkimuksen keskeisimpänä tuloksena on havainto yhteistyösuhteiden käytön lisääntymisestä vakiotuotteiden hankinnassa. Tämä johtuu pyrkimyksestä suorittaa ko. tuotteiden hankinta mahdollisimman vähin resurssein, jolloin hankintojen huomio voidaan keskittää kriittisempiin tuotteisiin. MRO-tuotteissa käytettäviä yleisimpiä liiketoimintasuhteita ovat kilpailutus sekä vuosi- ja puitesopimukset. Ylläpitosopimukset ja kumppanuus-suhteet ovat mahdollisia, kun tuotteiden strateginen merkitys nousee merkittäväksi ja osapuolten välillä vallitsee korkea luottamus.

From bird to sparrow: Learning-induced modulations in fine-grained semantic discrimination.

Recognition of environmental sounds is believed to proceed through discrimination steps from broad to more narrow categories. Very little is known about the neural processes that underlie fine-grained discrimination within narrow categories or about their plasticity in relation to newly acquired expertise. We investigated how the cortical representation of birdsongs is modulated by brief training to recognize individual species. During a 60-minute session, participants learned to recognize a set of birdsongs; they improved significantly their performance for trained (T) but not control species (C), which were counterbalanced across participants. Auditory evoked potentials (AEPs) were recorded during pre- and post-training sessions. Pre vs. post changes in AEPs were significantly different between T and C i) at 206-232ms post stimulus onset within a cluster on the anterior part of the left superior temporal gyrus; ii) at 246-291ms in the left middle frontal gyrus; and iii) 512-545ms in the left middle temporal gyrus as well as bilaterally in the cingulate cortex. All effects were driven by weaker activity for T than C species. Thus, expertise in discriminating T species modulated early stages of semantic processing, during and immediately after the time window that sustains the discrimination between human vs. animal vocalizations. Moreover, the training-induced plasticity is reflected by the sharpening of a left lateralized semantic network, including the anterior part of the temporal convexity and the frontal cortex. Training to identify birdsongs influenced, however, also the processing of C species, but at a much later stage. Correct discrimination of untrained sounds seems to require an additional step which results from lower-level features analysis such as apperception. We therefore suggest that the access to objects within an auditory semantic category is different and depends on subject's level of expertise. More specifically, correct intra-categorical auditory discrimination for untrained items follows the temporal hierarchy and transpires in a late stage of semantic processing. On the other hand, correct categorization of individually trained stimuli occurs earlier, during a period contemporaneous with human vs. animal vocalization discrimination, and involves a parallel semantic pathway requiring expertise.

Facing Structural Disadvantage: The Role of Ingroup Connectedness

This thesis focuses on the social-psychological factors that help coping with structural disadvantage, and specifically on the role of cohesive ingroups and the sense of connectedness and efficacy they entail in this process. It aims to complement existing group-based models of coping that are grounded in a categorization perspective to groups and consequently focus exclusively on the large-scale categories made salient in intergroup contexts of comparisons. The dissertation accomplishes this aim through a reconsideration of between-persons relational interdependence as a sufficient and independent antecedent of a sense of groupness, and the benefits that a sense of group connectedness in one's direct environment, regardless of the categorical or relational basis of groupness, might have in the everyday struggles of disadvantaged group members. The three empirical papers aim to validate this approach, outlined in the first theoretical introduction, by testing derived hypotheses. They are based on data collected with youth populations (15-30) from three institutions in French-speaking Switzerland within the context of a larger project on youth transitions. Methods of data collection are paper-pencil questionnaires and in-depth interviews with a selected sub-sample of participants. The key argument of the first paper is that members of socially disadvantaged categories face higher barriers to their life project and that a general sense of connectedness, either based on categorical identities or other proximal groups and relations, mitigates the feeling of powerlessness associated with this experience. The second paper develops and tests a model that defines individual needs satisfaction as antecedent of self-group bonds and the efficacy beliefs derived from these intragroup bonds as the mechanism underlining the role of ingroups in coping. The third paper highlights the complexities that might be associated with the construction of a sense of groupness directly from intergroup comparisons and categorization-based disadvantage, and points out a more subtle understanding of the processes underling the emergence of groupness out of the situation of structural disadvantage. Overall, the findings confirm the central role of ingroups in coping with structural disadvantage and the importance of an understanding of groupness and its role that goes beyond the dominant focus on intergroup contexts and categorization processes.

Identity, non-identity, and near-identity: Addressing the complexity of coreference

This article examines the mainstream categorical definition of coreference as "identity of reference." It argues that coreference is best handled when identity is treated as a continuum, ranging from full identity to non-identity, with room for near-identity relations to explain currently problematic cases. This middle ground is needed to account for those linguistic expressions in real text that stand in relations that are neither full coreference nor non-coreference, a situation that has led to contradictory treatment of cases in previous coreference annotation efforts. We discuss key issues for coreference such as conceptual categorization, individuation, criteria of identity, and the discourse model construct. We redefine coreference as a scalar relation between two (or more) linguistic expressions that refer to discourse entities considered to be at the same granularity level relevant to the linguistic and pragmatic context. We view coreference relations in terms of mental space theory and discuss a large number of real life examples that show near-identity at different degrees.

