@article{MolkenthinDonnerReichetal.2022,
  author    = {Molkenthin, Christian and Donner, Christian and Reich, Sebastian and Z{\"o}ller, Gert and Hainzl, Sebastian and Holschneider, Matthias and Opper, Manfred},
  title     = {GP-ETAS: semiparametric Bayesian inference for the spatio-temporal epidemic type aftershock sequence model},
  series = {Statistics and Computing},
  volume    = {32},
  journal   = {Statistics and Computing},
  number    = {2},
  publisher = {Springer},
  address   = {Dordrecht},
  issn      = {0960-3174},
  doi       = {10.1007/s11222-022-10085-3},
  pages     = {25},
  year      = {2022},
  abstract  = {The spatio-temporal epidemic type aftershock sequence (ETAS) model is widely used to describe the self-exciting nature of earthquake occurrences. While traditional inference methods provide only point estimates of the model parameters, we aim at a fully Bayesian treatment of model inference, allowing naturally to incorporate prior knowledge and uncertainty quantification of the resulting estimates. Therefore, we introduce a highly flexible, non-parametric representation for the spatially varying ETAS background intensity through a Gaussian process (GP) prior. Combined with classical triggering functions this results in a new model formulation, namely the GP-ETAS model. We enable tractable and efficient Gibbs sampling by deriving an augmented form of the GP-ETAS inference problem. This novel sampling approach allows us to assess the posterior model variables conditioned on observed earthquake catalogues, i.e., the spatial background intensity and the parameters of the triggering function. Empirical results on two synthetic data sets indicate that GP-ETAS outperforms standard models and thus demonstrate the predictive power for observed earthquake catalogues including uncertainty quantification for the estimated parameters. Finally, a case study for the l'Aquila region, Italy, with the devastating event on 6 April 2009, is presented.},
  language  = {en}
}
@article{BandyopadhyaySarkarMandaletal.2022,
  author    = {Bandyopadhyay, Soumyadip and Sarkar, Dipankar and Mandal, Chittaranjan and Giese, Holger},
  title     = {Translation validation of coloured Petri net models of programs on integers},
  series = {Acta informatica},
  volume    = {59},
  journal   = {Acta informatica},
  number    = {6},
  publisher = {Springer},
  address   = {New York},
  issn      = {0001-5903},
  doi       = {10.1007/s00236-022-00419-z},
  pages     = {725 -- 759},
  year      = {2022},
  abstract  = {Programs are often subjected to significant optimizing and parallelizing transformations based on extensive dependence analysis. Formal validation of such transformations needs modelling paradigms which can capture both control and data dependences in the program vividly. Being value-based with an inherent scope of capturing parallelism, the untimed coloured Petri net (CPN) models, reported in the literature, fit the bill well; accordingly, they are likely to be more convenient as the intermediate representations (IRs) of both the source and the transformed codes for translation validation than strictly sequential variable-based IRs like sequential control flow graphs (CFGs). In this work, an efficient path-based equivalence checking method for CPN models of programs on integers is presented. Extensive experimentation has been carried out on several sequential and parallel examples. Complexity and correctness issues have been treated rigorously for the method.},
  language  = {en}
}
@article{AndjelkovićChenSimevskietal.2021,
  author    = {Andjelković, Marko and Chen, Junchao and Simevski, Aleksandar and Schrape, Oliver and Krstić, Miloš and Kraemer, Rolf},
  title     = {Monitoring of particle count rate and LET variations with pulse stretching inverters},
  series = {IEEE transactions on nuclear science : a publication of the IEEE Nuclear and Plasma Sciences Society},
  volume    = {68},
  journal   = {IEEE transactions on nuclear science : a publication of the IEEE Nuclear and Plasma Sciences Society},
