Exploring behaviour patterns with self-organizing map for personalised mental stress detection

Abstract. Stress is an important health problem and the cause for many illnesses and working days lost. It is often measured with different questionnaires that capture only the current stress levels and may come in too late for early prevention. They are also prone to subjective inaccuracies since the feeling of stress, and the physiological response to it, have been found to be individual. Real-time stress detectors, trained on biosignals like heart rate variability, exist but majority of them employ supervised learning which requires collecting a large amount of labelled data from each system user. Commonly, they are tested in situations where the stress response is deliberately induced (e.g. laboratory). Thus they may not generalise to real-life conditions where more general behavioural data could be used. In this study the issues with labelling and individuality are addressed by fitting unsupervised stress detection models at several personalisation levels. The method explored, the Self-Organizing Map, is combined with different clustering algorithms to find personal, semi-personal and general behaviour patterns that are converted to stress predictions. Laboratory biosignal-data are used for method validation. To provide an always-on type stress detection, real-life behavioural data consisting of biosignals and smartphone data are experimented on. The results show that personalisation does improve the predictions. The best classification performance for the laboratory data was found with the fully personalised model (F1-score 0.89 vs. 0.45 with the general model) but for the real-life data there was no big difference between fully personal (F1-score 0.57) and general model as long as the behaviour patterns were mapped to stress individually (F1-score 0.60). While the scores also validate the feasibility of SOM for mental stress detection, further research is needed to determine the most suitable and practical level of personalisation and an unambiguous mapping between behaviour patterns and stress.Tiivistelmä. Stressi on merkittävä terveysongelma ja syynä useisiin sairauksiin sekä työpoissaoloihin. Sitä mitataan usein erilaisilla kyselyillä, jotka kuvaavat vain hetkellistä stressitasoa ja joihin voidaan vastata liian myöhään ennaltaehkäisyn kannalta. Kyselyt ovat myös alttiita subjektiivisille epätarkkuuksille, koska stressintunteen, ja stressinaikaisten fysiologisten reaktioiden, on havaittu olevan yksilöllisiä. Reaaliaikaisia, biosignaalien kuten sykevälivaihtelun analyysiin perustuvia, stressintunnistimia on olemassa, mutta pääosin ne käyttävät ohjatun oppimisen menetelmiä, mikä vaatii jokaiselta järjestelmän käyttäjältä suuren stressintunteella merkityn aineiston. Stressintunnistimia myös usein testataan tilanteissa, joissa stressi on tahallisesti aiheutettua (esimerkiksi laboratoriossa). Siten ne eivät yleisty tosielämän tarpeisiin, jolloin voidaan käyttää yleisempää käyttäytymistä kuvaavaa aineistoa. Tässä tutkimuksessa vastataan datan merkintäongelmaan sekä yksilöllisyyden huomioimiseen käyttäen ohjaamattoman oppimisen stressintunnistusmalleja eri yksilöimisen tasoilla. Käytetty menetelmä, itseorganisoituva kartta, yhdistetään eri ryhmittelyalgoritmeihin tavoitteena löytää henkilökohtaiset, osin henkilökohtaiset sekä yleiset käyttäytymismallit, jotka muunnetaan stressiennusteiksi. Menetelmän sopivuuden vahvistamiseksi käytetään laboratoriossa kerättyä biosignaalidataa. Menetelmää sovelletaan myös tosielämän stressintunnistukseen biosignaaleista ja älypuhelimen käyttödatasta koostuvalla käyttäytymisaineistolla. Tulokset osoittavat, että yksilöiminen parantaa ennustetarkkuutta. Laboratorio-aineistolla paras luokittelutarkkuus löydettiin täysin yksilöllisellä mallilla (F1-pistemäärä 0.89, kun yleisellä 0.45). Tosielämän aineistolla täysin yksilöllisen (F1-pistemäärä 0.57) ja yleisen mallin, jossa käyttäytymismallien ja stressin välinen kuvaus määrättiin yksilöidysti (F1-pistemäärä 0.60), välinen ero ei ollut suuri. Vaikka tulokset vahvistavatkin itseorganisoituvan kartan sopivuuden psyykkisen stressin tunnistamisessa, lisätutkimusta tarvitaan määräämään soveltuvin ja käytännöllisin yksilöimisen taso sekä yksikäsitteinen kuvaus käyttäytymismallien ja stressin välille

