@article{BordihnVaszil2021, author = {Bordihn, Henning and Vaszil, Gy{\"o}rgy}, title = {Reversible parallel communicating finite automata systems}, series = {Acta informatica}, volume = {58}, journal = {Acta informatica}, number = {4}, publisher = {Springer}, address = {Berlin ; Heidelberg ; New York, NY}, issn = {0001-5903}, doi = {10.1007/s00236-021-00396-9}, pages = {263 -- 279}, year = {2021}, abstract = {We study the concept of reversibility in connection with parallel communicating systems of finite automata (PCFA in short). We define the notion of reversibility in the case of PCFA (also covering the non-deterministic case) and discuss the relationship of the reversibility of the systems and the reversibility of its components. We show that a system can be reversible with non-reversible components, and the other way around, the reversibility of the components does not necessarily imply the reversibility of the system as a whole. We also investigate the computational power of deterministic centralized reversible PCFA. We show that these very simple types of PCFA (returning or non-returning) can recognize regular languages which cannot be accepted by reversible (deterministic) finite automata, and that they can even accept languages that are not context-free. We also separate the deterministic and non-deterministic variants in the case of systems with non-returning communication. We show that there are languages accepted by non-deterministic centralized PCFA, which cannot be recognized by any deterministic variant of the same type.}, language = {en} } @article{BordihnHolzer2021, author = {Bordihn, Henning and Holzer, Markus}, title = {On the number of active states in finite automata}, series = {Acta informatica}, volume = {58}, journal = {Acta informatica}, number = {4}, publisher = {Springer}, address = {Berlin ; Heidelberg [u.a.]}, issn = {0001-5903}, doi = {10.1007/s00236-021-00397-8}, pages = {301 -- 318}, year = {2021}, abstract = {We introduce a new measure of descriptional complexity on finite automata, called the number of active states. Roughly speaking, the number of active states of an automaton A on input w counts the number of different states visited during the most economic computation of the automaton A for the word w. This concept generalizes to finite automata and regular languages in a straightforward way. We show that the number of active states of both finite automata and regular languages is computable, even with respect to nondeterministic finite automata. We further compare the number of active states to related measures for regular languages. In particular, we show incomparability to the radius of regular languages and that the difference between the number of active states and the total number of states needed in finite automata for a regular language can be of exponential order.}, language = {en} } @article{KreowskyStabernack2021, author = {Kreowsky, Philipp and Stabernack, Christian Benno}, title = {A full-featured FPGA-based pipelined architecture for SIFT extraction}, series = {IEEE access : practical research, open solutions / Institute of Electrical and Electronics Engineers}, volume = {9}, journal = {IEEE access : practical research, open solutions / Institute of Electrical and Electronics Engineers}, publisher = {Inst. of Electr. and Electronics Engineers}, address = {New York, NY}, issn = {2169-3536}, doi = {10.1109/ACCESS.2021.3104387}, pages = {128564 -- 128573}, year = {2021}, abstract = {Image feature detection is a key task in computer vision. Scale Invariant Feature Transform (SIFT) is a prevalent and well known algorithm for robust feature detection. However, it is computationally demanding and software implementations are not applicable for real-time performance. In this paper, a versatile and pipelined hardware implementation is proposed, that is capable of computing keypoints and rotation invariant descriptors on-chip. All computations are performed in single precision floating-point format which makes it possible to implement the original algorithm with little alteration. Various rotation resolutions and filter kernel sizes are supported for images of any resolution up to ultra-high definition. For full high definition images, 84 fps can be processed. Ultra high definition images can be processed at 21 fps.