  number    = {8},
  publisher = {Institute of Electrical and Electronics Engineers},
  address   = {New York, NY},
  issn      = {0018-9499},
  doi       = {10.1109/TNS.2021.3076400},
  pages     = {1772 -- 1781},
  year      = {2021},
  abstract  = {This study investigates the use of pulse stretching (skew-sized) inverters for monitoring the variation of count rate and linear energy transfer (LET) of energetic particles. The basic particle detector is a cascade of two pulse stretching inverters, and the required sensing area is obtained by connecting up to 12 two-inverter cells in parallel and employing the required number of parallel arrays. The incident particles are detected as single-event transients (SETs), whereby the SET count rate denotes the particle count rate, while the SET pulsewidth distribution depicts the LET variations. The advantage of the proposed solution is the possibility to sense the LET variations using fully digital processing logic. SPICE simulations conducted on IHP's 130-nm CMOS technology have shown that the SET pulsewidth varies by approximately 550 ps over the LET range from 1 to 100 MeV center dot cm(2) center dot mg(-1). The proposed detector is intended for triggering the fault-tolerant mechanisms within a self-adaptive multiprocessing system employed in space. It can be implemented as a standalone detector or integrated in the same chip with the target system.},
  language  = {en}
}
@misc{Ziemann2024,
  type      = {Master Thesis},
  author    = {Ziemann, Felix},
  title     = {Entwicklung und Evaluation einer prototypischen Lernumgebung f{\"u}r das systematische Debugging logischer Fehler in Quellcode},
  doi       = {10.25932/publishup-63273},
  url       = {http://nbn-resolving.de/urn:nbn:de:kobv:517-opus4-632734},
  school      = {Universit{\"a}t Potsdam},
  pages     = {x, 98},
  year      = {2024},
  abstract  = {Wo programmiert wird, da passieren Fehler. Um das Debugging, also die Suche sowie die Behebung von Fehlern in Quellcode, st{\"a}rker explizit zu adressieren, verfolgt die vorliegende Arbeit das Ziel, entlang einer prototypischen Lernumgebung sowohl ein systematisches Vorgehen w{\"a}hrend des Debuggings zu vermitteln als auch Gestaltungsfolgerungen f{\"u}r ebensolche Lernumgebungen zu identifizieren. Dazu wird die folgende Forschungsfrage gestellt: Wie verhalten sich die Lernenden w{\"a}hrend des kurzzeitigen Gebrauchs einer Lernumgebung nach dem Cognitive Apprenticeship-Ansatz mit dem Ziel der expliziten Vermittlung eines systematischen Debuggingvorgehens und welche Eindr{\"u}cke entstehen w{\"a}hrend der Bearbeitung? Zur Beantwortung dieser Forschungsfrage wurde orientierend an literaturbasierten Implikationen f{\"u}r die Vermittlung von Debugging und (medien-)didaktischen Gestaltungsaspekten eine prototypische Lernumgebung entwickelt und im Rahmen einer qualitativen Nutzerstudie mit Bachelorstudierenden informatischer Studieng{\"a}nge erprobt. Hierbei wurden zum einen anwendungsbezogene Verbesserungspotenziale identifiziert. Zum anderen zeigte sich insbesondere gegen{\"u}ber der Systematisierung des Debuggingprozesses innerhalb der Aufgabenbearbeitung eine positive Resonanz. Eine Untersuchung, inwieweit sich die Nutzung der Lernumgebung l{\"a}ngerfristig auf das Verhalten von Personen und ihre Vorgehensweisen w{\"a}hrend des Debuggings auswirkt, k{\"o}nnte Gegenstand kommender Arbeiten sein.},
  language  = {de}
}
@article{ChenLangeAndjelkovicetal.2022,
  author    = {Chen, Junchao and Lange, Thomas and Andjelkovic, Marko and Simevski, Aleksandar and Lu, Li and Krstic, Milos},
  title     = {Solar particle event and single event upset prediction from SRAM-based monitor and supervised machine learning},
  series = {IEEE transactions on emerging topics in computing / IEEE Computer Society, Institute of Electrical and Electronics Engineers},
  volume    = {10},
  journal   = {IEEE transactions on emerging topics in computing / IEEE Computer Society, Institute of Electrical and Electronics Engineers},