Implementing a data protection impact assessment for the web-application on the piloting phase

Abstract. The General Data Protection Regulation (GDPR) contains several obligations for the ones that are processing personal data of the EU citizens. The major obligations are to take data protection by design and by default, and to carry out a data protection impact assessment (DPIA) whenever there is a high risk to breach privacy. Some organizations and companies are still struggling to achieve these obligations. Violating these obligations may cause sanctions that are up to 4% of the annual turnover. This created the motivation to research how these obligations should be implemented to achieve better compliance with the GDPR. The objective of this thesis work was to research how the GDPR should be considered in applications that are processing personal data. Based on the related work, it was possible to recognize that DPIA process was recommended to cover the obligations of the GDPR. Therefore, the purpose was to research how the DPIA process would affect to the case application. Case application was a web-application that was on the piloting phase. Design science research was applied as a research method. It was decided to carry out a DPIA by applying the guidelines of the Information commissioner’s office (ICO). The DPIA process was applied to the case application. After the DPIA was completed, it was possible to evaluate its impact on the case application. Evaluation was completed in three parts, by evaluating how well the process of the DPIA covered the requirements of the GDPR, by evaluating the technical advantages and costs of the process, and by evaluating how the DPIA was applied in practice. The results of this thesis showed that applying the DPIA process improved data protection, privacy and technical features of the case application. It was possible to reduce the privacy risks associated with data processing activities. In addition, DPIA process improved the technical side of the case application. The data model was simplified and unnecessary information flows were eliminated. These improvements were estimated to increase the workload of the developers for 2.7%. This meant that DPIA process was suitable way to cover the obligations of the GDPR

Collaborative flow in esports:a survey study

Abstract. During the 21th century, e-sports has been rapidly rising in popularity with multiple e-sports events with multi-million dollar prize pools. This popularity also has piqued the interest of scientist from all fields, and the number of scientific publications has continued to rise year–to-year, and multiple fields have started to study esports from multiple angles. Esports has no generally accepted definition. Esports is most often seen as “professional gaming” but at closer inspection, this definition is too narrow and does not cover all that esports is and what it has become. Esports can be defined in many ways depending on the research angle and the study field, however the similarities between studies are that esports is computer-mediated competition where athletes compete in high-stress situations where they try to outplay their opponent. Whether it is with reflexes and teamwork in a First-Person Shooter (FPS) or Multiplayer Online Battle Arena Games (MOBA), or with strategy in a Real-Time Strategy (RTS) games, or in one of the multitudes of video game genres. Esports acts as an umbrella term for all computer-mediated human versus human competition; it does not matter if humans go against a computer if they compare scores against each other at the end. In this thesis work, I will also be conducting a quantitative survey directed at people who play video games. According to the results time spent playing, team size and whether the player mostly plays in a team or alone all affect the immersion of the gameplay moment

Direct and inverse scattering problems for quasi-linear biharmonic operator in 3D

Abstract. We consider direct and inverse scattering problems for three-dimensional biharmonic operator $Hu = ∆^2u + Vu$, where $∆$ is the Laplacian and $V$ is a scalar valued perturbation. The scattering problem for this operator is given as a partial differential equation $Hu = k^4u$, with a parameter $k$. In the direct scattering problem, our goal is to find the solution $u$ while the perturbation (V\) is known. We also assume that the solution $u$ can be written as a sum of two functions $u_{0}$ and $u_{sc}$, where $u_{0}$ is a plane wave and $u_{sc}$ is an outgoing wave in the sense that it satisfies to the Sommerfeld radiation conditions at the infinity. Our approach in this text is to first modify the partial differential equation into an integral equation by using the fundamental solution. Next, we show that this integral equation is solvable, and it has a unique solution. Finally, we prove two main results of this text; an asymptotic formula for the solution with large values of $x ∈ \mathbb{R}^3$ and Saito’s formula. The asymptotic behaviour of the solution leads us to defining the scattering amplitude. In the inverse scattering problem, the goal is to gather some information about the unknown perturbation V while the behaviour of the function u is known. With Saito’s formula we obtain two corollaries regarding the inverse scattering problem, namely uniqueness and a representation formula for the function $V(x, 1)$, when the scattering amplitude is known. We end the text by first defining the inverse Born approximation for both full scattering data and backscattering data. We also discuss some results that have been obtained previously with this approach

Concept modeling of energy efficiency for heavy-duty trucks with E-axle equipped trailer