}, language = {en} } @article{BauerHerwigLienhardetal.2021, author = {Bauer, Chris and Herwig, Ralf and Lienhard, Matthias and Prasse, Paul and Scheffer, Tobias and Schuchhardt, Johannes}, title = {Large-scale literature mining to assess the relation between anti-cancer drugs and cancer types}, series = {Journal of translational medicine}, volume = {19}, journal = {Journal of translational medicine}, number = {1}, publisher = {BioMed Central}, address = {London}, issn = {1479-5876}, doi = {10.1186/s12967-021-02941-z}, pages = {13}, year = {2021}, abstract = {Background: There is a huge body of scientific literature describing the relation between tumor types and anti-cancer drugs. The vast amount of scientific literature makes it impossible for researchers and physicians to extract all relevant information manually. Methods: In order to cope with the large amount of literature we applied an automated text mining approach to assess the relations between 30 most frequent cancer types and 270 anti-cancer drugs. We applied two different approaches, a classical text mining based on named entity recognition and an AI-based approach employing word embeddings. The consistency of literature mining results was validated with 3 independent methods: first, using data from FDA approvals, second, using experimentally measured IC-50 cell line data and third, using clinical patient survival data. Results: We demonstrated that the automated text mining was able to successfully assess the relation between cancer types and anti-cancer drugs. All validation methods showed a good correspondence between the results from literature mining and independent confirmatory approaches. The relation between most frequent cancer types and drugs employed for their treatment were visualized in a large heatmap. All results are accessible in an interactive web-based knowledge base using the following link: . Conclusions: Our approach is able to assess the relations between compounds and cancer types in an automated manner. Both, cancer types and compounds could be grouped into different clusters. Researchers can use the interactive knowledge base to inspect the presented results and follow their own research questions, for example the identification of novel indication areas for known drugs.}, language = {en} } @article{HuangRichterKleickmannetal.2021, author = {Huang, Yizhen and Richter, Eric and Kleickmann, Thilo and Wiepke, Axel and Richter, Dirk}, title = {Classroom complexity affects student teachers' behavior in a VR classroom}, series = {Computers \& education : an international journal}, volume = {163}, journal = {Computers \& education : an international journal}, publisher = {Elsevier}, address = {Oxford}, issn = {0360-1315}, doi = {10.1016/j.compedu.2020.104100}, pages = {15}, year = {2021}, abstract = {Student teachers often struggle to keep track of everything that is happening in the classroom, and particularly to notice and respond when students cause disruptions. The complexity of the classroom environment is a potential contributing factor that has not been empirically tested. In this experimental study, we utilized a virtual reality (VR) classroom to examine whether classroom complexity affects the likelihood of student teachers noticing disruptions and how they react after noticing. Classroom complexity was operationalized as the number of disruptions and the existence of overlapping disruptions (multidimensionality) as well as the existence of parallel teaching tasks (simultaneity). Results showed that student teachers (n = 50) were less likely to notice the scripted disruptions, and also less likely to respond to the disruptions in a comprehensive and effortful manner when facing greater complexity. These results may have implications for both teacher training and the design of VR for training or research purpose. This study contributes to the field from two aspects: 1) it revealed how features of the classroom environment can affect student teachers' noticing of and reaction to disruptions; and 2) it extends the functionality of the VR environment-from a teacher training tool to a testbed of fundamental classroom processes that are difficult to manipulate in real-life.}, language = {en} } @article{HawroPrzybylowiczSpindleretal.2021, author = {Hawro, Tomasz and Przybylowicz, Katarzyna and Spindler, Max and Hawro, Marlena and Steć, Michał and Altrichter, Sabine and Weller, Karsten and Magerl, Markus and Reidel, Ulrich and Alarbeed, Ezzat and Alraboni, Ola and Maurer, Marcus and Metz, Martin}, title = {The characteristics and impact of pruritus in adult dermatology patients}, series = {Journal of the American Academy of Dermatology}, volume = {84}, journal = {Journal of the American Academy of Dermatology}, number = {3}, publisher = {Elsevier}, address = {Amsterdam [u.a.]