  number    = {2},
  publisher = {Institute of Electrical and Electronics Engineers},
  address   = {[New York, NY]},
  issn      = {2168-6750},
  doi       = {10.1109/TETC.2022.3147376},
  pages     = {564 -- 580},
  year      = {2022},
  abstract  = {The intensity of cosmic radiation may differ over five orders of magnitude within a few hours or days during the Solar Particle Events (SPEs), thus increasing for several orders of magnitude the probability of Single Event Upsets (SEUs) in space-borne electronic systems. Therefore, it is vital to enable the early detection of the SEU rate changes in order to ensure timely activation of dynamic radiation hardening measures. In this paper, an embedded approach for the prediction of SPEs and SRAM SEU rate is presented. The proposed solution combines the real-time SRAM-based SEU monitor, the offline-trained machine learning model and online learning algorithm for the prediction. With respect to the state-of-the-art, our solution brings the following benefits: (1) Use of existing on-chip data storage SRAM as a particle detector, thus minimizing the hardware and power overhead, (2) Prediction of SRAM SEU rate one hour in advance, with the fine-grained hourly tracking of SEU variations during SPEs as well as under normal conditions, (3) Online optimization of the prediction model for enhancing the prediction accuracy during run-time, (4) Negligible cost of hardware accelerator design for the implementation of selected machine learning model and online learning algorithm. The proposed design is intended for a highly dependable and self-adaptive multiprocessing system employed in space applications, allowing to trigger the radiation mitigation mechanisms before the onset of high radiation levels.},
  language  = {en}
}
@misc{Schroeter2024,
  type      = {Master Thesis},
  author    = {Schr{\"o}ter, Alexander},
  title     = {Erstellung und Evaluation eines Fragebogens zur Erfassung von komplexen Interaktionssituationen in Software-Entwicklungsprojekten},
  doi       = {10.25932/publishup-63187},
  url       = {http://nbn-resolving.de/urn:nbn:de:kobv:517-opus4-631873},
  school      = {Universit{\"a}t Potsdam},
  pages     = {75},
  year      = {2024},
  abstract  = {Die fortschreitende Digitalisierung durchzieht immer mehr Lebensbereiche und f{\"u}hrt zu immer komplexeren sozio-technischen Systemen. Obwohl diese Systeme zur Lebenserleichterung entwickelt werden, k{\"o}nnen auch unerw{\"u}nschte Nebeneffekte entstehen. Ein solcher Nebeneffekt k{\"o}nnte z.B. die Datennutzung aus Fitness-Apps f{\"u}r nachteilige Versicherungsentscheidungen sein. Diese Nebeneffekte manifestieren sich auf allen Ebenen zwischen Individuum und Gesellschaft. Systeme mit zuvor unerwarteten Nebeneffekten k{\"o}nnen zu sinkender Akzeptanz oder einem Verlust von Vertrauen f{\"u}hren. Da solche Nebeneffekte oft erst im Gebrauch in Erscheinung treten, bedarf es einer besonderen Betrachtung bereits im Konstruktionsprozess. Mit dieser Arbeit soll ein Beitrag geleistet werden, um den Konstruktionsprozess um ein geeignetes Hilfsmittel zur systematischen Reflexion zu erg{\"a}nzen. In vorliegender Arbeit wurde ein Analysetool zur Identifikation und Analyse komplexer Interaktionssituationen in Software-Entwicklungsprojekten entwickelt. Komplexe Interaktionssituationen sind von hoher Dynamik gepr{\"a}gt, aus der eine Unvorhersehbarkeit der Ursache-Wirkungs-Beziehungen folgt. Hierdurch k{\"o}nnen die Akteur*innen die Auswirkungen der eigenen Handlungen nicht mehr {\"u}berblicken, sondern lediglich im Nachhinein rekonstruieren. Hieraus k{\"o}nnen sich fehlerhafte Interaktionsverl{\"a}ufe auf vielf{\"a}ltigen Ebenen ergeben und oben genannte Nebeneffekte entstehen. Das Analysetool unterst{\"u}tzt die Konstrukteur*innen in jeder Phase der Entwicklung durch eine angeleitete Reflexion, um potenziell komplexe Interaktionssituationen zu antizipieren und ihnen durch Analyse der m{\"o}glichen Ursachen der Komplexit{\"a}tswahrnehmung zu begegnen. Ausgehend von der Definition f{\"u}r