Fenomenologinen tutkimus video-EEG potilaiden kohtauskokemuksista

Tässä fenomenologisessa tutkimuksessa kuvaillaan Video-EEG –tutkimukseen (VEEG) tulevien potilaiden kokemuksia kohtauksistaan. Tutkimusasetelmana on käytetty fenomenologiseen psykologiaan kuuluvaa Giorgin menetelmää soveltaen sitä hoitotieteen tutkimukseen. Tutkimuksen tarkoituksena oli kuvailla neurologisten kohtausoireiden vuoksi VEEG-tutkimukseen tulleiden potilaiden kokemuksia kohtauksistaan ja tunnistaa sekä kuvailla kokemukseen liittyviä tekijöitä. Tutkimuksen tavoitteena oli lisäta terveydenhoitohenkilökunnan ymmärrystä neurologisia kohtausoireita saavien ihmisten ohjaustarpeista. Materiaali kerättiin kahdeksalta potilaalta avoimilla haastatteluilla ja analysoitiin Giorgin analyysimenetelmällä. Aineistoon yhdistettiin kliinisen neurofysiologin lausunto ja muodostettiin kokemuskertomukset. Aineistosta tunnistettiin fenomenologista reduktiota käyttäen keskeiset kohtauksiin ja sairauteen liittyvät kokemukset. Käsitteiden suhdetta toisiinsa ja merkitystä sopeutumiselle analysoitiin käyttäen apuna Uncertainty in illness -mallia. Keskeisten kokemusten pohjalta toteutettiin kirjallisuushaku, jonka tuloksia reflektoitiin tämän tutkimuksen tuloksiin. Aineistosta muodostui kolme erillistä kokemuskertomusta: kertomus konkreettisista tapahtumista, kokemus hallinnan menettämisestä ja kokemus sairauden kanssa elämisesta. Keskeisiksi kokemussisällöiksi tunnistettiin kokemus terveysongelman hallinnasta, kokemus hallinnan menettämisestä, kokemus ympäristön negatiivisesta suhtautumisesta ja huoli läheisistä. Aikaisempaa tutkimusta löytyi kokemuksista terveysongelman hallinnasta ja hallinnan menetyksestä sekä ympäristön suhtautumisesta.

Fenomenologinen tutkimus video-EEG potilaiden kohtauskokemuksista

Tässä fenomenologisessa tutkimuksessa kuvaillaan Video-EEG –tutkimukseen (VEEG) tulevien potilaiden kokemuksia kohtauksistaan. Tutkimusasetelmana on käytetty fenomenologiseen psykologiaan kuuluvaa Giorgin menetelmää soveltaen sitä hoitotieteen tutkimukseen. Tutkimuksen tarkoituksena oli kuvailla neurologisten kohtausoireiden vuoksi VEEGtutkimukseen tulleiden potilaiden kokemuksia kohtauksistaan ja tunnistaa sekä kuvailla kokemukseen liittyviä tekijöitä. Tutkimuksen tavoitteena oli lisätä terveydenhoitohenkilökunnan ymmärrystä neurologisia kohtausoireita saavien ihmisten ohjaustarpeista. Materiaali kerättiin kahdeksalta potilaalta avoimilla haastatteluilla ja analysoitiin Giorgin analyysimenetelmällä. Aineistoon yhdistettiin kliinisen neurofysiologin lausunto ja muodostettiin kokemuskertomukset. Aineistosta tunnistettiin fenomenologista reduktiota käyttäen keskeiset kohtauksiin ja sairauteen liittyvät kokemukset. Käsitteiden suhdetta toisiinsa ja merkitystä sopeutumiselle analysoitiin käyttäen apuna Uncertainty in illness -mallia. Keskeisten kokemusten pohjalta toteutettiin kirjallisuushaku, jonka tuloksia reflektoitiin tämän tutkimuksen tuloksiin. Aineistosta muodostui kolme erillistä kokemuskertomusta: kertomus konkreettisista tapahtumista, kokemus hallinnan menettämisestä ja kokemus sairauden kanssa elämisestä. Keskeisiksi kokemussisällöiksi tunnistettiin kokemus terveysongelman hallinnasta, kokemus hallinnan menettämisestä, kokemus ympäristön negatiivisesta suhtautumisesta ja huoli läheisistä. Aikaisempaa tutkimusta löytyi kokemuksista terveysongelman hallinnasta ja hallinnan menetyksestä sekä ympäristön suhtautumisesta.

