Measurement-Based Automatic Parameterization of a Virtual Acoustic Room Model

Modernien auralisaatiotekniikoiden ansiosta kuulokkeilla voidaan tuottaa kuuntelukokemus, joka muistuttaa useimpien äänitteiden tuotannossa oletettua kaiutinkuuntelua. Huoneakustinen mallinnus on tärkeä osa toimivaa auralisaatiojärjestelmää. Huonemallinnuksen parametrien määrittäminen vaatii kuitenkin ammattitaitoa ja aikaa. Tässä työssä kehitetään järjestelmä parametrien automaattiseksi määrittämiseksi huoneakustisten mittausten perusteella. Parametrisaatio perustuu mikrofoniryhmällä mitattuihin huoneen impulssivasteisiin ja voidaan jakaa kahteen osaan: suoran äänen ja aikaisten heijastusten analyysiin sekä jälkikaiunnan analyysiin. Suorat äänet erotellaan impulssivasteista erilaisia signaalinkäsittelytekniikoita käyttäen ja niitä hyödynnetään heijastuksia etsivässä algoritmissa. Äänilähteet ja heijastuksia vastaavat kuvalähteet paikannetaan saapumisaikaeroon perustuvalla paikannusmenetelmällä ja taajuusriippuvat etenemistien vaikutukset arvioidaan kuvalähdemallissa käyttöä varten. Auralisaation jälkikaiunta on toteutettu takaisinkytkevällä viiveverkostomallilla. Sen parametrisointi vaatii taajuusriippuvan jälkikaiunta-ajan ja jälkikaiunnan taajuusvasteen määrittämistä. Normalisoitua kaikutiheyttä käytetään jälkikaiunnan alkamisajan löytämiseen mittauksista ja simuloidun jälkikaiunnan alkamisajan asettamiseen. Jälkikaiunta-aikojen määrittämisessä hyödynnetään energy decay relief -metodia. Kuuntelukokeiden perusteella automaattinen parametrisaatiojärjestelmä tuottaa parempia tuloksia kuin parametrien asettaminen manuaalisesti huoneen summittaisten geometriatietojen pohjalta. Järjestelmässä on ongelmia erityisesti jälkikaiunnan ekvalisoinnissa, mutta käytettyihin suhteellisen yksinkertaisiin tekniikoihin nähden järjestelmä toimii hyvin.Modern auralization techniques enable making the headphone listening experience similar to the experience of listening with loudspeakers, which is the reproduction method most content is made to be listened with. Room acoustic modeling is an essential part of a plausible auralization system. Specifying the parameters for room modeling requires expertise and time. In this thesis, a system is developed for automatic analysis of the parameters from room acoustic measurements. The parameterization is based on room impulse responses measured with a microphone array and can be divided into two parts: the analysis of the direct sound and early reflections, and the analysis of the late reverberation. The direct sounds are separated from the impulse responses using various signal processing techniques and used in the matching pursuit algorithm to find the reflections in the impulse responses. The sound sources and their reflection images are localized using time difference of arrival -based localization and frequency-dependent propagation path effects are estimated for use in an image source model. The late reverberation of the auralization is implemented using a feedback delay network. Its parameterization requires the analysis of the frequency-dependent reverberation time and frequency response of the late reverberation. Normalized echo density is used to determine the beginning of the late reverberation in the measurements and to set the starting point of the modeled late field. The reverberation times are analyzed using the energy decay relief. A formal listening test shows that the automatic parameterization system outperforms parameters set manually based on approximate geometrical data. Problems remain especially in the precision of the late reverberation equalization but the system works well considering the relative simplicity of the processing methods used

Myynnin kasvattaminen kokonaisvaltaisen asiakastiedon ja kehittyneiden analyyttisten sovellusten käytön avulla