Abstract. The purpose of this master’s thesis is to study potential of E-axle on a trailer to provide better maneuverability for heavy trucks, and the possibility of fuel savings and thus lower tailpipe emissions and operating costs of the vehicle. Three different truck combination types were studied, timber, tipper, and long-haul trucks. Real-life driving data and other information of the selected truck types are collected, and simulation model of the trucks are created with MATLAB. Models are validated by comparing the simulation results with the collected real life driving data. After validation, E-axle is added to the model and the potential of the E-axle is tested in the abovementioned use cases. The results indicate that even a relatively small battery of 20 kWh could yield substantial fuel savings in the range of 5–15 %, depending on the drive cycle. If battery has to be charged by driving operations, the net fuel saving ranges between -1–9 %. However, the used control logic for the E-axle in this study was very simple and better overall results can be expected with optimized system. Substantially increased hill climbing ability in highway speeds with E-axle was also demonstrated, even with downgraded engines. Findings provide good general information about the potential of E-axle in timber, tipper, and long-haul trucks.E-akselilla varustettujen raskaiden kuorma-autojen energiatehokkuuden konseptimallinnus. Tiivistelmä. Tämän diplomityön tarkoituksena on tutkia peräkärryyn asennettavan sähköisen akselin, eli E-akselin hyödyntämistä raskaiden ajoneuvojen liikkuvuuden parantamisessa, sekä kulutuksen ja siten päästöjen ja käyttökulujen pienentämisessä. Työn kohteena on kolme erilaista raskasta ajoneuvoyhdistelmää, puuauto, sora-auto, sekä kaukoliikenneauto, joista kerätään ajomittausdataa reaaliympäristössä. Kirjallisuudesta ja tutkimuksista hankittujen ajoneuvon tietojen, sekä kerätyn ajodatan perusteella luodaan ajoneuvoista simulointimallit MATLAB-ohjelmistolla, jossa mallin toimivuus validoidaan vertaamalla simuloinnissa saatuja tuloksia mitattuihin tuloksiin. Kun mallin toimivuus on varmistettu, lisätään malliin E-akseli ja verrataan ja arvioidaan E-akseli potentiaalia yllä mainituissa tapauksissa suhteessa tavalliseen autoon. Tulokset antavat olettaa, että jo suhteellisen pienellä akkukoolla kuten 20 kWh, voi olla mahdollista saavuttaa ajosyklistä riippuen 5–15 % polttoainesäästöjä. Mikäli akku joudutaan kuitenkin lataamaan ajamalla täyteen, niin nettopotentiaali voi vaihdella -1–9 % välillä. Täytyy kuitenkin muistaa, että tässä työssä käytetty ohjauslogiikka E-akselille on hyvin yksinkertainen ja siten voidaankin olettaa, että kunnollisella optimoidulla ohjauslogiikalla on mahdollista saavuttaa yleisesti ottaen parempia tuloksia. Myös mäennousukyvyssä huomattiin huomattava parannus Eakselilla varustetuissa ajoneuvoissa, myös tapauksissa, joissa moottorin kokoa oli pienennetty alkuperäisestä. Tulokset antavat yleispätevää tietoa E-akselin potentiaalista puuautossa, sora-autossa ja kaukoliikenne käytössä

