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With the emergence of the Internet of things (IoT), plenty of battery-powered and energy-harvesting devices are being deployed to fulfill sensing and actuation tasks in a variety of application areas, such as smart homes, precision agriculture, smart cities, and industrial automation. In this context, a critical issue is that of denial-of-sleep attacks. Such attacks temporarily or permanently deprive battery-powered, energy-harvesting, or otherwise energy-constrained devices of entering energy-saving sleep modes, thereby draining their charge. At the very least, a successful denial-of-sleep attack causes a long outage of the victim device. Moreover, to put battery-powered devices back into operation, their batteries have to be replaced. This is tedious and may even be infeasible, e.g., if a battery-powered device is deployed at an inaccessible location. While the research community came up with numerous defenses against denial-of-sleep attacks, most present-day IoT protocols include no denial-of-sleep defenses at all, presumably due to a lack of awareness and unsolved integration problems. After all, despite there are many denial-of-sleep defenses, effective defenses against certain kinds of denial-of-sleep attacks are yet to be found.
The overall contribution of this dissertation is to propose a denial-of-sleep-resilient medium access control (MAC) layer for IoT devices that communicate over IEEE 802.15.4 links. Internally, our MAC layer comprises two main components. The first main component is a denial-of-sleep-resilient protocol for establishing session keys among neighboring IEEE 802.15.4 nodes. The established session keys serve the dual purpose of implementing (i) basic wireless security and (ii) complementary denial-of-sleep defenses that belong to the second main component. The second main component is a denial-of-sleep-resilient MAC protocol. Notably, this MAC protocol not only incorporates novel denial-of-sleep defenses, but also state-of-the-art mechanisms for achieving low energy consumption, high throughput, and high delivery ratios. Altogether, our MAC layer resists, or at least greatly mitigates, all denial-of-sleep attacks against it we are aware of. Furthermore, our MAC layer is self-contained and thus can act as a drop-in replacement for IEEE 802.15.4-compliant MAC layers. In fact, we implemented our MAC layer in the Contiki-NG operating system, where it seamlessly integrates into an existing protocol stack.
Dark matter, DM, has not yet been directly observed, but it has a very solid theoretical basis. There are observations that provide indirect evidence, like galactic rotation curves that show that the galaxies are rotating too fast to keep their constituent parts, and galaxy clusters that bends the light coming from behind-lying galaxies more than expected with respect to the mass that can be calculated from what can be visibly seen. These observations, among many others, can be explained with theories that include DM. The missing piece is to detect something that can exclusively be explained by DM. Direct observation in a particle accelerator is one way and indirect detection using telescopes is another. This thesis is focused on the latter method.
The Very Energetic Radiation Imaging Telescope Array System, V ERITAS, is a telescope array that detects Cherenkov radiation. Theory predicts that DM particles annihilate into, e.g., a γγ pair and create a distinctive energy spectrum when detected by such telescopes, e.i., a monoenergetic line at the same energy as the particle mass. This so called ”smoking-gun” signature is sought with a sliding window line search within the sub-range ∼ 0.3 − 10 TeV of the VERITAS energy range, ∼ 0.01 − 30 TeV.
Standard analysis within the VERITAS collaboration uses Hillas analysis and look-up tables, acquired by analysing particle simulations, to calculate the energy of the particle causing the Cherenkov shower. In this thesis, an improved analysis method has been used. Modelling each shower as a 3Dgaussian should increase the energy recreation quality. Five dwarf spheroidal galaxies were chosen as targets with a total of ∼ 224 hours of data. The targets were analysed individually and stacked. Particle simulations were based on two simulation packages, CARE and GrISU.