New kernel functions and learning methods for text and data mining

Recent advances in machine learning methods enable increasingly the automatic construction of various types of computer assisted methods that have been difficult or laborious to program by human experts. The tasks for which this kind of tools are needed arise in many areas, here especially in the fields of bioinformatics and natural language processing. The machine learning methods may not work satisfactorily if they are not appropriately tailored to the task in question. However, their learning performance can often be improved by taking advantage of deeper insight of the application domain or the learning problem at hand. This thesis considers developing kernel-based learning algorithms incorporating this kind of prior knowledge of the task in question in an advantageous way. Moreover, computationally efficient algorithms for training the learning machines for specific tasks are presented. In the context of kernel-based learning methods, the incorporation of prior knowledge is often done by designing appropriate kernel functions. Another well-known way is to develop cost functions that fit to the task under consideration. For disambiguation tasks in natural language, we develop kernel functions that take account of the positional information and the mutual similarities of words. It is shown that the use of this information significantly improves the disambiguation performance of the learning machine. Further, we design a new cost function that is better suitable for the task of information retrieval and for more general ranking problems than the cost functions designed for regression and classification. We also consider other applications of the kernel-based learning algorithms such as text categorization, and pattern recognition in differential display. We develop computationally efficient algorithms for training the considered learning machines with the proposed kernel functions. We also design a fast cross-validation algorithm for regularized least-squares type of learning algorithm. Further, an efficient version of the regularized least-squares algorithm that can be used together with the new cost function for preference learning and ranking tasks is proposed. In summary, we demonstrate that the incorporation of prior knowledge is possible and beneficial, and novel advanced kernels and cost functions can be used in algorithms efficiently.

The learning about imaging diagnosis technology

Objective To investigate the learning about management of the technology (efficient use, acquisition and maintenance of imaging diagnosis equipment) in the radiology residency program of Escola Paulista de Medicina - Universidade Federal de São Paulo, with a view to improving the education of radiologists. Materials and Methods Exploratory research where residents, faculty staff and tutors of the program were quantitative and qualitatively approached with Likert scale questionnaires (46), and deepening with recorded interviews (18) and categorization based upon meaning units (thematic analysis). Results Among the participants, 66% agreed that they had the opportunity of learning about the use of radiological equipment; for 61% the program should include knowledge on the importance of acquiring equipment; and 72% emphasized the lack of learning about equipment management and maintenance. Conclusion As the major moment in the education of specialists, the medical residency program provides residents with a favorable environment to the learning of the skills required to the future of their professional practice, but with limited emphasis on the management of the technology: efficient use, acquisition and mainly maintenance of equipment, still poorly explored. Both the investigated program and the medical residency in radiology should incorporate, whenever possible, the commitment with the training in supplementary skills related to equipment management, developing the competence of the future radiologists.

Learning on human resources management in the radiology residency program

Objective To investigate the process of learning on human resource management in the radiology residency program at Escola Paulista de Medicina – Universidade Federal de São Paulo, aiming at improving radiologists' education. Materials and Methods Exploratory study with a quantitative and qualitative approach developed with the faculty staff, preceptors and residents of the program, utilizing a Likert questionnaire (46), taped interviews (18), and categorization based on thematic analysis. Results According to 71% of the participants, residents have clarity about their role in the development of their activities, and 48% said that residents have no opportunity to learn how to manage their work in a multidisciplinary team. Conclusion Isolation at medical records room, little interactivity between sectors with diversified and fixed activities, absence of a previous culture and lack of a training program on human resources management may interfere in the development of skills for the residents' practice. There is a need to review objectives of the medical residency in the field of radiology, incorporating, whenever possible, the commitment to the training of skills related to human resources management thus widening the scope of abilities of the future radiologists.

Bosniak classification of renal cystic lesions according to multidetector computed tomography findings

Renal cystic lesions are usually diagnosed in the radiologists' practice and therefore their characterization is crucial to determine the clinical approach to be adopted and prognosis. The Bosniak classification based on computed tomography findings has allowed for standardization and categorization of lesions in increasing order of malignancy (I, II, IIF, III and IV) in a simple and accurate way. The present iconographic essay developed with multidetector computed tomography images of selected cases from the archives of the authors' institution, is aimed at describing imaging findings that can help in the diagnosis of renal cysts.

La identificación de buenas prácticas en la mejora de la convivencia : un acercamiento a los centros públicos de Educación Secundaria de Cataluña

The article describes and summarizes some results of the research Identification of the difficulties, collection of good practices and analysis of the improvement processes in Secondary Education Institutes of Catalonia (2011). An approach to the situation of conviviality in the Catalan public Secondary schools gathering the perception of the management teams, through an ethnographic approach and of analysis of the stories. It has its origin in a work commissioned from the General Subdirectorate of Permanent Teacher Training of the Generalitat of Catalonia, developed in the context of the module “Conviviality and Organization of Centres”, within the program of permanent training of management teams. It falls in line with action-oriented research to improve practice. The paper gathers and synthesizes the results obtained in the collection and systematization of the proposed improvements. It is structured in three parts: a) a theoretical analysis which conceptualizes violence / conviviality and sense of good practices; b) the explanation of the design, methodology and development of research and c) the categorization of the improvement proposals and the conclusions of the work