}, issn = {0190-9622}, doi = {10.1016/J.JAAD.2020.08.035}, pages = {691 -- 700}, year = {2021}, abstract = {Background: Pruritus often accompanies chronic skin diseases, exerting considerable burden on many areas of patient functioning; this burden and the features of pruritus remain insufficiently characterized. Objective: To investigate characteristics, including localization patterns, and burden of pruritus in patients with chronic dermatoses. Methods: We recruited 800 patients with active chronic skin diseases. We assessed pruritus intensity, localization, and further characteristics. We used validated questionnaires to assess quality of life, work productivity and activity impairment, anxiety, depression, and sleep quality. Results: Nine out of every 10 patients had experienced pruritus throughout their disease and 73\% in the last 7 days. Pruritus often affected the entire body and was not restricted to skin lesions. Patients with moderate to severe pruritus reported significantly more impairment to their sleep quality and work productivity, and they were more depressed and anxious than control individuals and patients with mild or no pruritus. Suicidal ideations were highly prevalent in patients with chronic pruritus (18.5\%) and atopic dermatitis (11.8\%). Conclusions: Pruritus prevalence and intensity are very high across all dermatoses studied; intensity is linked to impairment in many areas of daily functioning. Effective treatment strategies are urgently required to treat pruritus and the underlying skin disease. ( J Am Acad Dermatol 2021;84:691-700.)}, language = {en} } @article{MiddelanisWillnerOttoetal.2021, author = {Middelanis, Robin and Willner, Sven N. and Otto, Christian and Kuhla, Kilian and Quante, Lennart and Levermann, Anders}, title = {Wave-like global economic ripple response to Hurricane Sandy}, series = {Environmental research letters : ERL / Institute of Physics}, volume = {16}, journal = {Environmental research letters : ERL / Institute of Physics}, number = {12}, publisher = {IOP Publ. Ltd.}, address = {Bristol}, issn = {1748-9326}, doi = {10.1088/1748-9326/ac39c0}, pages = {11}, year = {2021}, abstract = {Tropical cyclones range among the costliest disasters on Earth. Their economic repercussions along the supply and trade network also affect remote economies that are not directly affected. We here simulate possible global repercussions on consumption for the example case of Hurricane Sandy in the US (2012) using the shock-propagation model Acclimate. The modeled shock yields a global three-phase ripple: an initial production demand reduction and associated consumption price decrease, followed by a supply shortage with increasing prices, and finally a recovery phase. Regions with strong trade relations to the US experience strong magnitudes of the ripple. A dominating demand reduction or supply shortage leads to overall consumption gains or losses of a region, respectively. While finding these repercussions in historic data is challenging due to strong volatility of economic interactions, numerical models like ours can help to identify them by approaching the problem from an exploratory angle, isolating the effect of interest. For this, our model simulates the economic interactions of over 7000 regional economic sectors, interlinked through about 1.8 million trade relations. Under global warming, the wave-like structures of the economic response to major hurricanes like the one simulated here are likely to intensify and potentially overlap with other weather extremes.}, language = {en} } @article{QuanteWillnerMiddelanisetal.2021, author = {Quante, Lennart and Willner, Sven N. and Middelanis, Robin and Levermann, Anders}, title = {Regions of intensification of extreme snowfall under future warming}, series = {Scientific reports}, volume = {11}, journal = {Scientific reports}, number = {1}, publisher = {Macmillan Publishers Limited, part of Springer Nature}, address = {Berlin}, issn = {2045-2322}, doi = {10.1038/s41598-021-95979-4}, pages = {9}, year = {2021}, abstract = {Due to climate change the frequency and character of precipitation are changing as the hydrological cycle intensifies. With regards to snowfall, global warming has two opposing influences; increasing humidity enables intense snowfall, whereas higher temperatures decrease the likelihood of snowfall. Here we show an intensification of extreme snowfall across large areas of the Northern Hemisphere under future warming. This is robust across an ensemble of global climate models when they are bias-corrected with observational data. While mean daily snowfall decreases, both the 99th and the 99.9th percentiles of daily snowfall increase in many regions in the next decades, especially for Northern America and Asia. Additionally, the average intensity of snowfall events exceeding these percentiles as experienced historically increases in many regions. This is likely to pose a challenge to municipalities in mid to high latitudes. Overall, extreme snowfall events are likely to become an increasingly important impact of climate change in the next decades, even if they will become rarer, but not necessarily less intense, in the second half of the century.