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    Authors: Affia, Abasi-amefon Obot;

    Võrgutoega seadmete ja nende haavatavuste kasvuga on hakatud rohkem tähelepanu pöörama asjade interneti (IoT) turvariskide haldamisele (SRM). Võimalik ründepind laieneb asjade Interneti ökosüsteemi kasvades, tuues esile vajadust tugevate turvameetmete järele arenevate ohtude vastu. Olemasolevad uuringud toovad siiski välja lünki asjade Interneti arhitektuuri täielikul integreerimisel turvariskide haldamisse. Rakendamise praktilised väljakutsed tõstavad niigi keerukate asjade interneti süsteemide keerukust ja teevad turvariskide haldamise ülesannet veelgi keerulisemaks. Seega õõnestab teooria ja praktika vaheline ebavõrdsus turvaraamistike eduka rakendamise tõenäosust reaalsetes asjade interneti süsteemides, muutes need vastuvõtlikuks pidevalt arenevale ohumaastikule. Nende väljakutsete lahendamiseks tutvustame IoT-arhitektuuril põhinevat turvariskide haldamise (IoTA-SRM) raamistikku, mis pakub terviklikku ja integreeritavat lähenemist tuvariskide haldamisele asjade interneti süsteemides. Integreerides IoT arhitektuuri turvariskide haldamisse, saavad sidusrühmad tagada oma IoT süsteemi komponentide ja interaktsioonide igakülgse katvuse. Raamistikku hinnati autonoomsete sõidukisüsteemide ekspertide poolt läbiviidud juhtumiuuringute abil, et teha kindlaks selle praktilisus, kohanemisvõime ja eelised. Kuigi antud juhtumite analüüsis nähakse raamistiku praktilisust, võib selle teoreetiline rikkus jääda praktikutele rakendamise ajal abstraktseks. Arvestades asjade interneti süsteemide keerukust ja ohtude dünaamilist olemust, ei piisa üksi traditsioonilistest õpetamisviisidest, et hõlbustada raamistiku üleminekut teoreetiliselt arusaamiselt praktilisele rakendusele, mistõttu on vaja tavapärasest õpetamisviisidest edasi ulatuvaid haridusmeetodeid. Seega töötati välja sekkumispõhine häkatoni lähenemine. See lähenemisviis, mida täiustatakse kohandatud sekkumistega, soodustab kogemuslikku õppimist. Antud sekkumised on hoolikalt välja töötatud, kohandatavad erinevate häkatoni kontekstide ja turvalisuse aspektide õpetamise sisuga ning täiustatud tegevusuuringute tsüklite kaudu, et võimaldada osalejatel navigeerida ja rakendada IoTA-SRM raamistikku. Meie integreeritud raamistik ja häkatoni lähenemisviis täitsid kahte rolli: haridusmudel, mis on suunatud turvariskide haldamisele asjade interneti süsteemides, ja IoTA-SRM-i raamistiku hindamismehhanism häkatoni iteratsioonide kaudu, võimaldades selliselt selle iteratiivset täiustamist. See doktoritöö aitab kaasa IoT SRMi teoreetilisele mõistmisele ja IoT turvariskide juhtimise praktilistele lähenemisviisidele. Lisaks pakub see meetodit tulevaste spetsialistide koolitamiseks selles kiiresti arenevas valdkonnas. Siin esitatud leiud ja metoodikad loovad aluse tulevastele püüdlustele IoT SRM-i rakendamisel ja õpetamisel, näitlikustades sünergilist seost teoreetiliste turvakontseptsioonide ja nende praktilise rakendamise vahel. With the rise of network-capable devices and their vulnerabilities, attention has focused on security risk management (SRM) in the internet of things (IoT). The potential attack surface expands as the IoT ecosystem grows, underscoring the need for robust security measures against evolving threats. Yet, existing research reveals gaps in fully integrating the IoT architecture into SRM activities. Practical implementation challenges further complicate the intricate nature of IoT systems and the daunting task of SRM. Consequently, the disparity between theory and practice undermines the likelihood of successfully implementing security frameworks in real-world IoT systems, leaving them susceptible to an ever-evolving threat landscape. To address these challenges, we introduce the IoT Architecture-based Security Risk Management (IoTA-SRM) framework, offering a comprehensive and integrative approach to SRM in IoT systems. By integrating the IoT architecture into security risk management, stakeholders can ensure comprehensive coverage of their IoT system components and interactions. The framework was evaluated involving expert-validated case studies in autonomous vehicle systems to ascertain its practicality, adaptability, and benefits. However, though the practicality of the framework is seen in this case analysis, its theoretical richness may remain abstract for practitioners during application. Given the intricacy of IoT systems and the dynamic nature of threats, traditional instructional approaches alone prove insufficient to facilitate the framework's transition from theoretical understanding to practical application, necessitating educational methods that transcend conventional instruction. Thus, an intervention-based hackathon approach was developed. Enhanced with tailored interventions, this approach fosters an experiential learning approach. These interventions are carefully crafted, adaptable to diverse hackathon contexts and security learning content, and refined through action research cycles to enable participants to navigate and apply the IoTA-SRM framework. Our integrated framework and hackathon approach served dual roles: an educational model targeting SRM in IoT systems and an evaluation mechanism for the IoTA-SRM framework through hackathon iterations, thus allowing for its iterative refinement. This thesis contributes to the theoretical understanding of IoT SRM and practical approaches for IoT security risk management. It further offers a method for educating future professionals in this rapidly evolving field. The findings and methodologies presented herein provide a basis for future endeavours in applying and teaching IoT SRM, exemplifying the synergistic relationship between theoretical security concepts and their practical application. https://www.ester.ee/record=b5645350

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    Authors: Masnavi, Houman;

    Liikumise planeerimine on oluline osa robotite ja automatiseerimise valdkonnas. See hõlmab parima liikumiste või tegevuste järjestuse välja selgitamist, et robot saavutaks kindla eesmärgi, järgides teatud reegleid. Käesolev lõputöö keskendub teatud tüüpi liikumise planeerimisele, mida nimetatakse nähtavusele orienteeritud navigatsiooniks (VAN). VAN-i kasutatakse juhul, kui soovime, et robot liiguks kahe punkti vahel või järgiks teed, hoides alati teatud objekte oma vaateväljas. VAN-il on erinevaid rakendusi erinevates valdkondades. Näiteks sihtmärgi jälgimisel ja õhufotograafias aitab VAN tagada, et robot näeks alati sihtmärki, vältides takistusi. Seisundi hindamisel ja asukoha määramisel aitab VAN parandada täpsust, planeerides teid, mis säilitavad markerite nagu fidutsiaalsete markerite või majakate nähtavust. VAN võimaldab ka suuremate maapealsete robotite ja väiksemate õhurobotite koostööd. Maapealne robot saab juhendada õhurobotit seni, kuni nad saavad teineteist näha. Siiski on VAN-il kaks peamist väljakutset. Esiteks tuleb välja töötada uued algoritmid, mis suudavad hakkama saada keerulistes olukordades keskkondades, mis on täis takistusi. Teiseks peavad lahendused kiiresti töötama väikestel seadmetel, mida saab kanda väikeste robotite nagu droonide peal. Käesolev lõputöö pakub välja uued liikumise planeerimise algoritmid, mis on spetsiaalselt kavandatud nähtavusele orienteeritud navigatsiooni jaoks. Need algoritmid suudavad toime tulla keeruliste keskkondadega, kus on nii paiksed kui ka liikuvad takistused. Samuti töötavad need reaalajas piiratud ressurssidega väikestel seadmetel. Algoritme on põhjalikult testitud nii simulatsioonides kui ka reaalmaailma keskkondades ning võrreldud olemasolevate lähenemisviisidega. Pakutud algoritmid ületavad olemasolevaid algoritme erinevates aspektides, näiteks vähendades varjatuse aega, minimeerides juhtimispingutusi ja vajades vähem arvutusaega. Motion planning is an important part of robotics and automation. It involves figuring out the best sequence of movements or actions for a robot to achieve a specific goal while following certain rules. This thesis focuses on a particular type of motion planning called Visibility Aware Navigation (VAN). VAN is used when we want the robot to move between two points or follow a path while always keeping certain objects in its field of view. VAN has various applications in different areas. For example, in target tracking and aerial cinematography, VAN helps ensure that the robot can always see its target while avoiding obstacles. In state estimation and localization, VAN helps improve accuracy by planning paths that maintain visibility of markers like fiducial markers or beacons. VAN can also enable cooperation between larger ground robots and smaller aerial robots. The ground robot can guide the aerial robot as long as they can see each other. However, there are two main challenges with VAN. First, new algorithms need to be developed that can handle complex situations in environments cluttered with obstacles. Second, the solutions should work quickly on small devices that can be carried by small robots like drones. This thesis proposes new motion planning algorithms specifically designed for visibility-aware navigation. These algorithms can handle complex environments with both stationary and moving obstacles. They also perform in real-time on small devices with limited resources. The algorithms are extensively tested in both simulations and real-world environments and compared to existing approaches. The proposed algorithms outperform the existing ones in different aspects such as reducing occlusion time, minimizing control effort, and requiring less computation time. Väitekirja elektrooniline versioon ei sisalda publikatsioone https://www.ester.ee/record=b5567344

