El reclutamiento de personal en la nueva sociedad informacional

El artículo plantea un análisis empírico sobre las posibilidades de aplicación de las nuevas tecnologías de la información al proceso de reclutamiento de personal. Las competencias sociales y cognitivas que requieren las nuevas formas de organización de la producción plantean nuevos métodos de aprendizaje y la actualización del desarrollo de capacidades y comportamientos. Se trata de renovar y completar las competencias profesionales en un proceso permanente, que implica la adopción de una política de reclutamiento orientada por la consideración del conocimiento como elemento diferenciador de competitividad empresarial y de creación de riqueza.

Persistence of Transmitted HIV-1 Drug Resistance Mutations Associated with Fitness Costs and Viral Genetic Backgrounds.

Transmission of drug-resistant pathogens presents an almost-universal challenge for fighting infectious diseases. Transmitted drug resistance mutations (TDRM) can persist in the absence of drugs for considerable time. It is generally believed that differential TDRM-persistence is caused, at least partially, by variations in TDRM-fitness-costs. However, in vivo epidemiological evidence for the impact of fitness costs on TDRM-persistence is rare. Here, we studied the persistence of TDRM in HIV-1 using longitudinally-sampled nucleotide sequences from the Swiss-HIV-Cohort-Study (SHCS). All treatment-naïve individuals with TDRM at baseline were included. Persistence of TDRM was quantified via reversion rates (RR) determined with interval-censored survival models. Fitness costs of TDRM were estimated in the genetic background in which they occurred using a previously published and validated machine-learning algorithm (based on in vitro replicative capacities) and were included in the survival models as explanatory variables. In 857 sequential samples from 168 treatment-naïve patients, 17 TDRM were analyzed. RR varied substantially and ranged from 174.0/100-person-years;CI=[51.4, 588.8] (for 184V) to 2.7/100-person-years;[0.7, 10.9] (for 215D). RR increased significantly with fitness cost (increase by 1.6[1.3,2.0] per standard deviation of fitness costs). When subdividing fitness costs into the average fitness cost of a given mutation and the deviation from the average fitness cost of a mutation in a given genetic background, we found that both components were significantly associated with reversion-rates. Our results show that the substantial variations of TDRM persistence in the absence of drugs are associated with fitness-cost differences both among mutations and among different genetic backgrounds for the same mutation.

Functional error modeling for uncertainty quantification in hydrogeology

Approximate models (proxies) can be employed to reduce the computational costs of estimating uncertainty. The price to pay is that the approximations introduced by the proxy model can lead to a biased estimation. To avoid this problem and ensure a reliable uncertainty quantification, we propose to combine functional data analysis and machine learning to build error models that allow us to obtain an accurate prediction of the exact response without solving the exact model for all realizations. We build the relationship between proxy and exact model on a learning set of geostatistical realizations for which both exact and approximate solvers are run. Functional principal components analysis (FPCA) is used to investigate the variability in the two sets of curves and reduce the dimensionality of the problem while maximizing the retained information. Once obtained, the error model can be used to predict the exact response of any realization on the basis of the sole proxy response. This methodology is purpose-oriented as the error model is constructed directly for the quantity of interest, rather than for the state of the system. Also, the dimensionality reduction performed by FPCA allows a diagnostic of the quality of the error model to assess the informativeness of the learning set and the fidelity of the proxy to the exact model. The possibility of obtaining a prediction of the exact response for any newly generated realization suggests that the methodology can be effectively used beyond the context of uncertainty quantification, in particular for Bayesian inference and optimization.

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.