Improvements have been made to the energy resolution and bias correction, up to a few percent each, in comparison to standard analysis. Nevertheless, no line with a relevant significance has been detected. The most promising line is at an energy of ∼ 422 GeV with an upper limit cross section of 8.10 · 10^−24 cm^3 s^−1 and a significance of ∼ 2.73 σ, before trials correction and ∼ 1.56 σ after. Upper limit cross sections have also been calculated for the γγ annihilation process and four other outcomes. The limits are in line with current limits using other methods, from ∼ 8.56 · 10^−26 − 6.61 · 10^−23 cm^3s^−1. Future larger telescope arrays, like the upcoming Cherenkov Telescope Array, CTA, will provide better results with the help of this analysis method.
The aim of this dissertation was to conduct a larger-scale cross-linguistic empirical investigation of similarity-based interference effects in sentence comprehension.
Interference studies can offer valuable insights into the mechanisms that are involved in long-distance dependency completion.
Many studies have investigated similarity-based interference effects, showing that syntactic and semantic information are employed during long-distance dependency formation (e.g., Arnett & Wagers, 2017; Cunnings & Sturt, 2018; Van Dyke, 2007, Van Dyke & Lewis, 2003; Van Dyke & McElree, 2011). Nevertheless, there are some important open questions in the interference literature that are critical to our understanding of the constraints involved in dependency resolution.
The first research question concerns the relative timing of syntactic and semantic interference in online sentence comprehension. Only few interference studies have investigated this question, and, to date, there is not enough data to draw conclusions with regard to their time course (Van Dyke, 2007; Van Dyke & McElree, 2011).
Our first cross-linguistic study explores the relative timing of syntactic and semantic interference in two eye-tracking reading experiments that implement the study design used in Van Dyke (2007). The first experiment tests English sentences. The second, larger-sample experiment investigates the two interference types in German.
Overall, the data suggest that syntactic and semantic interference can arise simultaneously during retrieval.
The second research question concerns a special case of semantic interference: We investigate whether cue-based retrieval interference can be caused by semantically similar items which are not embedded in a syntactic structure.
This second interference study builds on a landmark study by Van Dyke & McElree (2006). The study design used in their study is unique in that it is able to pin down the source of interference as a consequence of cue overload during retrieval, when semantic retrieval cues do not uniquely match the retrieval target. Unlike most other interference studies, this design is able to rule out encoding interference as an alternative explanation. Encoding accounts postulate that it is not cue overload at the retrieval site but the erroneous encoding of similar linguistic items in memory that leads to interference (Lewandowsky et al., 2008; Oberauer & Kliegl, 2006). While Van Dyke & McElree (2006) reported cue-based retrieval interference from sentence-external distractors, the evidence for this effect was weak. A subsequent study did not show interference of this type (Van Dyke et al., 2014). Given these inconclusive findings, further research is necessary to investigate semantic cue-based retrieval interference.
The second study in this dissertation provides a larger-scale cross-linguistic investigation of cue-based retrieval interference from sentence-external items. Three larger-sample eye-tracking studies in English, German, and Russian tested cue-based interference in the online processing of filler-gap dependencies. This study further extends the previous research by investigating interference in each language under varying task demands (Logačev & Vasishth, 2016; Swets et al., 2008).
Overall, we see some very modest support for proactive cue-based retrieval interference in English. Unexpectedly, this was observed only under a low task demand. In German and Russian, there is some evidence against the interference effect. It is possible that interference is attenuated in languages with richer case marking.
In sum, the cross-linguistic experiments on the time course of syntactic and semantic interference from sentence-internal distractors support existing evidence of syntactic and semantic interference during sentence comprehension. Our data further show that both types of interference effects can arise simultaneously. Our cross-linguistic experiments investigating semantic cue-based retrieval interference from sentence-external distractors suggest that this type of interference may arise only in specific linguistic contexts.
Successful sentence comprehension requires the comprehender to correctly figure out who did what to whom. For example, in the sentence John kicked the ball, the comprehender has to figure out who did the action of kicking and what was being kicked. This process of identifying and connecting the syntactically-related words in a sentence is called dependency completion. What are the cognitive constraints that determine dependency completion? A widely-accepted theory is cue-based retrieval. The theory maintains that dependency completion is driven by a content-addressable search for the co-dependents in memory. The cue-based retrieval explains a wide range of empirical data from several constructions including subject-verb agreement, subject-verb non-agreement, plausibility mismatch configurations, and negative polarity items.