Influence of process mining in robotic process automation

Abstract. Companies are in an on-going competition against each other of the customers’ favour. Customers demand cheaper products and services with better quality. To be able to meet the customer requirements and stand up against their competitors, companies must be able to do more with less money and time invested. For this reason, process automation has been implemented widely in various companies. The latest breakthrough within process automation has been the implementation of Robotic Process Automation (RPA) which automatizes simple and rule-based back office tasks. While the existing literature reports high return on investment for RPA, challenges in identifying the best use cases to receive these returns remain. Some studies have suggested to combine RPA with Process Mining (PM) technology to help with this challenge. PM itself is still an emerging technology much like RPA. While both of these technologies have been studied somewhat, their combination remains undiscovered by prior literature. Therefore, the ambition of this research is to generate new understanding on how Process Mining can influence the efficiency of RPA’s utilisation. This ambition is achieved with a qualitative interview study that answers the following research questions: • RQ1: What are the benefits of RPA? • RQ2: What are the pre-requisites for successful RPA? • RQ3: How can process mining influence the efficiency of RPA? To answer the research questions, a literature review consisting of Business Process Management, RPA, and PM was conducted. The literature review forms an understanding of the key elements of RPA and PM while also identifying why businesses need these technologies. Interviews were conducted with professionals who had experience on RPA and PM to validate and expand the literature findings and to identify how RPA and PM could be combined. Combining the findings of literature review and interviews, a framework for RPA lifecycle augmented with PM was created to illustrate how RPA and PM can be beneficially combined. The results of this research reveal that PM is able to improve the efficiency of RPA by enabling data-based process understanding for organizations which helps to identify the best opportunities for automation, spot pre-automation process improvement needs, and to support decision making. In addition, PM is able to monitor and analyse the performance of the processes and the RPA robots to spot any deviances and to report the realized benefits of applying RPA to the process. This research contributes to the existing literature by providing new knowledge about the combination of RPA and PM. These results can be generally applied within organizations using RPA without restrictions to their industries.Tiivistelmä. Yritykset kilpailevat jatkuvasti toisiaan vastaan asiakkaidensa suosiosta. Asiakkaat vaativat halvempia ja laadukkaampia tuotteita ja palveluita. Vastatakseen asiakasvaatimuksiin ja säilyttääkseen kilpailukykynsä, yritysten täytyy tehdä enemmän asioita pienemmillä rahallisilla ja ajallisilla investoinneilla. Vastauksena tähän tarpeeseen, monet yritykset ovat automatisoineet prosessejaan. Viimeisin läpimurto prosessiautomaatiossa on ohjelmistorobotiikka, joka automatisoi yksinkertaisia ja sääntöpohjaisia tukitoimintojen työtehtäviä. Tämänhetkinen kirjallisuus raportoi suurta tuottoa investoinneille ohjelmistorobotiikkaan, mutta haasteita tuoton todelliseen toteutumiseen aiheutuu parhaiden käyttökohteiden tunnistamisen vaikeudesta. Muutamat tutkimukset ovat väläyttäneet prosessilouhinnan yhdistämistä ohjelmistorobotiikkaan, jotta parhaiden käyttökohteiden tunnistaminen helpottuisi. Prosessilouhinta, kuten ohjelmistorobotiikka, on myös kasvava teknologia. Sekä ohjelmistorobotiikkaa että prosessilouhintaa on tutkittu aikaisemmin, mutta näiden teknologioiden yhdistämistä ei ole juurikaan tutkittu aiemmin. Tästä syystä tämän tutkimuksen päämääränä on luoda uutta ymmärrystä siitä, miten prosessilouhinta vaikuttaa ohjelmistorobotiikan hyödyntämiseen. Tähän päämäärään päästään laadullisella haastattelututkimuksella, joka vastaa seuraaviin tutkimuskysymyksiin: • TK1: Mitkä ovat ohjelmistorobotiikan hyödyt? • TK2: Mitä ennakkovaatimuksia onnistuneelle ohjelmistorobotille on? • TK3: Kuinka prosessilouhinta voi vaikuttaa ohjelmistorobotiikan tehokkuuteen? Tutkimuskysymyksiin vastataan tekemällä aluksi kirjallisuuskatsaus, joka koostuu liiketoimintaprosessienhallinnasta, ohjelmistorobotiikasta ja prosessilouhinnasta. Kirjallisuuskatsaus luo ymmärrystä ohjelmistorobotiikan ja prosessilouhinnan perusteista sekä tunnistaa, miksi liiketoiminta tarvitsee näitä teknologioita. Kirjallisuuskatsauksen löydösten validointia ja laajentamista varten toteutettiin haastatteluja alan ammattilaisten kanssa, joilla oli työkokemusta ohjelmistorobotiikasta ja prosessilouhinnasta. Haastattelujen pohjalta pyrittiin myös tunnistamaan, miten prosessilouhintaa ja ohjelmistorobotiikkaa voitaisiin yhdistää. Kirjallisuuskatsauksen ja haastattelujen tulosten yhdistämisen ja analysoinnin pohjalta luotiin viitekehys ohjelmistorobotiikan elinkaarelle, johon liitettiin prosessilouhinnan käyttökohteet. Tämän viitekehyksen tarkoituksena on havainnollistaa, miten ohjelmistorobotiikkaa ja prosessilouhintaa voidaan hyödyntää yhdessä. Tutkimustulokset osoittavat, että prosessilouhinnan mahdollistama dataan perustuva prosessiymmärrys auttaa organisaatioita tunnistamaan parhaat käyttökohteet automaatiolle, havaitsemaan prosessinkehitys tarpeita sekä tukemaan päätöksentekoa, mitkä puolestaan parantavat ohjelmistorobotiikan tehokkuutta. Näiden lisäksi prosessilouhinnan avulla pystytään monitoroimaan ja analysoimaan prosessien ja robottien suorituskykyä, jolloin voidaan havaita mahdolliset poikkeamat sekä raportoimaan saavutetut hyödyt ohjelmistorobotiikan käytöstä prosessissa. Tämä tutkimus tukee aiempaa tutkimustietoa luomalla uutta tietoa ohjelmistorobotiikan ja prosessilouhinnan yhdistämisestä. Tutkimuksen tuloksia voidaan soveltaa yleisesti ohjelmistorobotiikkaa käyttävissä organisaatioissa toimialasta riippumattomasti