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    Authors: Buo, Isaac Newton Kwasi;

    Cities are warmer than their surrounding rural areas because of the abundance of impervious and heat-trapping surfaces. During a heatwave, a city’s ambient temperature rises to levels detrimental to the well-being of urban dwellers. This is known as urban overheating. Current climate projections indicate that heatwaves will increase in frequency with higher intensities. Lack of spatially explicit thermal data at various scales poses a significant challenge for city governments in developing comprehensive heat mitigation plans. This thesis proposes using remote sensing, machine learning, and radiative flux modeling to generate multi-scale thermal datasets for evaluating urban overheating. The thesis addresses two challenges when using satellite land surface temperature (LST) to assess urban overheating—the first concerns missing data due to clouds obscuring the satellite’s view of the Earth. The second is the trade-off between spatial and temporal resolution that must be made when using LST to assess overheating. The thesis created machine learning models to fill gaps in satellite LST and generate synthetic LST at local climate scales to address these challenges. The thesis also examines how Mean Radiant Temperature (TMRT) - the total heat load on a human body can be modeled for large cities at high spatial resolutions and how shade available to pedestrians can be quantified by calculating sidewalk shade coverage. When combined with socio-economic and demographic data, the datasets generated in the thesis will inform heat action plans in the respective study sites. Further research should improve machine learning models to predict LST and combine pedestrian heat exposure with travel patterns data. The thesis concludes by emphasizing the importance of making cities heat-ready to ensure the safety and well-being of urban dwellers, especially vulnerable populations. Linnas on palju soojust neelavaid pindu, mis muudavad linna ümbritsevast maapiirkonnast soojemaks. Kuumalaine ajal tõuseb linna õhutemperatuur tasemeni, mis kahjustab inimeste tervist ja heaolu: linn kuumeneb üle. Kliimaprognoosid näitavad, et kuumalained muutuvad sagedasemaks ja intensiivsusemaks. Ruumiliste soojusandmete puudumine takistab oluliselt kuuma leevendamise kavade väljatöötamist. Väitekirjas kasutatakse kaugseiret, masinõpet ja kiirgusvoo erinevas mõõtkavas modelleerimist linnade ülekuumenemise hindamiseks. Kaugseire andmete kasutamisel on kaks probleemi: pilvede tõttu tekkivad andmelüngad ja erinevatelt satelliitidelt saadud andmete erineva ajasamm ruumiline täpsus. Töös loodi masinõppe mudelid, et täita lüngad satelliidi mõõdetud maapinna temperatuuri andmestikus ja luua suure lahutusvõimega sünteetilisi kaarte. Uuriti ka, kuidas keskmist kiirgustemperatuuri ehk inimkeha soojuskoormust saab modelleerida suurtes linnades suure ruumilise lahutusvõimega ning kuidas jalakäijale majade ja puude varju hinnata kõnnitee varju katvust arvutades. Töös genereeritud andmestik on oluline sisend linna ülekuumenemise vältimisel. Edasised uuringud peavad keskenduma masinõppemudelite täiustamisele, et ennustada maapinna temperatuuri ja modelleerida inimkeha soojuskoormust sõltuvalt liikumisharjumustest. Töös loodud andmestik koos sotsialmajanduslike ja demograafiliste andmetega võimaldab linnakeskkonda ülekuumenemisele paremini kohandada, tagamaks elanikkonna ohutuse ja heaolu. Väitekirja elektrooniline versioon ei sisalda publikatsioone https://www.ester.ee/record=b5564856

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    Authors: Uusõue, Mirjam;

    Clean water is necessary for all living organisms, but human activities and climate change have deteriorated water quality in many regions. It is important to monitor water bodies to take the necessary measures. Conventional contact measurements have been carried out for decades. However, they are time-consuming and expensive and can cover only a small number of water bodies. This is insufficient as changes in waterbodies are often rapid and occur over large areas. Remote sensing methods have been introduced to fill these gaps in temporal and spatial coverage. On the other hand, there is a need to study parameters that impact the formation of water-leaving signal in order to increase the accuracy of remote sensing products. One such substance that requires further investigation is suspended particulate matter. It consists of mineral and organic particles suspended in the water column due to natural processes (waves, erosion, river transport) and human activities (trawling, dredging, construction). The high content of suspended particles increases the water turbidity, consequently reducing the light availability. In turn, this worsens aquatic organisms' living conditions and alters physical processes (like radiative heating) in the water environment. Suspended particles can contain harmful substances such as organic pollutants and heavy metals. We studied the behaviour of heavy metal-rich sediments in Portman Bay (one of the most polluted areas of the Mediterranean), in southern Spain, after trawling the sea bottom. Coarse and heavy particles and flocs settled quickly. Fine particles remained in suspension for a longer time. Therefore, the content of heavy metals in the water increased. From an optical point of view, the suspended particles mainly scatter light. The optical properties of suspended particles (light absorption, scattering, backscattering/scattering ratio) were studied in several Estonian coastal areas. The backscattering ratio, which is used as a constant in bio-optical remote sensing algorithms, was highly variable, depending on the conditions (algal bloom, storm). Such variability was also observed for other optical properties. It was found that small particles resuspended by a storm aggregated into larger flocs (> 30 μm), affecting the particles' optical properties in the Pärnu Bay, which has very low salinity and little organic content. This study shows that using an assumption that the backscattering ratio is a fixed constant reduces the accuracy of remote sensing products. Puhas vesi on eluks vajalik kõikidele elusolenditele, kuid inimtegevuse ja kliimamuutuste mõjul on paljudes piirkondades veekvaliteet halvenenud. Veekogude seisundi hindamiseks ja vajalike meetmete kasutusele võtmiseks, on tarvis neid seirata. Aastakümneid on tehtud kontaktmõõtmisi, kuid need on ajakulukad ja kallid ning nendega on keeruline jälgida kiireid muutusi suurtel aladel. Viimastel aastakümnetel on kasutusele võetud kaugseire meetodid, mis võimaldavad neid puudujääke täita. Selleks, et mõista mida kaugseire instrument mõõdab on vaja teada parameetreid, mis kaugseire signaali ja selle interpreteerimist mõjutavad. Üheks selliseks aineks on heljum. Heljum koosneb veemassis hõljuvatest mineraalsetest (setted) ja orgaanilistest osakestest ja see jõuab veemassi looduslike protsesside (lainetus, erosioon, jõgede transport) ja inimtegevuse (traalimine, süvendamine, ehitamine) tagajärjel. Kõrge heljumi sisaldus veemassis muudab vee häguseks, mõjutades valguse jõudmist sügavamatesse veekihtidesse, mis omakorda halvendab vee, kui elukeskkonna seisundit. Heljum võib sisaldada kahjulikke aineid, nagu orgaanilised saasteained ja raskemetallid. Seetõttu uurisime Portmani lahes (Vahemere üks reostatumaid alasid), Lõuna-Hispaanias põhjasetteid, milles on kõrge raskemetallide sisaldus, ning kuidas need setted jõuavad veesambasse traalimise mõjul. Suured osakesed settisid kiiresti. Väikesed osakesed, millega liitusid raskemetallid, jäid veemassi pikemaks ajaks. Seetõttu raskemetallide sisaldus vees tõusis. Eesti rannikualadel uuriti heljumi optilisi omadusi (valguse neeldumist, hajumist, tagasihajumise/hajumise suhet). Leiti, et tagasihajumise/hajumise suhe, mida kasutatakse bio-optilistes kaugseire algoritmides konstandina on tegelikult väga muutlik ning sõltub hetke tingimustest (vetikaõitseng, torm). Sellist varieeruvust täheldati ka muude optiliste omadustega seoses. Leiti, et väga väikese soolsuse ja vähese orgaanika sisaldusega Pärnu lahes agregeerisid väikesed tormi mõjul veemassi keerutatud osakesed suuremateks osakesteks (> 30 μm) mõjutades vee optilisi omadusi ning seega ka kaugseire signaali. Väitekirja elektrooniline versioon ei sisalda publikatsioone https://www.ester.ee/record=b5553931