However, there are two major empirical challenges to the theory: (i) Grammatical sentences’ data from subject-verb number agreement dependencies, where the theory predicts a slowdown at the verb in sentences like the key to the cabinet was rusty compared to the key to the cabinets was rusty, but the data are inconsistent with this prediction; and, (ii) Data from antecedent-reflexive dependencies, where a facilitation in reading times is predicted at the reflexive in the bodybuilder who worked with the trainers injured themselves vs. the bodybuilder who worked with the trainer injured themselves, but the data do not show a facilitatory effect.
The work presented in this dissertation is dedicated to building a more general theory of dependency completion that can account for the above two datasets without losing the original empirical coverage of the cue-based retrieval assumption. In two journal articles, I present computational modeling work that addresses the above two empirical challenges.
To explain the grammatical sentences’ data from subject-verb number agreement dependencies, I propose a new model that assumes that the cue-based retrieval operates on a probabilistically distorted representation of nouns in memory (Article I). This hybrid distortion-plus-retrieval model was compared against the existing candidate models using data from 17 studies on subject-verb number agreement in 4 languages. I find that the hybrid model outperforms the existing models of number agreement processing suggesting that the cue-based retrieval theory must incorporate a feature distortion assumption.
To account for the absence of facilitatory effect in antecedent-reflexive dependencies, I propose an individual difference model, which was built within the cue-based retrieval framework (Article II). The model assumes that individuals may differ in how strongly they weigh a syntactic cue over a number cue. The model was fitted to data from two studies on antecedent-reflexive dependencies, and the participant-level cue-weighting was estimated. We find that one-fourth of the participants, in both studies, weigh the syntactic cue higher than the number cue in processing reflexive dependencies and the remaining participants weigh the two cues equally. The result indicates that the absence of predicted facilitatory effect at the level of grouped data is driven by some, not all, participants who weigh syntactic cues higher than the number cue. More generally, the result demonstrates that the assumption of differential cue weighting is important for a theory of dependency completion processes. This differential cue weighting idea was independently supported by a modeling study on subject-verb non-agreement dependencies (Article III).
Overall, the cue-based retrieval, which is a general theory of dependency completion, needs to incorporate two new assumptions: (i) the nouns stored in memory can undergo probabilistic feature distortion, and (ii) the linguistic cues used for retrieval can be weighted differentially. This is the cumulative result of the modeling work presented in this dissertation.
The dissertation makes an important theoretical contribution: Sentence comprehension in humans is driven by a mechanism that assumes cue-based retrieval, probabilistic feature distortion, and differential cue weighting. This insight is theoretically important because there is some independent support for these three assumptions in sentence processing and the broader memory literature. The modeling work presented here is also methodologically important because for the first time, it demonstrates (i) how the complex models of sentence processing can be evaluated using data from multiple studies simultaneously, without oversimplifying the models, and (ii) how the inferences drawn from the individual-level behavior can be used in theory development.
Over the past decades, natural hazards, many of which are aggravated by climate change and reveal an increasing trend in frequency and intensity, have caused significant human and economic losses and pose a considerable obstacle to sustainable development. Hence, dedicated action toward disaster risk reduction is needed to understand the underlying drivers and create efficient risk mitigation plans. Such action is requested by the Sendai Framework for Disaster Risk Reduction 2015-2030 (SFDRR), a global agreement launched in 2015 that establishes stating priorities for action, e.g. an improved understanding of disaster risk. Turkey is one of the SFDRR contracting countries and has been severely affected by many natural hazards, in particular earthquakes and floods. However, disproportionately little is known about flood hazards and risks in Turkey. Therefore, this thesis aims to carry out a comprehensive analysis of flood hazards for the first time in Turkey from triggering drivers to impacts. It is intended to contribute to a better understanding of flood risks, improvements of flood risk mitigation and the facilitated monitoring of progress and achievements while implementing the SFDRR.
