Role of support services in business-to-business relationships − Case: Nordic ID

Siirretty Doriast

Luonnollisiin audiovisuaalisiin ärsykkeisiin liittyvän fMRI-aktivaation bayesilainen luokittelu harvoja ratkaisuja suosivia Laplace-prioreja käyttäen

Bayesian linear binary classification models with sparsity promoting Laplace priors were applied to discriminate fMRI patterns related to natural auditory and audiovisual speech and music stimuli. The region of interest comprised the auditory cortex and some surrounding regions related to auditory processing. Truly sparse posterior mean solutions for the classifier weights were obtained by implementing an automatic relevance determination method using expectation propagation (ARDEP). In ARDEP, the Laplace prior was decomposed into a Gaussian scale mixture, and these scales were optimised by maximising their marginal posterior density. ARDEP was also compared to two other methods, which integrated approximately over the original Laplace prior: LAEP approximated the posterior as well by expectation propagation, whereas MCMC used a Markov chain Monte Carlo simulation method implemented by Gibbs sampling. The resulting brain maps were consistent with previous studies for simpler stimuli and suggested that the proposed model is also able to reveal additional information about activation patterns related to natural audiovisual stimuli. The predictive performance of the model was significantly above chance level for all approximate inference methods. Regardless of intensive pruning of features, ARDEP was able to describe all of the most discriminative brain regions obtained by LAEP and MCMC. However, ARDEP lost the more specific shape of the regions by representing them as one or more smaller spots, removing also some relevant features.Bayesilaisia lineaarisia binääriluokittelumalleja ja harvoja ratkaisuja suosivia Laplace- prioreja sovellettiin erottelemaan luonnollisiin auditorisiin ja audiovisuaalisiin puhe- ja musiikkiärsykkeisiin liittyvää fMRI-aktivaatiota kuuloaivokuorella ja sitä ympäröivillä auditoriseen prosessointiin liittyvillä alueilla. Absoluuttisen harvoja posteriorisia odotusarvoratkaisuja luokittimien painoille saatiin expectation propagation -algoritmin avulla toteutetulla automatic relevance determination -menetelmällä (ARDEP). ARDEP-menetelmässä hyödynnettiin Laplace-priorin gaussista skaalahajotelmaa, jonka skaalaparametrit optimoitiin maksimoimalla niiden marginaalinen posterioritiheys. Menetelmää verrattiin myös kahteen muuhun menetelmään, jotka integroivat approksimatiivisesti alkuperäisen Laplace-priorin yli: LAEP approksimoi posteriorijakaumaa niin ikään expectation propagation -algoritmin avulla, kun taas MCMC käytti Gibbs -poiminnalla toteutettua Markovin ketju Monte Carlo -simulaatiomenetelmää. Tuloksena saadut aivokartat olivat linjassa aikaisempien, yksinkertaisemmilla ärsykkeillä saatujen tutkimustulosten kanssa, ja niiden perusteella bayesilaisten luokittelumallien avulla on mahdollista saada myös uudenlaista tietoa siitä, miten luonnollisia audiovisuaalisia ärsykkeitä koodataan aivoissa. Mallien ennustuskyky oli kaikilla approksimaatiomenetelmillä merkittävästi sattumanvaraista tasoa korkeampi. Piirteiden voimakkaasta karsinnasta huolimatta ARDEP pystyi kuvaamaan kaikki huomattavimmat LAEP:n ja MCMC:n erottelemat aivoalueet. ARDEP menetti kuitenkin alueiden tarkemman muodon esittämällä ne yhtenä tai useampana pienempänä alueena, poistaen myös osan merkittävistä piirteistä

If you are late, you are Beyond help : Disinformation and Authorities in Social Media

Fast paced, seemingly vast and ever-growing social media is a challenging environment for public authorities to communicate optimally. One challenge is malicious disinformation, which is intentionally disseminated to deceive and cause harm to citizens and authorities. It is known that exceptional circumstances create opportunities for malicious actors to negatively influence democratic societies. Disinformation is often designed to cause uncertainty towards information that public authorities offer and to decrease the overall trust in public authorities. The aim of disinformation is often to cause polarisation in society and to weaken national security. Furthermore, in a crisis, it is essential that authorities are able to deliver official information quickly, clearly and accurately to citizens. Communication between authorities and citizens in time-sensitive situations is typically online. One challenge to public authorities is how they can mitigate and repair the effects of disinformation and information influencing in complex and time-sensitive circumstances. In this article, our aim is to describe the challenges that public authorities face when communicating in social media spaces where disinformation is present. The empirical data, including 16 government official interviews, was collected in September 2021. The main theme of the interviews was related to how situational awareness about disinformation is formed in their organisations. Our research questions focus on how public authorities detect and counter disinformation in social media and what kind of problems and pressures they have when communicating in such environments. This study follows a qualitative design and the data was analysed using inductive content analysis. This study is part of larger project related to counterforces and the detection of disinformation. The results will provide a broader understanding of how different types of public authorities, from health to security organisations, and from agencies to ministries, communicate in complex environments such as social media

Are the Early Leavers the Lucky Ones?