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    Authors: Mass, Jakob;

    Värkvõrk, ehk Asjade Internet (Internet of Things, lüh IoT) edendab lahendusi nagu nn tark linn, kus meid igapäevaselt ümbritsevad objektid on ühendatud infosüsteemidega ja ka üksteisega. Selliseks näiteks võib olla teekatete seisukorra monitoorimissüsteem. Võrku ühendatud sõidukitelt (nt bussidelt) kogutakse videomaterjali, mida seejärel töödeldakse, et tuvastada löökauke või lume kogunemist. Tavaliselt hõlmab selline lahendus keeruka tsentraalse süsteemi ehitamist. Otsuste langetamiseks (nt milliseid sõidukeid parasjagu protsessi kaasata) vajab keskne süsteem pidevat ühendust kõigi IoT seadmetega. Seadmete hulga kasvades võib keskne lahendus aga muutuda pudelikaelaks. Selliste protsesside disaini, haldust, automatiseerimist ja seiret hõlbustavad märkimisväärselt äriprotsesside halduse (Business Process Management, lüh BPM) valdkonna standardid ja tööriistad. Paraku ei ole BPM tehnoloogiad koheselt kasutatavad uute paradigmadega nagu Udu- ja Servaarvutus, mis tuleviku värkvõrgu jaoks vajalikud on. Nende puhul liigub suur osa otsustustest ja arvutustest üksikutest andmekeskustest servavõrgu seadmetele, mis asuvad lõppkasutajatele ja IoT seadmetele lähemal. Videotöötlust võiks teostada mini-andmekeskustes, mis on paigaldatud üle linna, näiteks bussipeatustesse. Arvestades IoT seadmete üha suurenevat hulka, vähendab selline koormuse jaotamine vähendab riski, et tsentraalne andmekeskust ülekoormamist. Doktoritöö uurib, kuidas mobiilsusega seonduvaid IoT protsesse taoliselt ümber korraldada, kohanedes pidevalt muutlikule, liikuvate seadmetega täidetud servavõrgule. Nimelt on ühendused katkendlikud, mistõttu otsuste langetus ja planeerimine peavad arvestama muuhulgas mobiilseadmete liikumistrajektoore. Töö raames valminud prototüüpe testiti Android seadmetel ja simulatsioonides. Lisaks valmis tööriistakomplekt STEP-ONE, mis võimaldab teadlastel hõlpsalt simuleerida ja analüüsida taolisi probleeme erinevais realistlikes stsenaariumites nagu seda on tark linn. The Internet of Things (IoT) promotes solutions such as a smart city, where everyday objects connect with info systems and each other. One example is a road condition monitoring system, where connected vehicles, such as buses, capture video, which is then processed to detect potholes and snow build-up. Building such a solution typically involves establishing a complex centralised system. The centralised approach may become a bottleneck as the number of IoT devices keeps growing. It relies on constant connectivity to all involved devices to make decisions, such as which vehicles to involve in the process. Designing, automating, managing, and monitoring such processes can greatly be supported using the standards and software systems provided by the field of Business Process Management (BPM). However, BPM techniques are not directly applicable to new computing paradigms, such as Fog Computing and Edge Computing, on which the future of IoT relies. Here, a lot of decision-making and processing is moved from central data-centers to devices in the network edge, near the end-users and IoT sensors. For example, video could be processed in mini-datacenters deployed throughout the city, e.g., at bus stops. This load distribution reduces the risk of the ever-growing number of IoT devices overloading the data center. This thesis studies how to reorganise the process execution in this decentralised fashion, where processes must dynamically adapt to the volatile edge environment filled with moving devices. Namely, connectivity is intermittent, so decision-making and planning need to involve factors such as the movement trajectories of mobile devices. We examined this issue in simulations and with a prototype for Android smartphones. We also showcase the STEP-ONE toolset, allowing researchers to conveniently simulate and analyse these issues in different realistic scenarios, such as those in a smart city. https://www.ester.ee/record=b5525514

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    Authors: Montibeller, Bruno;

    Forests are strongly impacted by human activities. While the deforestation is very likely the most common examples of human impact on forested areas, the remaining standing forests are susceptible to other types of direct or indirect forest degradation by humans. The direct human-induced impacts can be exemplified by forest fragmentation or selective logging while the indirect human-induced impacts can be related to the changes in the ecosystem services (e.g., carbon and water cycling) induced by anthropogenic climate change. The aim of this thesis was to evaluate two processes related to forest degradation: (i) fragmentation of tropical forest cover in the Brazilian Amazon and (ii) changes in forest evapotranspiration over/across the Baltic countries and the carbon cycle in undisturbed forest areas across Europe. Satellite derived data and spatial analyses were used to assess the impacts of forest degradation in these three different case studies. The results of this thesis showed that although the anti-deforestation initiatives have played an important role in reducing deforestation in the Brazilian Amazon region, the forest fragmentation has increased mainly because of the decrease in the size of forest loss patches and the spatial shift into areas previously isolated areas. Hence, more forest areas are potentially being degraded because of the edge effects (e.g., tree mortality) caused by the fragmentation. For the Baltic region, the results indicated an intensification of the evapotranspiration rates over undisturbed forest areas. The intensification occurred mainly during spring and early autumn months because of the longer growing season induced by the increasing temperatures during these periods. Changes in the climate patterns were also the potential cause for changes in the carbon assimilation rates over the European forests. Approximately 25% of the undisturbed European forests showed reduced total carbon assimilation. That shows the vulnerability and incapacity of certain forest areas to act as carbon sink. Metsaökosüsteemid võivad siduda kuni 12% inimtekkelisest süsihappegaasist ning tagastada atmosfääri kuni 40% kohalikest sademetest. Seetõttu on metsaökosüsteemidel oluline roll süsihappegaasi emissioonide vähendamisel ja veeringe reguleerimisel. Samal ajal väheneb metsade pindala ning metsad degradeeruvad läbi killustumise ning nende süsiniku- ja veeringe reguleerimise võime võib väheneda kliimamuutuste tõttu. Käesoleva doktoritöö eesmärgiks oli hinnata kahte metsade degradeerumisega seotud protsessi: (1) troopilise vihmametsa killustumist Brasiilia Amasoonias ja (2) muutuseid evapotranspiratsioonis ja süsinikuringes Baltikumi ja Eurooma muutumatuna püsinud metsamassiivides. Käesoleva doktoritöö tulemused näitasid, et kuigi Brasiilias on metsatustumise vastased poliitikad vähendanud metsade raadamist, siis samal ajal on suurenenud metsade killustumine, sest raiutakse väiksemate eraldiste kaupa ja liikudes endiselt varem raadamata aladele. Killustunud metsas on rohkem metsaserva, kust on süsinikukaod suuremad nii leostumise kui ka gaasilise emissioonina. Baltikumis leiti, et pikem taimekasvuperiood on suurendanud evapotranspiratsiooni kevadel ja sügisel, kuid samal ajal on suvel evapotranspiratsioon mõnedes piirkondades vähenenud. Kuigi evapotranspiratsiooni suurenemisel ei ole metsade ökosüsteemile otseselt negatiivset mõju, siis võib sellel olla ebasoovitav mõju regiooni veeringele, sest suurenenud evapotranspiratsioon suurendab tõenäosust, et suveperioodil on mullas vähem vett, mis omakorda suurendab põuaohtu. Lisaks selgus, et neljandikus Euroopa muutumatuna püsinud metsamassiivides on süsiniku sidumine vähenenud. Vähenenud süsiniku sidumisega metsamassiivid paiknesid üle kogu Euroopa ning hõlmasid erinevaid metsatüüpe. Kliimamuutuste mõjul võib metsade süsiniku sidumine väheneda veelgi rohkem, mis seab kahtluse alla varasemalt eeldatud metsade võimekuse leevendada kliimamuutuste mõjusid. Väitekirja elektrooniline versioon ei sisalda publikatsioone https://www.ester.ee/record=b5519495