Minimal requirements for parameters to be used for the development of predictive models for microbial source tracking. The example of the pair somatic coliphages and phages infecting Bacteroides

Several methods and approaches for measuring parameters to determine fecal sources of pollution in water have been developed in recent years. No single microbial or chemical parameter has proved sufficient to determine the source of fecal pollution. Combinations of parameters involving at least one discriminating indicator and one universal fecal indicator offer the most promising solutions for qualitative and quantitative analyses. The universal (nondiscriminating) fecal indicator provides quantitative information regarding the fecal load. The discriminating indicator contributes to the identification of a specific source. The relative values of the parameters derived from both kinds of indicators could provide information regarding the contribution to the total fecal load from each origin. It is also essential that both parameters characteristically persist in the environment for similar periods. Numerical analysis, such as inductive learning methods, could be used to select the most suitable and the lowest number of parameters to develop predictive models. These combinations of parameters provide information on factors affecting the models, such as dilution, specific types of animal source, persistence of microbial tracers, and complex mixtures from different sources. The combined use of the enumeration of somatic coliphages and the enumeration of Bacteroides-phages using different host specific strains (one from humans and another from pigs), both selected using the suggested approach, provides a feasible model for quantitative and qualitative analyses of fecal source identification.

Väsymisen huomiointi laitteen ohjauksessa

Työssä selvitettiin väsymisen huomioivan ja minimoivan laitteen ohjausmenetelmiä. Väsymisilmiön huomioiva älykäs laite monitoroi itsenäisesti mm. väsymissäröjen kasvua ja muuttaa toimintaansa sen mukaisesti. Reagoinnin hyötyinä saavutetaan väsyttävästi kuormitetulle laitteelle mm. pidempi käyttöikä ja riskin hallinta, jossa laite tietää, miten sitä voidaan käyttää ennen vauriota ja sen jälkeen. Kunnossapitoon liittyen ennustetaan jäljellä olevaa käyttöikää, jolloin voidaan suunnitella huolto. Tutkimuksessa käsiteltiin mm. laitteiden ohjauksen tarvitsemia mittausmenetelmiä, mittaustiedon käsittelyä, vaurion luokittelua ja vauriota minimoivan ohjauksen rakennetta. Lisäksi käsiteltiin lyhyesti vaurion luokittelussa sekä ohjausreaktioiden ratkaisemisessa tarvittavia oppivia menetelmiä. Väsymistä minimoivan laitteen ohjauksen perusedellytys on laitteen kokemien rasitusten ja/tai suorituksen mittaaminen. Mittaustulosten perusteella määritetään vaurioitumista kuvaavat suureet. Ohjauksen vaurioon reagoivassa osassa määritetään tieto vaurioitumisen kriittisyydestä ja tämän perusteella tarvittava ohjauksen optimaalinen muutos sekä optimaalinen ohjaussignaali tai muu korjaava toimenpide. Ohjaus optimoidaan vaurioitumisnopeus minimoiden ja suorituskyky maksimoiden. Näiden välille etsitään sopiva tasapaino, jossa suorituskyvyn häviö on pieni mahdollisimman suurella vaurioitumisen pienenemisellä. Tämän jälkeen mittauksien avulla saadaan tieto korjatun ohjauksen vaikutuksesta vauriosuureisiin.

Asiakasosaamisen oppiminen Case Etelä-Karjalan Osuuspankki

Tämän tutkimuksen tarkoituksena on selvittää pankin sisäisellä termillä nimitetyn asiakasosaamisen sisältöä. Tutkimuksessa tarkastellaan kokeneille toimihenkilöille kehittyneitä asiakaspalvelutaitoja sekä keinoja, joilla näitä taitoja ja osaamista voidaan siirtää pankkiin rekrytoiduille vasta-alkajille. Tutkimuksen tavoitteena on myös löytää menetelmiä organisaation oppimisen tukemiseen. Tutkimuksen teoriaosassa tarkastellaan yksilöä oppijana ja tiedonkäsittelijänä sekä organisaation oppimista. Työyhteisön oppimisen edistämisen keinoja käsitellään työssä oppimisen ja henkilöstöjohtamisen näkökulmista. Empiirinen osa koostuu haastatteluista, joissa kokeneet toimihenkilöt ja vasta-alkajat tuovat esiin näkemyksiään hyvästä asiakaspalvelusta. Tutkimustulosten perusteella asiakasosaaminen koostuu teknisestä ja tiedollisesta osaamisesta sekä vuorovaikutustaidoista. Näiden taitojen siirtäminen edellyttää avointa, keskustelevaa organisaatiota, joka jatkuvasti kyseenalaistaa käytäntöjään ja on halukas sitoutumaan pysyvän oppimiskulttuurin kehittämiseen.