Interaktionskomplexit{\"a}t wurden Item-Indikatoren zur Erfassung komplexer Interaktionssituationen entwickelt, die dann anhand von geeigneten Kriterien f{\"u}r Komplexit{\"a}t analysiert werden. Das Analysetool ist als „Do-It-Yourself" Fragebogen mit eigenst{\"a}ndiger Auswertung aufgebaut. Die Genese des Fragebogens und die Ergebnisse der durchgef{\"u}hrten Evaluation an f{\"u}nf Softwarentwickler*innen werden dargestellt. Es konnte festgestellt werden, dass das Analysetool bei den Befragten als anwendbar, effektiv und hilfreich wahrgenommen wurde und damit eine hohe Akzeptanz bei der Zielgruppe genießt. Dieser Befund unterst{\"u}tzt die gute Einbindung des Analysetools in den Software-Entwicklungsprozess.},
  language  = {de}
}
@article{BredeBotta2021,
  author    = {Brede, Nuria and Botta, Nicola},
  title     = {On the correctness of monadic backward induction},
  series = {Journal of functional programming},
  volume    = {31},
  journal   = {Journal of functional programming},
  publisher = {Cambridge University Press},
  address   = {Cambridge},
  issn      = {1469-7653},
  doi       = {10.1017/S0956796821000228},
  pages     = {39},
  year      = {2021},
  abstract  = {In control theory, to solve a finite-horizon sequential decision problem (SDP) commonly means to find a list of decision rules that result in an optimal expected total reward (or cost) when taking a given number of decision steps. SDPs are routinely solved using Bellman's backward induction. Textbook authors (e.g. Bertsekas or Puterman) typically give more or less formal proofs to show that the backward induction algorithm is correct as solution method for deterministic and stochastic SDPs. Botta, Jansson and Ionescu propose a generic framework for finite horizon, monadic SDPs together with a monadic version of backward induction for solving such SDPs. In monadic SDPs, the monad captures a generic notion of uncertainty, while a generic measure function aggregates rewards. In the present paper, we define a notion of correctness for monadic SDPs and identify three conditions that allow us to prove a correctness result for monadic backward induction that is comparable to textbook correctness proofs for ordinary backward induction. The conditions that we impose are fairly general and can be cast in category-theoretical terms using the notion of Eilenberg-Moore algebra. They hold in familiar settings like those of deterministic or stochastic SDPs, but we also give examples in which they fail. Our results show that backward induction can safely be employed for a broader class of SDPs than usually treated in textbooks. However, they also rule out certain instances that were considered admissible in the context of Botta et al. 's generic framework. Our development is formalised in Idris as an extension of the Botta et al. framework and the sources are available as supplementary material.},
  language  = {en}
}
@article{MarcoFigueraRiedelRossietal.2022,
  author    = {Marco Figuera, Ramiro and Riedel, Christian and Rossi, Angelo Pio and Unnithan, Vikram},
  title     = {Depth to diameter analysis on small simple craters at the lunar south pole - possible implications for ice harboring},
  series = {Remote sensing},
  volume    = {14},
  journal   = {Remote sensing},
  number    = {3},
  publisher = {MDPI},
  address   = {Basel},
  issn      = {2072-4292},
  doi       = {10.3390/rs14030450},
  pages     = {13},
  year      = {2022},
  abstract  = {In this paper, we present a study comparing the depth to diameter (d/D) ratio of small simple craters (200-1000 m) of an area between -88.5 degrees to -90 degrees latitude at the lunar south pole containing Permanent Shadowed Regions (PSRs) versus craters without PSRs. As PSRs can reach temperatures of 110 K and are capable of harboring volatiles, especially water ice, we analyzed the relationship of depth versus diameter ratios and its possible implications for harboring water ice. Variations in the d/D ratios can also be caused by other processes such as degradation, isostatic adjustment, or differences in surface properties. The conducted d/D ratio analysis suggests that a differentiation between craters containing PSRs versus craters without PSRs occurs. Thus, a possible direct relation between d/D ratio, PSRs, and water ice harboring might exist. Our results suggest that differences in the target's surface properties may explain the obtained results. The resulting d/D ratios of craters with PSRs can help to select target areas for future In-Situ Resource Utilization (ISRU) missions.},