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    Authors: Maksimova, Mariia; Alishani, Art; Solvak, Mihkel; Krimmer, Robert;

    As interest in the digital transformation of public administration grows, the main challenge remains to improve government governance systems and integrate a wider range of evidence into decisionmaking processes. The successful digitalization and application of such approaches improves the quality, responsiveness and flexibility of public administrations. The digialtization of processes has made it possible to use micro-level data to assess the impact of a policy or program and apply the feedback to improve the design and delivery of public services. Evidence-based policy-making evaluates programs based on their visible impacts. Large-scale data collected through digitized governance, coupled with econometric impact assessment, provides an ideal working toolkit for this. However, the current situation of European governments is one of slow adoption, as they are often slow to respond to new challenges. This is due to the static one-off impact assessment approaches used, the results of which quickly become outdated. With further digitalization, improvement of systems, and a rapidly changing situation, there is a need to speed up institutions’ ability to quickly draw working solutions to offset the effects of unexpected events in society and economy and react without delays if policy effects dissipate. This paper demonstrates how a high level of digitalization in government allows addressing such issues by automating causal impact assessment and making it a continuous part of the service delivery. The use case is an automated system for assessing active labour market policies in Estonia using individual-level data from government digital registers. Building on this, it shows how impact assessment automation depends on automatically generated data, only available due to the digitalization of other public services, and how versatile it is when it comes to proving casual evidence in a suddenly changing environment.

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    Authors: Vahter, Tanel;

    This doctoral thesis provides a deeper understanding of the ecology of soil fungi that form mycorrhizas in arable landscapes. These fungi provide plants with much needed soil nutrients and are therefore a vital part of sustainable food production. One of the central aims was to understand how the common agricultural practices used in the fields affect these key fungi. In our studies we found that much like in the rest of Europe, there are large differences in the diversity of mycorrhizal fungi in arable field soils. Differences in mycorrhizal fungal richness between the most and least diverse fields were sixfold. The major factors decreasing mycorrhizal fungal diversity were the use of synthetic fertilizers and pesticides but also biodiversity impoverished agricultural landscapes. In addition, we learned that temporary grasslands within the crop rotations have important implications for sustaining soil fungal biodiversity. Furthermore, we found that the crop varieties sown can have an impact on mycorrhizal fungi, with some older varieties faring better in organically managed soils than newer breeds. Although the plants’ affinity to mycorrhizal fungi was not clearly dependant on the era a variety was bred, it does show that we should bear mycorrhizal associations in mind when breeding crops of the future. We also experimented with creating diverse vegetation assemblages in biodiversity impoverished landscapes, using depleted oil-shale quarries as a model system. We used native plants and sowed them onto the restoration sites together with the mycorrhizal fungi they naturally grow with. Using this methodology, we were able to bring dosens of plant species into a former biodiversity desert, highlighting the possibilities of restoring biodiversity hot-spots also in other areas. To conclude, we emphasize that safeguarding the biodiversity of vital mycorrhizal fungi is possible even with the measures available to farmers today. More organic fertilizers with diverse crop rotations for disease and weed control, accompanied by the biodiversity support of diverse landscapes is something that would pave the way for sustainable food production. Doktoritöö käigus uuriti taimede ja seente vahelist vastastikku kasulikku kooselu, mükoriisat, moodustavate mullaseente ökoloogiat põllumajandusmaastikes. Kuna nende seente abil saavad taimed mullast vajaminevaid toitaineid, on nad oluline osa mulla elustikust ning panustavad ka põllumajanduse jätkusuutlikkusse. Töö üks põhieesmärke oli uurida, kuidas levinud põlluharimise praktikad mükoriisaseeni mõjutavad ning millised praktikad võiksid nende elurikkust suurendada. Uuringutes leidsime, et sarnaselt Lääne-Euroopaga on ka Eestis olenevalt põlluharimise viisidest mükoriisaseente elurikkuses suured erinevused – mitmekesisemate ja vaesemate põldude mükoriisaseente liigirikkuse vahe oli koguni kuuekordne. Olulisteks negatiivseteks teguriteks olid sünteetiliste väetiste ja pestitsiidide kasutamine, kuid positiivselt mõjusid orgaaniliste väetiste kasutamine ja maastikuelementide rohkus. Lisaks saime teada, et lühiajaliste rohumaade lisamine külvikorda soodustab mullaseeni ning külvikorra planeerimisel tasuks mõelda kasvatatavate sortide valiku peale. Näiteks selgus, et mõned ajaloolised nisusordid kasvavad paremini koos mahetootmise põllu mullast pärit seentega, samas kui mõni kaasaegne sort jällegi intensiivtootmise mulla seentega. Selle teadmise baasilt oleks võimalik tulevikus aretada näiteks mükoriisasõbralikke sorte nii mahe- kui tavaviljelusse. Lisaks eksperimenteerisime ka liigirikaste taimekoosluste taastamisega, luues liigivaestesse põlevkivikarjääridesse mükoriisaseente abiga kõigest mõne aastaga rohelised niidud. Sama metoodikat kasutades võiks tekitada elurikkuse tugipunkte ka intensiivselt majandatud põllumajandusmaastikesse, kus taimede, putukate ja mükoriisaseente elustik põllumajandustootjale kasu saaks tuua. Seega, kasutades rohkem orgaanilisi väetisi ja tõrjudes haiguseid ning kahjureid mitmekesise külvikorraga saab luua mükoriisaseeni soodustavad tingimused. Lisades maastikesse veel uusi ja hoides olemasolevaid elurikkuse tugipunkte, võiksime olla eeskujuks oma kodukandi kõrge elurikkuse ja sellega arvestava toidutootmisega. Väitekirja elektrooniline versioon ei sisalda publikatsioone https://www.ester.ee/record=b5449439

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    Authors: Kustavus, Allan;

    Autonomous robots are utilized in a wide range of domains, combining a large number of resources like sensors, actuators and algorithms to form a self-acting robotic system. Tools, such as ROS and TeMoto, have been developed to allow for handling and managing of resources composing such systems. While TeMoto is meant to handle dynamic and changing situations the current implementation of its Resource Registrar, a core TeMoto component tasked with allocating, deallocating and tracking of resources, is tightly coupled to ROS, making it difficult to modify and improve. As a result of this thesis, the Resource Registrar (RR) of TeMoto was completely redesigned to be extendable to other robotic middleware, such as ROS2, and to improve TeMoto’s robustness with features, e.g., full recovery of the RR, that were unattainable with the previous design.