Alternative Techniques of Neural Signal Processing in Neuroengineering

Neural signal processing is a discipline within neuroengineering. This interdisciplinary approach combines principles from machine learning, signal processing theory, and computational neuroscience applied to problems in basic and clinical neuroscience. The ultimate goal of neuroengineering is a technological revolution, where machines would interact in real time with the brain. Machines and brains could interface, enabling normal function in cases of injury or disease, brain monitoring, and/or medical rehabilitation of brain disorders. Much current research in neuroengineering is focused on understanding the coding and processing of information in the sensory and motor systems, quantifying how this processing is altered in the pathological state, and how it can be manipulated through interactions with artificial devices including brain–computer interfaces and neuroprosthetics.

Analysis of Satellite Data for Forest Segmentation

In this work we study the classification of forest types using mathematics based image analysis on satellite data. We are interested in improving classification of forest segments when a combination of information from two or more different satellites is used. The experimental part is based on real satellite data originating from Canada. This thesis gives summary of the mathematics basics of the image analysis and supervised learning , methods that are used in the classification algorithm. Three data sets and four feature sets were investigated in this thesis. The considered feature sets were 1) histograms (quantiles) 2) variance 3) skewness and 4) kurtosis. Good overall performances were achieved when a combination of ASTERBAND and RADARSAT2 data sets was used.

Ekonomien ammatillisen kehittymisen tarpeet

Tämä pro gradu -tutkielma käsittelee ekonomien ammatillisen kehittymisen tarpeita muuttuvassa maailmassa, jossa ammatillinen erityisosaaminen vanhenee nopeasti. Tutkimuksessa tarkastellaan ekonomikunnassa koettuja ammatillisen kehittymisen tarpeita substanssin ja oppimistapojen näkökulmasta. Tutkimuksen tavoitteena on selvittää, millaisia ammatillisen kehittymisen tarpeita ekonomeilla on ja miten näihin tarpeisiin voisi vastata. Tutkimuksen pyrkimyksenä on selvittää myös, miten Suomen Ekonomiliitto SEFE voisi auttaa jäseniään kehittymään edelleen ammatillisesti. Aikuisoppimis- ja motivaatioteorioita on olemassa lukuisia. Pro gradun teoriaosassa selvitetään, miten aikuisten oppiminen tapahtuu, mitä se pitää sisällään ja mikä motivoi oppimaan. Lisäksi tutkimuksessa tarkastellaan työelämän ekonomeille asettamia vaatimuksia tänään ja tulevaisuudessa. Pro graduni tutkimusmenetelmänä käytettiin sähköistä kyselyä, ja otoksena oli 2000 SEFEn jäsenrekisteristä poimittua ekonomia. Tutkimustulokset osoittavat, että heterogeenisen ekonomikunnan näkemykset ammatillisen kehittymisen tarpeista ja varsinkin juuri itselle sopivista koulutusmuodoista eroavat melko paljon. Tärkeimmiksi ekonomiosaamisen osa-alueiksi nousivat seikat, joista on hyötyä muuttuvan maailman mukana pysymisessä, kuten valmius omaksua uusia asioita ja ongelmanratkaisutaito. Seuraavaksi tärkeimmäksi osaamisalueeksi nimettiin yleinen talouden tuntemus. Kehittää tulisi paitsi näitä osa-alueita, myös erilaisia johtamistaitoja. Tulosten mukaan suurin este ammatilliselle lisäkoulutukselle on ajan puute. Kyselyn vastauksissa painotettiin koulutuksesta saatavaa hyötyä suhteessa siihen laitettuihin panostuksiin. Kiireessä priorisoidaan työssä oppimista ja lyhyitä täsmäkoulutuksia.