Companies are required to understand their customers more in depth in order to answer to the challenges introduced by the growingly complex operating environment. This understanding can be acquired through customer analytics in which the available customer information is analyzed with the help of advanced analytical applications. This research studied both customer analytics and the business intelligence architecture required to make customer analytics work. The aim of this study was especially to identify the correlation between the business intelligence architecture maturity and the insightfulness of customer analytics. In addition, particularly the application areas of customer analytics producing customer insight, which can be used to increase sales or sustain current sales, were focused on. The research was conducted as a case study including five different case companies. A semi-structured interview was used as a data collection method. Additionally, case descriptions including both the current status of business intelligence architecture and customer analytics in the case companies were created based on these semi-structured interviews. Furthermore, the case descriptions were analyzed in order to evaluate the business intelligence architecture maturity, amount of different application areas of customer analytics, and the level of customer analytics’ sophistication in the case companies. The results of these analyses were then compared to each other creating understanding from the correlation between these three entities. Based on these results a conclusion was drawn that there exists a correlation especially between the use of comprehensive customer information and advanced analytical applications and the insightfulness of company’s customer analytics. Furthermore, there also exists a correlation between the insightfulness of the company’s customer analytics and its ability to use customer information to further increase sales. The main results of this study can be used as a guideline when developing business intelligence architecture and as a source of ideas for new application areas of customer analytics. /Kir1

Metabolic Regulation in Progression to Autoimmune Diabetes

Recent evidence from serum metabolomics indicates that specific metabolic disturbances precede β-cell autoimmunity in humans and can be used to identify those children who subsequently progress to type 1 diabetes. The mechanisms behind these disturbances are unknown. Here we show the specificity of the pre-autoimmune metabolic changes, as indicated by their conservation in a murine model of type 1 diabetes. We performed a study in non-obese prediabetic (NOD) mice which recapitulated the design of the human study and derived the metabolic states from longitudinal lipidomics data. We show that female NOD mice who later progress to autoimmune diabetes exhibit the same lipidomic pattern as prediabetic children. These metabolic changes are accompanied by enhanced glucose-stimulated insulin secretion, normoglycemia, upregulation of insulinotropic amino acids in islets, elevated plasma leptin and adiponectin, and diminished gut microbial diversity of the Clostridium leptum group. Together, the findings indicate that autoimmune diabetes is preceded by a state of increased metabolic demands on the islets resulting in elevated insulin secretion and suggest alternative metabolic related pathways as therapeutic targets to prevent diabetes

Suomen ja Iso-Britannian kaupankäynti Brexitin jälkeen

Opinnäytetyössäni halusin selvittää, miten ero Euroopan unionista vaikuttaa jatkossa kaupankäyntiin suomalaisten yritysten näkökulmasta brittiläisten yritysten kanssa ja heidän markkina-alueellaan. Tarkoitus oli ymmärtää mitkä asiat ovat muuttuneet tai tulevat muuttumaan, ja mitkä ovat niiden vaikutukset kaupankäyntiin kohdemaan kanssa. Opinnäytetyöni on ajankohtainen, koska neuvottelut tulevaisuudesta olivat vielä käynnissä työn teko hetkellä ja saatiin päättymään loppuvaiheessa. Halusin tällä opinnäytetyölläni selvittää, kuinka Brexit on jo vaikuttanut ja tulee vaikuttamaan suomalaisiin yrityksiin tulevaisuudessa tehtäessä kauppaa Iso-Britannian markkinoilla. Opinnäytetyöni on kvalitatiivinen ja se perustuu teoriaosuudesta ja empiirisestä osuudesta, jossa hyödynsin asiantuntijahaastatteluja. Teoreettinen viitekehys sisältää kolme pääotsikkoa: Kansainvälinen kauppa Iso-Britannian näkökulmasta, Suomen ja Iso-Britannian välinen kauppa ennen Brexitiä ja Brexit ja sen välittömät vaikutukset Suomen ja Iso-Britannian kaupankäyntiin. Teoriaosuudessa olen hyödyntänyt jo valmiiksi kirjoitettua materiaalia ja sähköisiä artikkeleita. Haastatteluita sain viisi kappaletta, ja jokaisella haastateltavallani oli vankka kokemus kaupankäynnistä Britanniaan. Tutkimustulosten perusteella kaupankäynti maiden välillä tulee muuttumaan, ja Brexit ei pelkästään vaikuta taloudellisesti yrityksiin, vaan myös poliittisesti lähes koko maailmaan. Kaupankäynti tulee olemaan byrokraattisempaa ja tilanne vaatii ketteryyttä yritysmaailmassa. Välit maiden välillä todennäköisesti pysyy hyvinä, mutta kaupankäynti voi hiipua muutamaksi vuodeksi. EU ja Britannia saivat neuvoteltua kauppasopimukset, mutta aika näyttää kuinka kaupankäynti jatkuu maiden välillä