Accessing nanomechanical resonators via a fast microwave circuit

The measurement of micron-sized mechanical resonators by electrical techniques is difficult, because of the combination of a high frequency and a small mechanical displacement which together suppress the electromechanical coupling. The only electromagnetic technique proven up to the range of several hundred MHz requires the usage of heavy magnetic fields and cryogenic conditions. Here we show how, without the need of either of them, to fully electrically detect the vibrations of conductive nanomechanical resonators up to the microwave regime. We use the electrically actuated vibrations to modulate an LC tank circuit which blocks the stray capacitance, and detect the created sideband voltage by a microwave analyzer. We show the novel technique up to mechanical frequencies of 200 MHz. Finally, we estimate how one could approach the quantum limit of mechanical systems

Corporate entrepreneurship and employee engagement:investigating the connection

Abstract. The study of employee engagement has become a prominent topic in scientific research and modern-day business world. Organizations that aim to describe their employees as dedicated, vigorous, and absorbed in their work, are stating that they value employee engagement as a critical aspect of their operations. However, knowledge on the drivers of employee engagement is fragmented, and various suggestions have emerged from current research, which this thesis aims to contribute to. Corporate entrepreneurship has attracted interest among both academics and practitioners since the turn of the millennium. Organizations are increasingly seeking to create an environment of corporate entrepreneurship to foster innovation, proactivity and risk-taking. The academic literature regarding antecedents of corporate entrepreneurship highlights five antecedents, namely rewards and reinforcements, management support, work discretion and autonomy, time availability, and organizational boundaries. The focus of this thesis is to investigate whether these five antecedents, which create an environment of innovation, proactiveness, and risk-taking, could also serve as antecedents for fostering employee engagement. The research methodology employed is qualitative in nature, and the central question of the study is to understand the relationship between the antecedents of corporate entrepreneurship and employee engagement within the Finnish office of a multinational IT company. Through an in-depth analysis of the interview data, this study identifies new dimensions of rewards and reinforcements, management support, work discretion and autonomy, time availability, and organizational boundaries that are critical to understanding the complexities of employee engagement. The revised framework offers a more nuanced understanding of the factors that drive employee engagement and will serve as a useful guide for practitioners seeking to enhance engagement within their organizations. Additionally, this thesis contributes to the research of employee engagement by enhancing our understanding of the connection between the antecedents of corporate entrepreneurship and employee engagement

Film dynamics and lubricant depletion by droplets moving on lubricated surfaces

Lubricated surfaces have shown promise in numerous applications where impinging foreign droplets must be removed easily; however, before they can be widely adopted, the problem of lubricant depletion, which eventually leads to decreased performance, must be solved. Despite recent progress, a quantitative mechanistic explanation for lubricant depletion is still lacking. Here, we first explained the shape of a droplet on a lubricated surface by balancing the Laplace pressures across interfaces. We then showed that the lubricant film thicknesses beneath, behind, and wrapping around a moving droplet change dynamically with droplet's speed---analogous to the classical Landau-Levich-Derjaguin problem. The interconnected lubricant dynamics results in the growth of the wetting ridge around the droplet, which is the dominant source of lubricant depletion. We then developed an analytic expression for the maximum amount of lubricant that can be depleted by a single droplet. Counter-intuitively, faster moving droplets subjected to higher driving forces deplete less lubricant than their slower moving counterparts. The insights developed in this work will inform future work and the design of longer-lasting lubricated surfaces