Verkkosovellus oppimistyylien selvittämiseen ja tilastointiin

Oppimistyyleillä määritellään opiskelijan mieltymykset tavoissa, joilla hän vastaanottaa ja omaksuu helpoiten uutta tietoa. Opiskelijan henkilökohtaiseen oppimistyyliin vaikuttavat opiskelijan luonteenpiirteet ja ominaisuudet. Uusien asioiden oppiminen on helpompaa, jos opettajan käyttämä opetustyyli on ainakin osittain yhteneväinen opiskelijan oppimistyylin kanssa. Tässä diplomityössä kehitetty verkkosovellus on tarkoitettu opiskelijoiden käyttöön heidän oppimistyyliensä selvittämiseksi. Opiskelijat rekisteröityvät sovelluksen käyttäjiksi ja antavat samalla itsestään taustatietoja. Tämän jälkeen opiskelijat tekevät sovelluksessa oppimistyylit selvittävän testin. Taustatiedot ja testitulokset tallennetaan tietokantaan. Testituloksen ja oppimistyyleistä tarjolla olevien lisätietojen avulla opiskelijat voivat kehittää omia opiskelutapojaan. Testi on mahdollista tehdä myöhemmin uudelleen, ja tällöin opiskelijat näkevät omassa oppimistyylissään tapahtuneen kehityksen. Opettajat voivat käyttää sovellusta opiskelijoiden testituloksista muodostettavien tilastojen seuraamiseen. Näin opettajilla on mahdollisuus nähdä mitä oppimistyyliä heidän pitämilleen kursseille osallistuvat opiskelijat edustavat. Tämä tieto auttaa opettajia opetussuunnitelman teossa. Sovelluksella voidaan myös muodostaa opiskelijoiden taustatietoihin perustuvia tilastoja tutkimustarkoituksia varten.

Patient Seclusion and Restraint Practices in Psychiatric Hospitals - Towards Evidence Based Clinical Nursing

The overall goal of this study was to support evidence based clinical nursing regarding patient seclusion and restraint practices. This was done by ensuring professional competence through innovative learning methods. The data were collected in three phases between March 2007 and May 2009 on acute psychiatric wards. Firstly, psychiatric inpatients’ experiences and suggestions for seclusion and restraint practices were explored (n=30). Secondly, nursing and medical personnel’s perceptions of seclusion and restraint practices were explored (n=27). Thirdly, the impacts of a continuing vocational eLearning course on nurses’ professional competence was evaluated (n=158). Patients’ perspectives received insufficient attention during the seclusion and restraint process. Improvements and alternatives to seclusion and restraint as suggested by the patients focused on essential parts of clinical nursing, but were not extensively adopted. Also nursing and medical personnel thought that patients’ subjective perspective received little attention. Personnel proposed a number of alternatives to seclusion and restraint, and they expressed a need for education and support to adopt these in clinical nursing. Evaluation of impacts of eLearning course on nurses’ professional competence showed no statistical differences between an eLearning group and an education-as-usual group. This dissertation provides evidence based knowledge about the realization of seclusion and restraint practices and the impacts of eLearning course on nurses’ professional competence in psychiatric hospitals. In order to improve clinical nursing the patient perspective must be accentuated. To ensure personnel’s professional competence, there is a need for written clinical guidelines, education and support. Continuing vocational education should bring together written clinical guidelines, ethical and legal issues and the support for personnel. To achieve the ambitious goal of such integration, achievable and affordable educational programmes are required. This, in turn, yields a call for innovative learning methods.