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    Authors: Hartmann, Dennis;
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    Authors: Affia, Abasi-amefon Obot;

    Võrgutoega seadmete ja nende haavatavuste kasvuga on hakatud rohkem tähelepanu pöörama asjade interneti (IoT) turvariskide haldamisele (SRM). Võimalik ründepind laieneb asjade Interneti ökosüsteemi kasvades, tuues esile vajadust tugevate turvameetmete järele arenevate ohtude vastu. Olemasolevad uuringud toovad siiski välja lünki asjade Interneti arhitektuuri täielikul integreerimisel turvariskide haldamisse. Rakendamise praktilised väljakutsed tõstavad niigi keerukate asjade interneti süsteemide keerukust ja teevad turvariskide haldamise ülesannet veelgi keerulisemaks. Seega õõnestab teooria ja praktika vaheline ebavõrdsus turvaraamistike eduka rakendamise tõenäosust reaalsetes asjade interneti süsteemides, muutes need vastuvõtlikuks pidevalt arenevale ohumaastikule. Nende väljakutsete lahendamiseks tutvustame IoT-arhitektuuril põhinevat turvariskide haldamise (IoTA-SRM) raamistikku, mis pakub terviklikku ja integreeritavat lähenemist tuvariskide haldamisele asjade interneti süsteemides. Integreerides IoT arhitektuuri turvariskide haldamisse, saavad sidusrühmad tagada oma IoT süsteemi komponentide ja interaktsioonide igakülgse katvuse. Raamistikku hinnati autonoomsete sõidukisüsteemide ekspertide poolt läbiviidud juhtumiuuringute abil, et teha kindlaks selle praktilisus, kohanemisvõime ja eelised. Kuigi antud juhtumite analüüsis nähakse raamistiku praktilisust, võib selle teoreetiline rikkus jääda praktikutele rakendamise ajal abstraktseks. Arvestades asjade interneti süsteemide keerukust ja ohtude dünaamilist olemust, ei piisa üksi traditsioonilistest õpetamisviisidest, et hõlbustada raamistiku üleminekut teoreetiliselt arusaamiselt praktilisele rakendusele, mistõttu on vaja tavapärasest õpetamisviisidest edasi ulatuvaid haridusmeetodeid. Seega töötati välja sekkumispõhine häkatoni lähenemine. See lähenemisviis, mida täiustatakse kohandatud sekkumistega, soodustab kogemuslikku õppimist. Antud sekkumised on hoolikalt välja töötatud, kohandatavad erinevate häkatoni kontekstide ja turvalisuse aspektide õpetamise sisuga ning täiustatud tegevusuuringute tsüklite kaudu, et võimaldada osalejatel navigeerida ja rakendada IoTA-SRM raamistikku. Meie integreeritud raamistik ja häkatoni lähenemisviis täitsid kahte rolli: haridusmudel, mis on suunatud turvariskide haldamisele asjade interneti süsteemides, ja IoTA-SRM-i raamistiku hindamismehhanism häkatoni iteratsioonide kaudu, võimaldades selliselt selle iteratiivset täiustamist. See doktoritöö aitab kaasa IoT SRMi teoreetilisele mõistmisele ja IoT turvariskide juhtimise praktilistele lähenemisviisidele. Lisaks pakub see meetodit tulevaste spetsialistide koolitamiseks selles kiiresti arenevas valdkonnas. Siin esitatud leiud ja metoodikad loovad aluse tulevastele püüdlustele IoT SRM-i rakendamisel ja õpetamisel, näitlikustades sünergilist seost teoreetiliste turvakontseptsioonide ja nende praktilise rakendamise vahel. With the rise of network-capable devices and their vulnerabilities, attention has focused on security risk management (SRM) in the internet of things (IoT). The potential attack surface expands as the IoT ecosystem grows, underscoring the need for robust security measures against evolving threats. Yet, existing research reveals gaps in fully integrating the IoT architecture into SRM activities. Practical implementation challenges further complicate the intricate nature of IoT systems and the daunting task of SRM. Consequently, the disparity between theory and practice undermines the likelihood of successfully implementing security frameworks in real-world IoT systems, leaving them susceptible to an ever-evolving threat landscape. To address these challenges, we introduce the IoT Architecture-based Security Risk Management (IoTA-SRM) framework, offering a comprehensive and integrative approach to SRM in IoT systems. By integrating the IoT architecture into security risk management, stakeholders can ensure comprehensive coverage of their IoT system components and interactions. The framework was evaluated involving expert-validated case studies in autonomous vehicle systems to ascertain its practicality, adaptability, and benefits. However, though the practicality of the framework is seen in this case analysis, its theoretical richness may remain abstract for practitioners during application. Given the intricacy of IoT systems and the dynamic nature of threats, traditional instructional approaches alone prove insufficient to facilitate the framework's transition from theoretical understanding to practical application, necessitating educational methods that transcend conventional instruction. Thus, an intervention-based hackathon approach was developed. Enhanced with tailored interventions, this approach fosters an experiential learning approach. These interventions are carefully crafted, adaptable to diverse hackathon contexts and security learning content, and refined through action research cycles to enable participants to navigate and apply the IoTA-SRM framework. Our integrated framework and hackathon approach served dual roles: an educational model targeting SRM in IoT systems and an evaluation mechanism for the IoTA-SRM framework through hackathon iterations, thus allowing for its iterative refinement. This thesis contributes to the theoretical understanding of IoT SRM and practical approaches for IoT security risk management. It further offers a method for educating future professionals in this rapidly evolving field. The findings and methodologies presented herein provide a basis for future endeavours in applying and teaching IoT SRM, exemplifying the synergistic relationship between theoretical security concepts and their practical application. https://www.ester.ee/record=b5645350

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    Authors: Masnavi, Houman;

    Liikumise planeerimine on oluline osa robotite ja automatiseerimise valdkonnas. See hõlmab parima liikumiste või tegevuste järjestuse välja selgitamist, et robot saavutaks kindla eesmärgi, järgides teatud reegleid. Käesolev lõputöö keskendub teatud tüüpi liikumise planeerimisele, mida nimetatakse nähtavusele orienteeritud navigatsiooniks (VAN). VAN-i kasutatakse juhul, kui soovime, et robot liiguks kahe punkti vahel või järgiks teed, hoides alati teatud objekte oma vaateväljas. VAN-il on erinevaid rakendusi erinevates valdkondades. Näiteks sihtmärgi jälgimisel ja õhufotograafias aitab VAN tagada, et robot näeks alati sihtmärki, vältides takistusi. Seisundi hindamisel ja asukoha määramisel aitab VAN parandada täpsust, planeerides teid, mis säilitavad markerite nagu fidutsiaalsete markerite või majakate nähtavust. VAN võimaldab ka suuremate maapealsete robotite ja väiksemate õhurobotite koostööd. Maapealne robot saab juhendada õhurobotit seni, kuni nad saavad teineteist näha. Siiski on VAN-il kaks peamist väljakutset. Esiteks tuleb välja töötada uued algoritmid, mis suudavad hakkama saada keerulistes olukordades keskkondades, mis on täis takistusi. Teiseks peavad lahendused kiiresti töötama väikestel seadmetel, mida saab kanda väikeste robotite nagu droonide peal. Käesolev lõputöö pakub välja uued liikumise planeerimise algoritmid, mis on spetsiaalselt kavandatud nähtavusele orienteeritud navigatsiooni jaoks. Need algoritmid suudavad toime tulla keeruliste keskkondadega, kus on nii paiksed kui ka liikuvad takistused. Samuti töötavad need reaalajas piiratud ressurssidega väikestel seadmetel. Algoritme on põhjalikult testitud nii simulatsioonides kui ka reaalmaailma keskkondades ning võrreldud olemasolevate lähenemisviisidega. Pakutud algoritmid ületavad olemasolevaid algoritme erinevates aspektides, näiteks vähendades varjatuse aega, minimeerides juhtimispingutusi ja vajades vähem arvutusaega. Motion planning is an important part of robotics and automation. It involves figuring out the best sequence of movements or actions for a robot to achieve a specific goal while following certain rules. This thesis focuses on a particular type of motion planning called Visibility Aware Navigation (VAN). VAN is used when we want the robot to move between two points or follow a path while always keeping certain objects in its field of view. VAN has various applications in different areas. For example, in target tracking and aerial cinematography, VAN helps ensure that the robot can always see its target while avoiding obstacles. In state estimation and localization, VAN helps improve accuracy by planning paths that maintain visibility of markers like fiducial markers or beacons. VAN can also enable cooperation between larger ground robots and smaller aerial robots. The ground robot can guide the aerial robot as long as they can see each other. However, there are two main challenges with VAN. First, new algorithms need to be developed that can handle complex situations in environments cluttered with obstacles. Second, the solutions should work quickly on small devices that can be carried by small robots like drones. This thesis proposes new motion planning algorithms specifically designed for visibility-aware navigation. These algorithms can handle complex environments with both stationary and moving obstacles. They also perform in real-time on small devices with limited resources. The algorithms are extensively tested in both simulations and real-world environments and compared to existing approaches. The proposed algorithms outperform the existing ones in different aspects such as reducing occlusion time, minimizing control effort, and requiring less computation time. Väitekirja elektrooniline versioon ei sisalda publikatsioone https://www.ester.ee/record=b5567344