In order to investigate the occurrence and severity of flooding in comparison to other natural hazards in Turkey and provide an overview of the temporal and spatial distribution of flood losses, the Turkey Disaster Database (TABB) was examined for the years 1960-2014. The TABB database was reviewed through comparison with the Emergency Events Database (EM-DAT), the Dartmouth Flood Observatory database, the scientific literature and news archives. In addition, data on the most severe flood events between 1960 and 2014 were retrieved. These served as a basis for analyzing triggering mechanisms (i.e. atmospheric circulation and precipitation amounts) and aggravating pathways (i.e. topographic features, catchment size, land use types and soil properties). For this, a new approach was developed and the events were classified using hierarchical cluster analyses to identify the main influencing factor per event and provide additional information about the dominant flood pathways for severe floods. The main idea of the study was to start with the event impacts based on a bottom-up approach and identify the causes that created damaging events, instead of applying a model chain with long-term series as input and searching for potentially impacting events as model outcomes. However, within the frequency analysis of the flood-triggering circulation pattern types, it was discovered that events in terms of heavy precipitation were not included in the list of most severe floods, i.e. their impacts were not recorded in national and international loss databases but were mentioned in news archives and reported by the Turkish State Meteorological Service. This finding challenges bottom-up modelling approaches and underlines the urgent need for consistent event and loss documentation. Therefore, as a next step, the aim was to enhance the flood loss documentation by calibrating, validating and applying the United Nations Office for Disaster Risk Reduction (UNDRR) loss estimation method for the recent severe flood events (2015-2020). This provided, a consistent flood loss estimation model for Turkey, allowing governments to estimate losses as quickly as possible after events, e.g. to better coordinate financial aid.
This thesis reveals that, after earthquakes, floods have the second most destructive effects in Turkey in terms of human and economic impacts, with over 800 fatalities and US$ 885.7 million in economic losses between 1960 and 2020, and that more attention should be paid on the national scale. The clustering results of the dominant flood-producing mechanisms (e.g. circulation pattern types, extreme rainfall, sudden snowmelt) present crucial information regarding the source and pathway identification, which can be used as base information for hazard identification in the preliminary risk assessment process. The implementation of the UNDRR loss estimation model shows that the model with country-specific parameters, calibrated damage ratios and sufficient event documentation (i.e. physically damaged units) can be recommended in order to provide first estimates of the magnitude of direct economic losses, even shortly after events have occurred, since it performed well when estimates were compared to documented losses.
The presented results can contribute to improving the national disaster loss database in Turkey and thus enable a better monitoring of the national progress and achievements with regard to the targets stated by the SFDRR. In addition, the outcomes can be used to better characterize and classify flood events. Information on the main underlying factors and aggravating flood pathways further supports the selection of suitable risk reduction policies.
All input variables used in this thesis were obtained from publicly available data. The results are openly accessible and can be used for further research.
As an overall conclusion, it can be stated that consistent loss data collection and better event documentation should gain more attention for a reliable monitoring of the implementation of the SFDRR. Better event documentation should be established according to a globally accepted standard for disaster classification and loss estimation in Turkey. Ultimately, this enables stakeholders to create better risk mitigation actions based on clear hazard definitions, flood event classification and consistent loss estimations.