Characterization of fiber and vessel elements in pulp suspension images

The thesis is related to the topic of image-based characterization of fibers in pulp suspension during the papermaking process. Papermaking industry is focusing on process control optimization and automatization, which makes it possible to manufacture highquality products in a resource-efficient way. Being a part of the process control, pulp suspension analysis allows to predict and modify properties of the end product. This work is a part of the tree species identification task and focuses on analysis of fiber parameters in the pulp suspension at the wet stage of paper production. The existing machine vision methods for pulp characterization were investigated, and a method exploiting direction sensitive filtering, non-maximum suppression, hysteresis thresholding, tensor voting, and curve extraction from tensor maps was developed. Application of the method to the microscopic grayscale pulp images made it possible to detect curves corresponding to fibers in the pulp image and to compute their morphological characteristics. Performance of the method was evaluated based on the manually produced ground truth data. An accuracy of fiber characteristics estimation, including length, width, and curvature, for the acacia pulp images was found to be 84, 85, and 60% correspondingly.

Reflexive Space. A Constructionist Model of the Russian Reflexive Marker

This study examines the structure of the Russian Reflexive Marker ( ся/-сь) and offers a usage-based model building on Construction Grammar and a probabilistic view of linguistic structure. Traditionally, reflexive verbs are accounted for relative to non-reflexive verbs. These accounts assume that linguistic structures emerge as pairs. Furthermore, these accounts assume directionality where the semantics and structure of a reflexive verb can be derived from the non-reflexive verb. However, this directionality does not necessarily hold diachronically. Additionally, the semantics and the patterns associated with a particular reflexive verb are not always shared with the non-reflexive verb. Thus, a model is proposed that can accommodate the traditional pairs as well as for the possible deviations without postulating different systems. A random sample of 2000 instances marked with the Reflexive Marker was extracted from the Russian National Corpus and the sample used in this study contains 819 unique reflexive verbs. This study moves away from the traditional pair account and introduces the concept of Neighbor Verb. A neighbor verb exists for a reflexive verb if they share the same phonological form excluding the Reflexive Marker. It is claimed here that the Reflexive Marker constitutes a system in Russian and the relation between the reflexive and neighbor verbs constitutes a cross-paradigmatic relation. Furthermore, the relation between the reflexive and the neighbor verb is argued to be of symbolic connectivity rather than directionality. Effectively, the relation holding between particular instantiations can vary. The theoretical basis of the present study builds on this assumption. Several new variables are examined in order to systematically model variability of this symbolic connectivity, specifically the degree and strength of connectivity between items. In usage-based models, the lexicon does not constitute an unstructured list of items. Instead, items are assumed to be interconnected in a network. This interconnectedness is defined as Neighborhood in this study. Additionally, each verb carves its own niche within the Neighborhood and this interconnectedness is modeled through rhyme verbs constituting the degree of connectivity of a particular verb in the lexicon. The second component of the degree of connectivity concerns the status of a particular verb relative to its rhyme verbs. The connectivity within the neighborhood of a particular verb varies and this variability is quantified by using the Levenshtein distance. The second property of the lexical network is the strength of connectivity between items. Frequency of use has been one of the primary variables in functional linguistics used to probe this. In addition, a new variable called Constructional Entropy is introduced in this study building on information theory. It is a quantification of the amount of information carried by a particular reflexive verb in one or more argument constructions. The results of the lexical connectivity indicate that the reflexive verbs have statistically greater neighborhood distances than the neighbor verbs. This distributional property can be used to motivate the traditional observation that the reflexive verbs tend to have idiosyncratic properties. A set of argument constructions, generalizations over usage patterns, are proposed for the reflexive verbs in this study. In addition to the variables associated with the lexical connectivity, a number of variables proposed in the literature are explored and used as predictors in the model. The second part of this study introduces the use of a machine learning algorithm called Random Forests. The performance of the model indicates that it is capable, up to a degree, of disambiguating the proposed argument construction types of the Russian Reflexive Marker. Additionally, a global ranking of the predictors used in the model is offered. Finally, most construction grammars assume that argument construction form a network structure. A new method is proposed that establishes generalization over the argument constructions referred to as Linking Construction. In sum, this study explores the structural properties of the Russian Reflexive Marker and a new model is set forth that can accommodate both the traditional pairs and potential deviations from it in a principled manner.