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    Authors: Buo, Isaac Newton Kwasi;

    Cities are warmer than their surrounding rural areas because of the abundance of impervious and heat-trapping surfaces. During a heatwave, a city’s ambient temperature rises to levels detrimental to the well-being of urban dwellers. This is known as urban overheating. Current climate projections indicate that heatwaves will increase in frequency with higher intensities. Lack of spatially explicit thermal data at various scales poses a significant challenge for city governments in developing comprehensive heat mitigation plans. This thesis proposes using remote sensing, machine learning, and radiative flux modeling to generate multi-scale thermal datasets for evaluating urban overheating. The thesis addresses two challenges when using satellite land surface temperature (LST) to assess urban overheating—the first concerns missing data due to clouds obscuring the satellite’s view of the Earth. The second is the trade-off between spatial and temporal resolution that must be made when using LST to assess overheating. The thesis created machine learning models to fill gaps in satellite LST and generate synthetic LST at local climate scales to address these challenges. The thesis also examines how Mean Radiant Temperature (TMRT) - the total heat load on a human body can be modeled for large cities at high spatial resolutions and how shade available to pedestrians can be quantified by calculating sidewalk shade coverage. When combined with socio-economic and demographic data, the datasets generated in the thesis will inform heat action plans in the respective study sites. Further research should improve machine learning models to predict LST and combine pedestrian heat exposure with travel patterns data. The thesis concludes by emphasizing the importance of making cities heat-ready to ensure the safety and well-being of urban dwellers, especially vulnerable populations. Linnas on palju soojust neelavaid pindu, mis muudavad linna ümbritsevast maapiirkonnast soojemaks. Kuumalaine ajal tõuseb linna õhutemperatuur tasemeni, mis kahjustab inimeste tervist ja heaolu: linn kuumeneb üle. Kliimaprognoosid näitavad, et kuumalained muutuvad sagedasemaks ja intensiivsusemaks. Ruumiliste soojusandmete puudumine takistab oluliselt kuuma leevendamise kavade väljatöötamist. Väitekirjas kasutatakse kaugseiret, masinõpet ja kiirgusvoo erinevas mõõtkavas modelleerimist linnade ülekuumenemise hindamiseks. Kaugseire andmete kasutamisel on kaks probleemi: pilvede tõttu tekkivad andmelüngad ja erinevatelt satelliitidelt saadud andmete erineva ajasamm ruumiline täpsus. Töös loodi masinõppe mudelid, et täita lüngad satelliidi mõõdetud maapinna temperatuuri andmestikus ja luua suure lahutusvõimega sünteetilisi kaarte. Uuriti ka, kuidas keskmist kiirgustemperatuuri ehk inimkeha soojuskoormust saab modelleerida suurtes linnades suure ruumilise lahutusvõimega ning kuidas jalakäijale majade ja puude varju hinnata kõnnitee varju katvust arvutades. Töös genereeritud andmestik on oluline sisend linna ülekuumenemise vältimisel. Edasised uuringud peavad keskenduma masinõppemudelite täiustamisele, et ennustada maapinna temperatuuri ja modelleerida inimkeha soojuskoormust sõltuvalt liikumisharjumustest. Töös loodud andmestik koos sotsialmajanduslike ja demograafiliste andmetega võimaldab linnakeskkonda ülekuumenemisele paremini kohandada, tagamaks elanikkonna ohutuse ja heaolu. Väitekirja elektrooniline versioon ei sisalda publikatsioone https://www.ester.ee/record=b5564856

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    Authors: Uusõue, Mirjam;

    Clean water is necessary for all living organisms, but human activities and climate change have deteriorated water quality in many regions. It is important to monitor water bodies to take the necessary measures. Conventional contact measurements have been carried out for decades. However, they are time-consuming and expensive and can cover only a small number of water bodies. This is insufficient as changes in waterbodies are often rapid and occur over large areas. Remote sensing methods have been introduced to fill these gaps in temporal and spatial coverage. On the other hand, there is a need to study parameters that impact the formation of water-leaving signal in order to increase the accuracy of remote sensing products. One such substance that requires further investigation is suspended particulate matter. It consists of mineral and organic particles suspended in the water column due to natural processes (waves, erosion, river transport) and human activities (trawling, dredging, construction). The high content of suspended particles increases the water turbidity, consequently reducing the light availability. In turn, this worsens aquatic organisms' living conditions and alters physical processes (like radiative heating) in the water environment. Suspended particles can contain harmful substances such as organic pollutants and heavy metals. We studied the behaviour of heavy metal-rich sediments in Portman Bay (one of the most polluted areas of the Mediterranean), in southern Spain, after trawling the sea bottom. Coarse and heavy particles and flocs settled quickly. Fine particles remained in suspension for a longer time. Therefore, the content of heavy metals in the water increased. From an optical point of view, the suspended particles mainly scatter light. The optical properties of suspended particles (light absorption, scattering, backscattering/scattering ratio) were studied in several Estonian coastal areas. The backscattering ratio, which is used as a constant in bio-optical remote sensing algorithms, was highly variable, depending on the conditions (algal bloom, storm). Such variability was also observed for other optical properties. It was found that small particles resuspended by a storm aggregated into larger flocs (> 30 μm), affecting the particles' optical properties in the Pärnu Bay, which has very low salinity and little organic content. This study shows that using an assumption that the backscattering ratio is a fixed constant reduces the accuracy of remote sensing products. Puhas vesi on eluks vajalik kõikidele elusolenditele, kuid inimtegevuse ja kliimamuutuste mõjul on paljudes piirkondades veekvaliteet halvenenud. Veekogude seisundi hindamiseks ja vajalike meetmete kasutusele võtmiseks, on tarvis neid seirata. Aastakümneid on tehtud kontaktmõõtmisi, kuid need on ajakulukad ja kallid ning nendega on keeruline jälgida kiireid muutusi suurtel aladel. Viimastel aastakümnetel on kasutusele võetud kaugseire meetodid, mis võimaldavad neid puudujääke täita. Selleks, et mõista mida kaugseire instrument mõõdab on vaja teada parameetreid, mis kaugseire signaali ja selle interpreteerimist mõjutavad. Üheks selliseks aineks on heljum. Heljum koosneb veemassis hõljuvatest mineraalsetest (setted) ja orgaanilistest osakestest ja see jõuab veemassi looduslike protsesside (lainetus, erosioon, jõgede transport) ja inimtegevuse (traalimine, süvendamine, ehitamine) tagajärjel. Kõrge heljumi sisaldus veemassis muudab vee häguseks, mõjutades valguse jõudmist sügavamatesse veekihtidesse, mis omakorda halvendab vee, kui elukeskkonna seisundit. Heljum võib sisaldada kahjulikke aineid, nagu orgaanilised saasteained ja raskemetallid. Seetõttu uurisime Portmani lahes (Vahemere üks reostatumaid alasid), Lõuna-Hispaanias põhjasetteid, milles on kõrge raskemetallide sisaldus, ning kuidas need setted jõuavad veesambasse traalimise mõjul. Suured osakesed settisid kiiresti. Väikesed osakesed, millega liitusid raskemetallid, jäid veemassi pikemaks ajaks. Seetõttu raskemetallide sisaldus vees tõusis. Eesti rannikualadel uuriti heljumi optilisi omadusi (valguse neeldumist, hajumist, tagasihajumise/hajumise suhet). Leiti, et tagasihajumise/hajumise suhe, mida kasutatakse bio-optilistes kaugseire algoritmides konstandina on tegelikult väga muutlik ning sõltub hetke tingimustest (vetikaõitseng, torm). Sellist varieeruvust täheldati ka muude optiliste omadustega seoses. Leiti, et väga väikese soolsuse ja vähese orgaanika sisaldusega Pärnu lahes agregeerisid väikesed tormi mõjul veemassi keerutatud osakesed suuremateks osakesteks (> 30 μm) mõjutades vee optilisi omadusi ning seega ka kaugseire signaali. Väitekirja elektrooniline versioon ei sisalda publikatsioone https://www.ester.ee/record=b5553931