}, language = {en} } @article{SchirrmannLandwehrGiebeletal.2021, author = {Schirrmann, Michael and Landwehr, Niels and Giebel, Antje and Garz, Andreas and Dammer, Karl-Heinz}, title = {Early detection of stripe rust in winter wheat using deep residual neural networks}, series = {Frontiers in plant science : FPLS}, volume = {12}, journal = {Frontiers in plant science : FPLS}, publisher = {Frontiers Media}, address = {Lausanne}, issn = {1664-462X}, doi = {10.3389/fpls.2021.469689}, pages = {14}, year = {2021}, abstract = {Stripe rust (Pst) is a major disease of wheat crops leading untreated to severe yield losses. The use of fungicides is often essential to control Pst when sudden outbreaks are imminent. Sensors capable of detecting Pst in wheat crops could optimize the use of fungicides and improve disease monitoring in high-throughput field phenotyping. Now, deep learning provides new tools for image recognition and may pave the way for new camera based sensors that can identify symptoms in early stages of a disease outbreak within the field. The aim of this study was to teach an image classifier to detect Pst symptoms in winter wheat canopies based on a deep residual neural network (ResNet). For this purpose, a large annotation database was created from images taken by a standard RGB camera that was mounted on a platform at a height of 2 m. Images were acquired while the platform was moved over a randomized field experiment with Pst-inoculated and Pst-free plots of winter wheat. The image classifier was trained with 224 x 224 px patches tiled from the original, unprocessed camera images. The image classifier was tested on different stages of the disease outbreak. At patch level the image classifier reached a total accuracy of 90\%. To test the image classifier on image level, the image classifier was evaluated with a sliding window using a large striding length of 224 px allowing for fast test performance. At image level, the image classifier reached a total accuracy of 77\%. Even in a stage with very low disease spreading (0.5\%) at the very beginning of the Pst outbreak, a detection accuracy of 57\% was obtained. Still in the initial phase of the Pst outbreak with 2 to 4\% of Pst disease spreading, detection accuracy with 76\% could be attained. With further optimizations, the image classifier could be implemented in embedded systems and deployed on drones, vehicles or scanning systems for fast mapping of Pst outbreaks.}, 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{CamargoSchirrmannLandwehretal.2021, author = {Camargo, Tibor de and Schirrmann, Michael and Landwehr, Niels and Dammer, Karl-Heinz and Pflanz, Michael}, title = {Optimized deep learning model as a basis for fast UAV mapping of weed species in winter wheat crops}, series = {Remote sensing / Molecular Diversity Preservation International (MDPI)}, volume = {13}, journal = {Remote sensing / Molecular Diversity Preservation International (MDPI)}, number = {9}, publisher = {MDPI}, address = {Basel}, issn = {2072-4292}, doi = {10.3390/rs13091704}, pages = {19}, year = {2021}, abstract = {Weed maps should be available quickly, reliably, and with high detail to be useful for site-specific management in crop protection and to promote more sustainable agriculture by reducing pesticide use. Here, the optimization of a deep residual convolutional neural network (ResNet-18) for the classification of weed and crop plants in UAV imagery is proposed. The target was to reach sufficient performance on an embedded system by maintaining the same features of the ResNet-18 model as a basis for fast UAV mapping. This would enable online recognition and subsequent mapping of weeds during UAV flying operation. Optimization was achieved mainly by avoiding redundant computations that arise when a classification model is applied on overlapping tiles in a larger input image. The model was trained and tested with imagery obtained from a UAV flight campaign at low altitude over a winter wheat field, and classification was performed on species level with the weed species Matricaria chamomilla L., Papaver rhoeas L., Veronica hederifolia L., and Viola arvensis ssp. arvensis observed in that field. The ResNet-18 model with the optimized image-level prediction pipeline reached a performance of 2.2 frames per second with an NVIDIA Jetson AGX Xavier on the full resolution UAV image, which would amount to about 1.78 ha h(-1) area output for continuous field mapping. The overall accuracy for determining crop, soil, and weed species was 94\%. There were some limitations in the detection of species unknown to the model. When shifting from 16-bit to 32-bit model precision, no improvement in classification accuracy was observed, but a strong decline in speed performance, especially when a higher number of filters was used in the ResNet-18 model. Future work should be directed towards the integration of the mapping process on UAV platforms, guiding UAVs autonomously for mapping purpose, and ensuring the transferability of the models to other crop fields.