Visual analytics for behavioral and niche market segmentation

Companies require information in order to gain an improved understanding of their customers. Data concerning customers, their interests and behavior are collected through different loyalty programs. The amount of data stored in company data bases has increased exponentially over the years and become difficult to handle. This research area is the subject of much current interest, not only in academia but also in practice, as is shown by several magazines and blogs that are covering topics on how to get to know your customers, Big Data, information visualization, and data warehousing. In this Ph.D. thesis, the Self-Organizing Map and two extensions of it – the Weighted Self-Organizing Map (WSOM) and the Self-Organizing Time Map (SOTM) – are used as data mining methods for extracting information from large amounts of customer data. The thesis focuses on how data mining methods can be used to model and analyze customer data in order to gain an overview of the customer base, as well as, for analyzing niche-markets. The thesis uses real world customer data to create models for customer profiling. Evaluation of the built models is performed by CRM experts from the retailing industry. The experts considered the information gained with help of the models to be valuable and useful for decision making and for making strategic planning for the future.

The Nature of Object of Perception and Its Role in the Knowledge Concerning the External World

Questions concerning perception are as old as the field of philosophy itself. Using the first-person perspective as a starting point and philosophical documents, the study examines the relationship between knowledge and perception. The problem is that of how one knows what one immediately perceives. The everyday belief that an object of perception is known to be a material object on grounds of perception is demonstrated as unreliable. It is possible that directly perceived sensible particulars are mind-internal images, shapes, sounds, touches, tastes and smells. According to the appearance/reality distinction, the world of perception is the apparent realm, not the real external world. However, the distinction does not necessarily refute the existence of the external world. We have a causal connection with the external world via mind-internal particulars, and therefore we have indirect knowledge about the external world through perceptual experience. The research especially concerns the reasons for George Berkeley’s claim that material things are mind-dependent ideas that really are perceived. The necessity of a perceiver’s own qualities for perceptual experience, such as mind, consciousness, and the brain, supports the causal theory of perception. Finally, it is asked why mind-internal entities are present when perceiving an object. Perception would not directly discern material objects without the presupposition of extra entities located between a perceiver and the external world. Nevertheless, the results show that perception is not sufficient to know what a perceptual object is, and that the existence of appearances is necessary to know that the external world is being perceived. However, the impossibility of matter does not follow from Berkeley’s theory. The main result of the research is that singular knowledge claims about the external world never refer directly and immediately to the objects of the external world. A perceiver’s own qualities affect how perceptual objects appear in a perceptual situation.

Generative Part-Based Gabor Object Detector

Object detection is a fundamental task of computer vision that is utilized as a core part in a number of industrial and scientific applications, for example, in robotics, where objects need to be correctly detected and localized prior to being grasped and manipulated. Existing object detectors vary in (i) the amount of supervision they need for training, (ii) the type of a learning method adopted (generative or discriminative) and (iii) the amount of spatial information used in the object model (model-free, using no spatial information in the object model, or model-based, with the explicit spatial model of an object). Although some existing methods report good performance in the detection of certain objects, the results tend to be application specific and no universal method has been found that clearly outperforms all others in all areas. This work proposes a novel generative part-based object detector. The generative learning procedure of the developed method allows learning from positive examples only. The detector is based on finding semantically meaningful parts of the object (i.e. a part detector) that can provide additional information to object location, for example, pose. The object class model, i.e. the appearance of the object parts and their spatial variance, constellation, is explicitly modelled in a fully probabilistic manner. The appearance is based on bio-inspired complex-valued Gabor features that are transformed to part probabilities by an unsupervised Gaussian Mixture Model (GMM). The proposed novel randomized GMM enables learning from only a few training examples. The probabilistic spatial model of the part configurations is constructed with a mixture of 2D Gaussians. The appearance of the parts of the object is learned in an object canonical space that removes geometric variations from the part appearance model. Robustness to pose variations is achieved by object pose quantization, which is more efficient than previously used scale and orientation shifts in the Gabor feature space. Performance of the resulting generative object detector is characterized by high recall with low precision, i.e. the generative detector produces large number of false positive detections. Thus a discriminative classifier is used to prune false positive candidate detections produced by the generative detector improving its precision while keeping high recall. Using only a small number of positive examples, the developed object detector performs comparably to state-of-the-art discriminative methods.