Myynnin kasvattaminen kokonaisvaltaisen asiakastiedon ja kehittyneiden analyyttisten sovellusten käytön avulla

Companies are required to understand their customers more in depth in order to answer to the challenges introduced by the growingly complex operating environment. This understanding can be acquired through customer analytics in which the available customer information is analyzed with the help of advanced analytical applications. This research studied both customer analytics and the business intelligence architecture required to make customer analytics work. The aim of this study was especially to identify the correlation between the business intelligence architecture maturity and the insightfulness of customer analytics. In addition, particularly the application areas of customer analytics producing customer insight, which can be used to increase sales or sustain current sales, were focused on. The research was conducted as a case study including five different case companies. A semi-structured interview was used as a data collection method. Additionally, case descriptions including both the current status of business intelligence architecture and customer analytics in the case companies were created based on these semi-structured interviews. Furthermore, the case descriptions were analyzed in order to evaluate the business intelligence architecture maturity, amount of different application areas of customer analytics, and the level of customer analytics’ sophistication in the case companies. The results of these analyses were then compared to each other creating understanding from the correlation between these three entities. Based on these results a conclusion was drawn that there exists a correlation especially between the use of comprehensive customer information and advanced analytical applications and the insightfulness of company’s customer analytics. Furthermore, there also exists a correlation between the insightfulness of the company’s customer analytics and its ability to use customer information to further increase sales. The main results of this study can be used as a guideline when developing business intelligence architecture and as a source of ideas for new application areas of customer analytics. /Kir1

A Comparison of Rule-based Analysis with Regression Methods in Understanding the Risk Factors for Study Withdrawal in a Pediatric Study

Regression models are extensively used in many epidemiological studies to understand the linkage between specific outcomes of interest and their risk factors. However, regression models in general examine the average effects of the risk factors and ignore subgroups with different risk profiles. As a result, interventions are often geared towards the average member of the population, without consideration of the special health needs of different subgroups within the population. This paper demonstrates the value of using rule-based analysis methods that can identify subgroups with heterogeneous risk profiles in a population without imposing assumptions on the subgroups or method. The rules define the risk pattern of subsets of individuals by not only considering the interactions between the risk factors but also their ranges. We compared the rule-based analysis results with the results from a logistic regression model in The Environmental Determinants of Diabetes in the Young (TEDDY) study. Both methods detected a similar suite of risk factors, but the rule-based analysis was superior at detecting multiple interactions between the risk factors that characterize the subgroups. A further investigation of the particular characteristics of each subgroup may detect the special health needs of the subgroup and lead to tailored interventions

Early probiotic supplementation and the risk of celiac disease in children at genetic risk

Abstract Probiotics are linked to positive regulatory effects on the immune system. The aim of the study was to examine the association between the exposure of probiotics via dietary supplements or via infant formula by the age of 1 year and the development of celiac disease autoimmunity (CDA) and celiac disease among a cohort of 6520 genetically susceptible children. Use of probiotics during the first year of life was reported by 1460 children. Time-to-event analysis was used to examine the associations. Overall exposure of probiotics during the first year of life was not associated with either CDA (n = 1212) (HR 1.15; 95%CI 0.99, 1.35; p = 0.07) or celiac disease (n = 455) (HR 1.11; 95%CI 0.86, 1.43; p = 0.43) when adjusting for known risk factors. Intake of probiotic dietary supplements, however, was associated with a slightly increased risk of CDA (HR 1.18; 95%CI 1.00, 1.40; p = 0.043) compared to children who did not get probiotics. It was concluded that the overall exposure of probiotics during the first year of life was not associated with CDA or celiac disease in children at genetic risk