}, language = {en} } @article{TavakoliAlirezazadehHedayatipouretal.2021, author = {Tavakoli, Hamad and Alirezazadeh, Pendar and Hedayatipour, Ava and Nasib, A. H. Banijamali and Landwehr, Niels}, title = {Leaf image-based classification of some common bean cultivars using discriminative convolutional neural networks}, series = {Computers and electronics in agriculture : COMPAG online ; an international journal}, volume = {181}, journal = {Computers and electronics in agriculture : COMPAG online ; an international journal}, publisher = {Elsevier}, address = {Amsterdam [u.a.]}, issn = {0168-1699}, doi = {10.1016/j.compag.2020.105935}, pages = {11}, year = {2021}, abstract = {In recent years, many efforts have been made to apply image processing techniques for plant leaf identification. However, categorizing leaf images at the cultivar/variety level, because of the very low inter-class variability, is still a challenging task. In this research, we propose an automatic discriminative method based on convolutional neural networks (CNNs) for classifying 12 different cultivars of common beans that belong to three various species. We show that employing advanced loss functions, such as Additive Angular Margin Loss and Large Margin Cosine Loss, instead of the standard softmax loss function for the classification can yield better discrimination between classes and thereby mitigate the problem of low inter-class variability. The method was evaluated by classifying species (level I), cultivars from the same species (level II), and cultivars from different species (level III), based on images from the leaf foreside and backside. The results indicate that the performance of the classification algorithm on the leaf backside image dataset is superior. The maximum mean classification accuracies of 95.86, 91.37 and 86.87\% were obtained at the levels I, II and III, respectively. The proposed method outperforms the previous relevant works and provides a reliable approach for plant cultivars identification.}, language = {en} } @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{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} } @article{SchrapeAndjelkovicBreitenreiteretal.2021, author = {Schrape, Oliver and Andjelkovic, Marko and Breitenreiter, Anselm and Zeidler, Steffen and Balashov, Alexey and Krstić, Miloš}, title = {Design and evaluation of radiation-hardened standard cell flip-flops}, series = {IEEE transactions on circuits and systems : a publication of the IEEE Circuits and Systems Society: 1, Regular papers}, volume = {68}, journal = {IEEE transactions on circuits and systems : a publication of the IEEE Circuits and Systems Society: 1, Regular papers}, number = {11}, publisher = {Inst. of Electr. and Electronics Engineers}, address = {New York, NY}, issn = {1549-8328}, doi = {10.1109/TCSI.2021.3109080}, pages = {4796 -- 4809}, year = {2021}, abstract = {Use of a standard non-rad-hard digital cell library in the rad-hard design can be a cost-effective solution for space applications. In this paper we demonstrate how a standard non-rad-hard flip-flop, as one of the most vulnerable digital cells, can be converted into a rad-hard flip-flop without modifying its internal structure. We present five variants of a Triple Modular Redundancy (TMR) flip-flop: baseline TMR flip-flop, latch-based TMR flip-flop, True-Single Phase Clock (TSPC) TMR flip-flop, scannable TMR flip-flop and self-correcting TMR flipflop. For all variants, the multi-bit upsets have been addressed by applying special placement constraints, while the Single Event Transient (SET) mitigation was achieved through the usage of customized SET filters and selection of optimal inverter sizes for the clock and reset trees. The proposed flip-flop variants feature differing performance, thus enabling to choose the optimal solution for every sensitive node in the circuit, according to the predefined design constraints. Several flip-flop designs have been validated on IHP's 130nm BiCMOS process, by irradiation of custom-designed shift registers. It has been shown that the proposed TMR flip-flops are robust to soft errors with a threshold Linear Energy Transfer (LET) from (32.4 MeV.cm(2)/mg) to (62.5 MeV.cm(2)/mg), depending on the variant.}, language = {en} }