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    Authors: Mass, Jakob;

    Värkvõrk, ehk Asjade Internet (Internet of Things, lüh IoT) edendab lahendusi nagu nn tark linn, kus meid igapäevaselt ümbritsevad objektid on ühendatud infosüsteemidega ja ka üksteisega. Selliseks näiteks võib olla teekatete seisukorra monitoorimissüsteem. Võrku ühendatud sõidukitelt (nt bussidelt) kogutakse videomaterjali, mida seejärel töödeldakse, et tuvastada löökauke või lume kogunemist. Tavaliselt hõlmab selline lahendus keeruka tsentraalse süsteemi ehitamist. Otsuste langetamiseks (nt milliseid sõidukeid parasjagu protsessi kaasata) vajab keskne süsteem pidevat ühendust kõigi IoT seadmetega. Seadmete hulga kasvades võib keskne lahendus aga muutuda pudelikaelaks. Selliste protsesside disaini, haldust, automatiseerimist ja seiret hõlbustavad märkimisväärselt äriprotsesside halduse (Business Process Management, lüh BPM) valdkonna standardid ja tööriistad. Paraku ei ole BPM tehnoloogiad koheselt kasutatavad uute paradigmadega nagu Udu- ja Servaarvutus, mis tuleviku värkvõrgu jaoks vajalikud on. Nende puhul liigub suur osa otsustustest ja arvutustest üksikutest andmekeskustest servavõrgu seadmetele, mis asuvad lõppkasutajatele ja IoT seadmetele lähemal. Videotöötlust võiks teostada mini-andmekeskustes, mis on paigaldatud üle linna, näiteks bussipeatustesse. Arvestades IoT seadmete üha suurenevat hulka, vähendab selline koormuse jaotamine vähendab riski, et tsentraalne andmekeskust ülekoormamist. Doktoritöö uurib, kuidas mobiilsusega seonduvaid IoT protsesse taoliselt ümber korraldada, kohanedes pidevalt muutlikule, liikuvate seadmetega täidetud servavõrgule. Nimelt on ühendused katkendlikud, mistõttu otsuste langetus ja planeerimine peavad arvestama muuhulgas mobiilseadmete liikumistrajektoore. Töö raames valminud prototüüpe testiti Android seadmetel ja simulatsioonides. Lisaks valmis tööriistakomplekt STEP-ONE, mis võimaldab teadlastel hõlpsalt simuleerida ja analüüsida taolisi probleeme erinevais realistlikes stsenaariumites nagu seda on tark linn. The Internet of Things (IoT) promotes solutions such as a smart city, where everyday objects connect with info systems and each other. One example is a road condition monitoring system, where connected vehicles, such as buses, capture video, which is then processed to detect potholes and snow build-up. Building such a solution typically involves establishing a complex centralised system. The centralised approach may become a bottleneck as the number of IoT devices keeps growing. It relies on constant connectivity to all involved devices to make decisions, such as which vehicles to involve in the process. Designing, automating, managing, and monitoring such processes can greatly be supported using the standards and software systems provided by the field of Business Process Management (BPM). However, BPM techniques are not directly applicable to new computing paradigms, such as Fog Computing and Edge Computing, on which the future of IoT relies. Here, a lot of decision-making and processing is moved from central data-centers to devices in the network edge, near the end-users and IoT sensors. For example, video could be processed in mini-datacenters deployed throughout the city, e.g., at bus stops. This load distribution reduces the risk of the ever-growing number of IoT devices overloading the data center. This thesis studies how to reorganise the process execution in this decentralised fashion, where processes must dynamically adapt to the volatile edge environment filled with moving devices. Namely, connectivity is intermittent, so decision-making and planning need to involve factors such as the movement trajectories of mobile devices. We examined this issue in simulations and with a prototype for Android smartphones. We also showcase the STEP-ONE toolset, allowing researchers to conveniently simulate and analyse these issues in different realistic scenarios, such as those in a smart city. https://www.ester.ee/record=b5525514

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    Authors: Montibeller, Bruno;

    Forests are strongly impacted by human activities. While the deforestation is very likely the most common examples of human impact on forested areas, the remaining standing forests are susceptible to other types of direct or indirect forest degradation by humans. The direct human-induced impacts can be exemplified by forest fragmentation or selective logging while the indirect human-induced impacts can be related to the changes in the ecosystem services (e.g., carbon and water cycling) induced by anthropogenic climate change. The aim of this thesis was to evaluate two processes related to forest degradation: (i) fragmentation of tropical forest cover in the Brazilian Amazon and (ii) changes in forest evapotranspiration over/across the Baltic countries and the carbon cycle in undisturbed forest areas across Europe. Satellite derived data and spatial analyses were used to assess the impacts of forest degradation in these three different case studies. The results of this thesis showed that although the anti-deforestation initiatives have played an important role in reducing deforestation in the Brazilian Amazon region, the forest fragmentation has increased mainly because of the decrease in the size of forest loss patches and the spatial shift into areas previously isolated areas. Hence, more forest areas are potentially being degraded because of the edge effects (e.g., tree mortality) caused by the fragmentation. For the Baltic region, the results indicated an intensification of the evapotranspiration rates over undisturbed forest areas. The intensification occurred mainly during spring and early autumn months because of the longer growing season induced by the increasing temperatures during these periods. Changes in the climate patterns were also the potential cause for changes in the carbon assimilation rates over the European forests. Approximately 25% of the undisturbed European forests showed reduced total carbon assimilation. That shows the vulnerability and incapacity of certain forest areas to act as carbon sink. Metsaökosüsteemid võivad siduda kuni 12% inimtekkelisest süsihappegaasist ning tagastada atmosfääri kuni 40% kohalikest sademetest. Seetõttu on metsaökosüsteemidel oluline roll süsihappegaasi emissioonide vähendamisel ja veeringe reguleerimisel. Samal ajal väheneb metsade pindala ning metsad degradeeruvad läbi killustumise ning nende süsiniku- ja veeringe reguleerimise võime võib väheneda kliimamuutuste tõttu. Käesoleva doktoritöö eesmärgiks oli hinnata kahte metsade degradeerumisega seotud protsessi: (1) troopilise vihmametsa killustumist Brasiilia Amasoonias ja (2) muutuseid evapotranspiratsioonis ja süsinikuringes Baltikumi ja Eurooma muutumatuna püsinud metsamassiivides. Käesoleva doktoritöö tulemused näitasid, et kuigi Brasiilias on metsatustumise vastased poliitikad vähendanud metsade raadamist, siis samal ajal on suurenenud metsade killustumine, sest raiutakse väiksemate eraldiste kaupa ja liikudes endiselt varem raadamata aladele. Killustunud metsas on rohkem metsaserva, kust on süsinikukaod suuremad nii leostumise kui ka gaasilise emissioonina. Baltikumis leiti, et pikem taimekasvuperiood on suurendanud evapotranspiratsiooni kevadel ja sügisel, kuid samal ajal on suvel evapotranspiratsioon mõnedes piirkondades vähenenud. Kuigi evapotranspiratsiooni suurenemisel ei ole metsade ökosüsteemile otseselt negatiivset mõju, siis võib sellel olla ebasoovitav mõju regiooni veeringele, sest suurenenud evapotranspiratsioon suurendab tõenäosust, et suveperioodil on mullas vähem vett, mis omakorda suurendab põuaohtu. Lisaks selgus, et neljandikus Euroopa muutumatuna püsinud metsamassiivides on süsiniku sidumine vähenenud. Vähenenud süsiniku sidumisega metsamassiivid paiknesid üle kogu Euroopa ning hõlmasid erinevaid metsatüüpe. Kliimamuutuste mõjul võib metsade süsiniku sidumine väheneda veelgi rohkem, mis seab kahtluse alla varasemalt eeldatud metsade võimekuse leevendada kliimamuutuste mõjusid. Väitekirja elektrooniline versioon ei sisalda publikatsioone https://www.ester.ee/record=b5519495