Digital Exhaustion in relation to Video Games – The Consumer Perspective

This thesis regards exhaustion of copyright’s distribution right in intangible transfers of video games. It analyses whether, under the current law of the European Union, the phenomenon of digital exhaustion, especially in relation to games exists. The thesis analyses the consumers’ position in the market for copyright protected goods. It uses video games market as an example of the wider phenomenon of the effect of latest technological developments on consumers. The research conducted for the thesis is mostly legal dogmatic, although also comparative analysis, law and economics and law and technology methods are utilised. The thesis evaluates the effects of the most recent case law of the European Court of Justice to analyse the current state of digital exhaustion. In the analysis of effects that the existence of digital exhaustion has, the thesis uses the consumers’ point of view. The thesis introduces the current state of technology in the field of video games from a legal perspective. Furthermore the thesis analyses the effects on consumers of a scenario that no digital exhaustion exists in the future. Such scenario under the recent European case law at the moment seems realistic. The conclusion of my research is most importantly that the consumer position in the market for digital goods has deteriorated and that the probable exclusion of the exhaustion for digital goods is another piece of evidence of this development. Most importantly however, the state of affairs where no certainty prevails on whether digital exhaustion exists, creates injustice from the consumers’ point of view. Accordingly, acts by EU legislators of the Court of Justice of the European Union are required to clarify the issue.

Formal modelling for digital media distribution

Human beings have always strived to preserve their memories and spread their ideas. In the beginning this was always done through human interpretations, such as telling stories and creating sculptures. Later, technological progress made it possible to create a recording of a phenomenon; first as an analogue recording onto a physical object, and later digitally, as a sequence of bits to be interpreted by a computer. By the end of the 20th century technological advances had made it feasible to distribute media content over a computer network instead of on physical objects, thus enabling the concept of digital media distribution. Many digital media distribution systems already exist, and their continued, and in many cases increasing, usage is an indicator for the high interest in their future enhancements and enriching. By looking at these digital media distribution systems, we have identified three main areas of possible improvement: network structure and coordination, transport of content over the network, and the encoding used for the content. In this thesis, our aim is to show that improvements in performance, efficiency and availability can be done in conjunction with improvements in software quality and reliability through the use of formal methods: mathematical approaches to reasoning about software so that we can prove its correctness, together with the desirable properties. We envision a complete media distribution system based on a distributed architecture, such as peer-to-peer networking, in which different parts of the system have been formally modelled and verified. Starting with the network itself, we show how it can be formally constructed and modularised in the Event-B formalism, such that we can separate the modelling of one node from the modelling of the network itself. We also show how the piece selection algorithm in the BitTorrent peer-to-peer transfer protocol can be adapted for on-demand media streaming, and how this can be modelled in Event-B. Furthermore, we show how modelling one peer in Event-B can give results similar to simulating an entire network of peers. Going further, we introduce a formal specification language for content transfer algorithms, and show that having such a language can make these algorithms easier to understand. We also show how generating Event-B code from this language can result in less complexity compared to creating the models from written specifications. We also consider the decoding part of a media distribution system by showing how video decoding can be done in parallel. This is based on formally defined dependencies between frames and blocks in a video sequence; we have shown that also this step can be performed in a way that is mathematically proven correct. Our modelling and proving in this thesis is, in its majority, tool-based. This provides a demonstration of the advance of formal methods as well as their increased reliability, and thus, advocates for their more wide-spread usage in the future.