  language  = {en}
}
@article{GautamZhangLandwehretal.2021,
  author    = {Gautam, Khem Raj and Zhang, Guoqiang and Landwehr, Niels and Adolphs, Julian},
  title     = {Machine learning for improvement of thermal conditions inside a hybrid ventilated animal building},
  series = {Computers and electronics in agriculture : COMPAG online ; an international journal},
  volume    = {187},
  journal   = {Computers and electronics in agriculture : COMPAG online ; an international journal},
  publisher = {Elsevier Science},
  address   = {Amsterdam [u.a.]},
  issn      = {0168-1699},
  doi       = {10.1016/j.compag.2021.106259},
  pages     = {10},
  year      = {2021},
  abstract  = {In buildings with hybrid ventilation, natural ventilation opening positions (windows), mechanical ventilation rates, heating, and cooling are manipulated to maintain desired thermal conditions. The indoor temperature is regulated solely by ventilation (natural and mechanical) when the external conditions are favorable to save external heating and cooling energy. The ventilation parameters are determined by a rule-based control scheme, which is not optimal. This study proposes a methodology to enable real-time optimum control of ventilation parameters. We developed offline prediction models to estimate future thermal conditions from the data collected from building in operation. The developed offline model is then used to find the optimal controllable ventilation parameters in real-time to minimize the setpoint deviation in the building. With the proposed methodology, the experimental building's setpoint deviation improved for 87\% of time, on average, by 0.53 degrees C compared to the current deviations.},
  language  = {en}
}
@article{AbdelwahabLandwehr2022,
  author    = {Abdelwahab, Ahmed and Landwehr, Niels},
  title     = {Deep Distributional Sequence Embeddings Based on a Wasserstein Loss},
  series = {Neural processing letters},
  journal   = {Neural processing letters},
  publisher = {Springer},
  address   = {Dordrecht},
  issn      = {1370-4621},
  doi       = {10.1007/s11063-022-10784-y},
  pages     = {21},
  year      = {2022},
  abstract  = {Deep metric learning employs deep neural networks to embed instances into a metric space such that distances between instances of the same class are small and distances between instances from different classes are large. In most existing deep metric learning techniques, the embedding of an instance is given by a feature vector produced by a deep neural network and Euclidean distance or cosine similarity defines distances between these vectors. This paper studies deep distributional embeddings of sequences, where the embedding of a sequence is given by the distribution of learned deep features across the sequence. The motivation for this is to better capture statistical information about the distribution of patterns within the sequence in the embedding. When embeddings are distributions rather than vectors, measuring distances between embeddings involves comparing their respective distributions. The paper therefore proposes a distance metric based on Wasserstein distances between the distributions and a corresponding loss function for metric learning, which leads to a novel end-to-end trainable embedding model. We empirically observe that distributional embeddings outperform standard vector embeddings and that training with the proposed Wasserstein metric outperforms training with other distance functions.},
  language  = {en}
}