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    Authors: Maksimova, Mariia; Alishani, Art; Solvak, Mihkel; Krimmer, Robert;

    As interest in the digital transformation of public administration grows, the main challenge remains to improve government governance systems and integrate a wider range of evidence into decisionmaking processes. The successful digitalization and application of such approaches improves the quality, responsiveness and flexibility of public administrations. The digialtization of processes has made it possible to use micro-level data to assess the impact of a policy or program and apply the feedback to improve the design and delivery of public services. Evidence-based policy-making evaluates programs based on their visible impacts. Large-scale data collected through digitized governance, coupled with econometric impact assessment, provides an ideal working toolkit for this. However, the current situation of European governments is one of slow adoption, as they are often slow to respond to new challenges. This is due to the static one-off impact assessment approaches used, the results of which quickly become outdated. With further digitalization, improvement of systems, and a rapidly changing situation, there is a need to speed up institutions’ ability to quickly draw working solutions to offset the effects of unexpected events in society and economy and react without delays if policy effects dissipate. This paper demonstrates how a high level of digitalization in government allows addressing such issues by automating causal impact assessment and making it a continuous part of the service delivery. The use case is an automated system for assessing active labour market policies in Estonia using individual-level data from government digital registers. Building on this, it shows how impact assessment automation depends on automatically generated data, only available due to the digitalization of other public services, and how versatile it is when it comes to proving casual evidence in a suddenly changing environment.

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    Authors: Vahter, Tanel;

    This doctoral thesis provides a deeper understanding of the ecology of soil fungi that form mycorrhizas in arable landscapes. These fungi provide plants with much needed soil nutrients and are therefore a vital part of sustainable food production. One of the central aims was to understand how the common agricultural practices used in the fields affect these key fungi. In our studies we found that much like in the rest of Europe, there are large differences in the diversity of mycorrhizal fungi in arable field soils. Differences in mycorrhizal fungal richness between the most and least diverse fields were sixfold. The major factors decreasing mycorrhizal fungal diversity were the use of synthetic fertilizers and pesticides but also biodiversity impoverished agricultural landscapes. In addition, we learned that temporary grasslands within the crop rotations have important implications for sustaining soil fungal biodiversity. Furthermore, we found that the crop varieties sown can have an impact on mycorrhizal fungi, with some older varieties faring better in organically managed soils than newer breeds. Although the plants’ affinity to mycorrhizal fungi was not clearly dependant on the era a variety was bred, it does show that we should bear mycorrhizal associations in mind when breeding crops of the future. We also experimented with creating diverse vegetation assemblages in biodiversity impoverished landscapes, using depleted oil-shale quarries as a model system. We used native plants and sowed them onto the restoration sites together with the mycorrhizal fungi they naturally grow with. Using this methodology, we were able to bring dosens of plant species into a former biodiversity desert, highlighting the possibilities of restoring biodiversity hot-spots also in other areas. To conclude, we emphasize that safeguarding the biodiversity of vital mycorrhizal fungi is possible even with the measures available to farmers today. More organic fertilizers with diverse crop rotations for disease and weed control, accompanied by the biodiversity support of diverse landscapes is something that would pave the way for sustainable food production. Doktoritöö käigus uuriti taimede ja seente vahelist vastastikku kasulikku kooselu, mükoriisat, moodustavate mullaseente ökoloogiat põllumajandusmaastikes. Kuna nende seente abil saavad taimed mullast vajaminevaid toitaineid, on nad oluline osa mulla elustikust ning panustavad ka põllumajanduse jätkusuutlikkusse. Töö üks põhieesmärke oli uurida, kuidas levinud põlluharimise praktikad mükoriisaseeni mõjutavad ning millised praktikad võiksid nende elurikkust suurendada. Uuringutes leidsime, et sarnaselt Lääne-Euroopaga on ka Eestis olenevalt põlluharimise viisidest mükoriisaseente elurikkuses suured erinevused – mitmekesisemate ja vaesemate põldude mükoriisaseente liigirikkuse vahe oli koguni kuuekordne. Olulisteks negatiivseteks teguriteks olid sünteetiliste väetiste ja pestitsiidide kasutamine, kuid positiivselt mõjusid orgaaniliste väetiste kasutamine ja maastikuelementide rohkus. Lisaks saime teada, et lühiajaliste rohumaade lisamine külvikorda soodustab mullaseeni ning külvikorra planeerimisel tasuks mõelda kasvatatavate sortide valiku peale. Näiteks selgus, et mõned ajaloolised nisusordid kasvavad paremini koos mahetootmise põllu mullast pärit seentega, samas kui mõni kaasaegne sort jällegi intensiivtootmise mulla seentega. Selle teadmise baasilt oleks võimalik tulevikus aretada näiteks mükoriisasõbralikke sorte nii mahe- kui tavaviljelusse. Lisaks eksperimenteerisime ka liigirikaste taimekoosluste taastamisega, luues liigivaestesse põlevkivikarjääridesse mükoriisaseente abiga kõigest mõne aastaga rohelised niidud. Sama metoodikat kasutades võiks tekitada elurikkuse tugipunkte ka intensiivselt majandatud põllumajandusmaastikesse, kus taimede, putukate ja mükoriisaseente elustik põllumajandustootjale kasu saaks tuua. Seega, kasutades rohkem orgaanilisi väetisi ja tõrjudes haiguseid ning kahjureid mitmekesise külvikorraga saab luua mükoriisaseeni soodustavad tingimused. Lisades maastikesse veel uusi ja hoides olemasolevaid elurikkuse tugipunkte, võiksime olla eeskujuks oma kodukandi kõrge elurikkuse ja sellega arvestava toidutootmisega. Väitekirja elektrooniline versioon ei sisalda publikatsioone https://www.ester.ee/record=b5449439

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    Authors: Kustavus, Allan;

    Autonomous robots are utilized in a wide range of domains, combining a large number of resources like sensors, actuators and algorithms to form a self-acting robotic system. Tools, such as ROS and TeMoto, have been developed to allow for handling and managing of resources composing such systems. While TeMoto is meant to handle dynamic and changing situations the current implementation of its Resource Registrar, a core TeMoto component tasked with allocating, deallocating and tracking of resources, is tightly coupled to ROS, making it difficult to modify and improve. As a result of this thesis, the Resource Registrar (RR) of TeMoto was completely redesigned to be extendable to other robotic middleware, such as ROS2, and to improve TeMoto’s robustness with features, e.g., full recovery of the RR, that were unattainable with the previous design.

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    Authors: Hartmann, Dennis;
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