Visual Customer Segmentation and Data Exploration with the Self-Organizing Map

Advancements in information technology have made it possible for organizations to gather and store vast amounts of data of their customers. Information stored in databases can be highly valuable for organizations. However, analyzing large databases has proven to be difficult in practice. For companies in the retail industry, customer intelligence can be used to identify profitable customers, their characteristics, and behavior. By clustering customers into homogeneous groups, companies can more effectively manage their customer base and target profitable customer segments. This thesis will study the use of the self-organizing map (SOM) as a method for analyzing large customer datasets, clustering customers, and discovering information about customer behavior. Aim of the thesis is to find out whether the SOM could be a practical tool for retail companies to analyze their customer data.

TEHOHOITAJIEN KIVUN ARVIOINNIN OSAAMINEN – Tehohoitopotilaille kehitetyn kivunarviointimittarin käytön oppiminen video-opetuksen avulla.

Tehohoitopotilaan kivun arvioiminen on usein haastavaa, johtuen potilaan kyvyttömyydestä kommunikoida. Kivun arvioinnin avuksi onkin tästä syystä kehitetty käyttäytymiseen perustuvia kipumittareita. Tehohoitajilla on keskeinen asema kivun arvioinnissa, mutta tutkimusten perusteella tehohoitajien kivun arvioinnin osaaminen on puutteellista niin tietojen kuin taitojen osalta ja heillä on ennakkoasenteita kivun arviointiin liittyen. Tehohoitajien kouluttaminen kivun arviointiin liittyen on tärkeä keino tehohoitopotilaan kivun arvioinnin edistämisessä. Koulutuksen tulee kuitenkin olla helposti saatavilla, ottaen huomioon hoitotodellisuuden siihen tuomat haasteet. Tutkimuksen tarkoituksena oli arvioida video-opetuksen vaikutusta tehohoitajien tietoihin ja taitoihin tehohoitopotilaalle kehitetyn Critical-Care Pain Observation Tool (CPOT)-kipumittarin käyttöön liittyen, sekä kuvailla tehohoitajien kokemuksia video-opetuksesta oppimismenetelmänä. Yhdeltä teho-osastolta 48 tehohoitajaa katsoi tutkimusta varten kehitetyn CPOT-opetusvideon, jonka jälkeen he arvioivat kahden potilaan kipua CPOT-kipumittarilla, tutkijan tehdessä samanaikaisesti rinnakkaisarvioinnit potilaista. Arviointien jälkeen tehohoitajat tekivät tietotestin ja täyttivät CPOT-arviointilomakkeen. Tehohoitajien CPOT-kipumittarin käyttötaitoja arvioitiin tarkastelemalla tehohoitajien ja tutkijan tekemien kivunarviointien yhdenmukaisuutta interrater reliabiliteettilaskelmin. Kaksikymmentä tehohoitajaa haastateltiin heidän kokemuksista oppimismenetelmään liittyen. Haastattelut analysoitiin deduktiivisella temaattisella analyysillä. Tehohoitajat oppivat CPOT-kipumittarin käytön periaatteet ja kokivat oppineensa mittarin käytön, mutta interrater reliabiliteetti suhteessa tutkijan tekemiin kivun arviointeihin oli keskinkertainen. Video-opetus koettiin positiivisena, vaikkakin vuorovaikutuksellisuutta kaivattiin. Tutkimus osoitti video-opetuksen olevan käyttökelpoinen oppimismenetelmä CPOT-kipumittarin käytön periaatteiden oppimiseen, mutta parempien käyttötaitojen saavuttaminen vaatii lisäharjoittelua. Koska tehohoitajien subjektiivinen arvio käyttötaidoista ei välttämättä vastaa todellisia käyttötaitoja, oleellista olisi varmistaa myös objektiivisesti mittarin käyttötaidot koulutuksen jälkeen. Jatkossa tulisi tutkia käytäntöön soveltuvia keinoja varmistaa mittarin käyttötaidot, sekä teho-osastojen oppimiskulttuuria ja tehohoitajien motivaatiota ja asenteita työhön liittyvään oppimiseen.