Companies develop process models to explicitly describe their business operations. In the same time, business operations, business processes, must adhere to various types of compliance requirements. Regulations, e.g., Sarbanes Oxley Act of 2002, internal policies, best practices are just a few sources of compliance requirements. In some cases, non-adherence to compliance requirements makes the organization subject to legal punishment. In other cases, non-adherence to compliance leads to loss of competitive advantage and thus loss of market share. Unlike the classical domain-independent behavioral correctness of business processes, compliance requirements are domain-specific. Moreover, compliance requirements change over time. New requirements might appear due to change in laws and adoption of new policies. Compliance requirements are offered or enforced by different entities that have different objectives behind these requirements. Finally, compliance requirements might affect different aspects of business processes, e.g., control flow and data flow. As a result, it is infeasible to hard-code compliance checks in tools. Rather, a repeatable process of modeling compliance rules and checking them against business processes automatically is needed. This thesis provides a formal approach to support process design-time compliance checking. Using visual patterns, it is possible to model compliance requirements concerning control flow, data flow and conditional flow rules. Each pattern is mapped into a temporal logic formula. The thesis addresses the problem of consistency checking among various compliance requirements, as they might stem from divergent sources. Also, the thesis contributes to automatically check compliance requirements against process models using model checking. We show that extra domain knowledge, other than expressed in compliance rules, is needed to reach correct decisions. In case of violations, we are able to provide a useful feedback to the user. The feedback is in the form of parts of the process model whose execution causes the violation. In some cases, our approach is capable of providing automated remedy of the violation.
Situated in an active tectonic region, Santiago de Chile, the country´s capital with more than six million inhabitants, faces tremendous earthquake hazard. Macroseismic data for the 1985 Valparaiso and the 2010 Maule events show large variations in the distribution of damage to buildings within short distances indicating strong influence of local sediments and the shape of the sediment-bedrock interface on ground motion. Therefore, a temporary seismic network was installed in the urban area for recording earthquake activity, and a study was carried out aiming to estimate site amplification derived from earthquake data and ambient noise. The analysis of earthquake data shows significant dependence on the local geological structure with regards to amplitude and duration. Moreover, the analysis of noise spectral ratios shows that they can provide a lower bound in amplitude for site amplification and, since no variability in terms of time and amplitude is observed, that it is possible to map the fundamental resonance frequency of the soil for a 26 km x 12 km area in the northern part of the Santiago de Chile basin. By inverting the noise spectral rations, local shear wave velocity profiles could be derived under the constraint of the thickness of the sedimentary cover which had previously been determined by gravimetric measurements. The resulting 3D model was derived by interpolation between the single shear wave velocity profiles and shows locally good agreement with the few existing velocity profile data, but allows the entire area, as well as deeper parts of the basin, to be represented in greater detail. The wealth of available data allowed further to check if any correlation between the shear wave velocity in the uppermost 30 m (vs30) and the slope of topography, a new technique recently proposed by Wald and Allen (2007), exists on a local scale. While one lithology might provide a greater scatter in the velocity values for the investigated area, almost no correlation between topographic gradient and calculated vs30 exists, whereas a better link is found between vs30 and the local geology. When comparing the vs30 distribution with the MSK intensities for the 1985 Valparaiso event it becomes clear that high intensities are found where the expected vs30 values are low and over a thick sedimentary cover. Although this evidence cannot be generalized for all possible earthquakes, it indicates the influence of site effects modifying the ground motion when earthquakes occur well outside of the Santiago basin. Using the attained knowledge on the basin characteristics, simulations of strong ground motion within the Santiago Metropolitan area were carried out by means of the spectral element technique. The simulation of a regional event, which has also been recorded by a dense network installed in the city of Santiago for recording aftershock activity following the 27 February 2010 Maule earthquake, shows that the model is capable to realistically calculate ground motion in terms of amplitude, duration, and frequency and, moreover, that the surface topography and the shape of the sediment bedrock interface strongly modify ground motion in the Santiago basin. An examination on the dependency of ground motion on the hypocenter location for a hypothetical event occurring along the active San Ramón fault, which is crossing the eastern outskirts of the city, shows that the unfavorable interaction between fault rupture, radiation mechanism, and complex geological conditions in the near-field may give rise to large values of peak ground velocity and therefore considerably increase the level of seismic risk for Santiago de Chile.