According to previous studies, major workforce downsizings are commonly preceded by increased employee turnover due to ‘early leavers’. There is a common belief that early leavers are winners in terms of re-employment. This seven-year follow-up study based on register data from Finland questions if this is a valid finding in the Nordic context. We set the hypothesis that early leavers are not undisputed winners compared with those who leave during the actual downsizing. Trajectory and sequence analyses were used to test the hypothesis. Six employment trajectories were identified, ranging from permanently strong to permanently weak labor market attachment. Supporting the hypothesis, the early leavers assumed more commonly the weak and less commonly the strong employment trajectory. However, within the weak employment group, the early leavers and ultimately displaced workers were equal in terms of unemployment and retiring, as well as within the strong employment group in terms of income level

Time of Displacement as a Predictor of Re-employment

Previous studies addressing plant closures suggest that the reemployment of workers varies according to the economic cycle at the time of displacement. However, there are few studies on the selectivity of labor demand and reemployment in the long run. This study applied trajectory analyses in exploring the 7-year labor market attachment of workers displaced in plant closures in Finland during the recession in 1992, the boom in 1997, and slow economic growth in 2003. Results of the multinomial logistic regression analyses indicated that those displaced during the recession assumed the trajectory of strong employment significantly less commonly than those displaced under better economic conditions. Moreover, a significant interaction between age and year of displacement was found, whereas the gender, education-, and industryrelated risks turned out to be timeindependent. The study contributes to the sociological understanding of economic restructuring and how different times frame the individual’s opportunities to gain re-employment

Public Authorities as a Target of Disinformation

Disinformation is a part of a modern digitalised society and thus affects public authorities´ daily work. Through disinformation, malicious actors can often erode the fundamentals of democratic societies. In practice, this can be achieved by influencing authorities’ decision-making processes and creating distrust towards public organisations which can weaken authorities’ ability to function. In Finland, public authorities have relatively transparent and open decision-making processes and communication practices compared to other democratic societies. This transparency and openness can be seen as a vulnerability, increasing the opportunities for malicious actors to use disinformation. The authorities of public services are also seen as producers of evidence-based official information. In general, Finns have very high trust in public authorities. Trust has a major impact on societies’ psychological resilience and susceptibility to disinformation. The results of this article strengthen the idea that disinformation weakens authorities’ ability to function. The producers of disinformation, aided by citizens’ high confidence of public authorities, aim to utilise authorities’ communication by misrepresenting the content according to their own agenda. In this study, our purpose is to describe public authorities’ experiences relating to disinformation in their own organisation. This study follows a qualitative design framework by analysing data collected in September 2021 using inductive content analysis. The empirical data includes 16 government officials’ interviews with themes exploring how disinformation affects their daily activities and why they are targets of disinformation. This article is part of a larger project relating to counterforces and detection of disinformation. The results contribute towards a broader understanding on how different types of public authorities, ranging from health to security organisations, communicate in complex social media environments

Koneellinen hakkuu : Seurantatutkimus

Tutkimuksessa selvitettiin koneellisen hakkuun tuottavuutta ja ajankäytön rakennetta 23 hakkuukoneen tallentaman aineiston avulla. Hakkukertymä oli yhteensä 626 000 m3 ja se oli peräisin 1 573 korjuulohkolta eri puolilta maata. Hakkuun keskimääräinen tuotantoaikatuottavuus oli 15,0 m3/h. harvennuksilla se oli 10,2 m3/h ja päätehakkuilla 22,1 m3/h. Tuotantoaika käsittää käyttöajan lisäksi kaikki keskeytykset. Hakkuupoistuman keskimääräinen runkotilavuus oli 198 dm3 (harvennukset 127 dm3, päätehakkuut 327 dm3). Rungon keskitilavuus oli harvennuksilla huomattavasti pienempi kuin 1990-luvun alussa, jolloin tehtiin edellinen julkinen koneellisen puunkorjuun seurantatutkimus. Rungon keskitilavuus oli Pohjois-Suomessa pienempi kuin muilla alueilla, varsinkin päätehakkuilla. Hakkuun tuottavuus on noussut harvennuksilla suhteellisesti enemmän kuin päätehakkuilla. Hakkuun ajanmenekkiä, polttoaineen kulutusta ja niihin vaikuttavia tekijöitä tutkittiin koneoppimisen avulla erillisissä osa-aineistoissa, joita jouduttiin muodostamaan ajanseuranta-aineiston konemerkkikohtaisten erojen ja vaihtelevien tallennusparametrien vuoksi. Lisäksi selvitettiin kantokäsittelyliuoksen kulutusta. Rungon keskitilavuus ja hakkuutapa olivat tärkeimmät ajanmenekkiä selittävät tekijät. Työskentelytavan mukauttaminen hakkuutähteen talteenottoa varten alensi kuusivaltaisilla avohakkuilla tuottavuutta noin kymmenellä prosentilla. Tuotantoajan polttoaineenkulutus oli keskimäärin 0,9 l/m3 (rungon keskitilavuus 220 dm3), ja kantokäsittelyliuosta kului keskimäärin 0,6 l hakattua havupuukuutiometriä kohti (rungon keskitilavuus 256 dm3). Hakkuun tuottavuudesta ja polttoaineenkulutuksesta saadut tulokset viittaavat siihen, että suuria hakkuukoneita käytettiin osittain niiden optimaalisen käyttöalueen ulkopuolella.201