TY - JOUR A1 - Schindler, Daniel A1 - Moldenhawer, Ted A1 - Stange, Maike A1 - Lepro, Valentino A1 - Beta, Carsten A1 - Holschneider, Matthias A1 - Huisinga, Wilhelm T1 - Analysis of protrusion dynamics in amoeboid cell motility by means of regularized contour flows JF - PLoS Computational Biology : a new community journal N2 - Amoeboid cell motility is essential for a wide range of biological processes including wound healing, embryonic morphogenesis, and cancer metastasis. It relies on complex dynamical patterns of cell shape changes that pose long-standing challenges to mathematical modeling and raise a need for automated and reproducible approaches to extract quantitative morphological features from image sequences. Here, we introduce a theoretical framework and a computational method for obtaining smooth representations of the spatiotemporal contour dynamics from stacks of segmented microscopy images. Based on a Gaussian process regression we propose a one-parameter family of regularized contour flows that allows us to continuously track reference points (virtual markers) between successive cell contours. We use this approach to define a coordinate system on the moving cell boundary and to represent different local geometric quantities in this frame of reference. In particular, we introduce the local marker dispersion as a measure to identify localized membrane expansions and provide a fully automated way to extract the properties of such expansions, including their area and growth time. The methods are available as an open-source software package called AmoePy, a Python-based toolbox for analyzing amoeboid cell motility (based on time-lapse microscopy data), including a graphical user interface and detailed documentation. Due to the mathematical rigor of our framework, we envision it to be of use for the development of novel cell motility models. We mainly use experimental data of the social amoeba Dictyostelium discoideum to illustrate and validate our approach.
Author summary Amoeboid motion is a crawling-like cell migration that plays an important key role in multiple biological processes such as wound healing and cancer metastasis. This type of cell motility results from expanding and simultaneously contracting parts of the cell membrane. From fluorescence images, we obtain a sequence of points, representing the cell membrane, for each time step. By using regression analysis on these sequences, we derive smooth representations, so-called contours, of the membrane. Since the number of measurements is discrete and often limited, the question is raised of how to link consecutive contours with each other. In this work, we present a novel mathematical framework in which these links are described by regularized flows allowing a certain degree of concentration or stretching of neighboring reference points on the same contour. This stretching rate, the so-called local dispersion, is used to identify expansions and contractions of the cell membrane providing a fully automated way of extracting properties of these cell shape changes. We applied our methods to time-lapse microscopy data of the social amoeba Dictyostelium discoideum. Y1 - 2021 U6 - https://doi.org/10.1371/journal.pcbi.1009268 SN - 1553-734X SN - 1553-7358 VL - 17 IS - 8 PB - PLoS CY - San Fransisco ER - TY - GEN A1 - Panzer, Marcel A1 - Bender, Benedict A1 - Gronau, Norbert T1 - Neural agent-based production planning and control BT - an architectural review T2 - Zweitveröffentlichungen der Universität Potsdam : Wirtschafts- und Sozialwissenschaftliche Reihe N2 - Nowadays, production planning and control must cope with mass customization, increased fluctuations in demand, and high competition pressures. Despite prevailing market risks, planning accuracy and increased adaptability in the event of disruptions or failures must be ensured, while simultaneously optimizing key process indicators. To manage that complex task, neural networks that can process large quantities of high-dimensional data in real time have been widely adopted in recent years. Although these are already extensively deployed in production systems, a systematic review of applications and implemented agent embeddings and architectures has not yet been conducted. The main contribution of this paper is to provide researchers and practitioners with an overview of applications and applied embeddings and to motivate further research in neural agent-based production. Findings indicate that neural agents are not only deployed in diverse applications, but are also increasingly implemented in multi-agent environments or in combination with conventional methods — leveraging performances compared to benchmarks and reducing dependence on human experience. This not only implies a more sophisticated focus on distributed production resources, but also broadening the perspective from a local to a global scale. Nevertheless, future research must further increase scalability and reproducibility to guarantee a simplified transfer of results to reality. T3 - Zweitveröffentlichungen der Universität Potsdam : Wirtschafts- und Sozialwissenschaftliche Reihe - 172 KW - production planning and control KW - machine learning KW - neural networks KW - systematic literature review KW - taxonomy Y1 - 2022 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:kobv:517-opus4-604777 SN - 1867-5808 ER - TY - JOUR A1 - Panzer, Marcel A1 - Bender, Benedict A1 - Gronau, Norbert T1 - Neural agent-based production planning and control BT - an architectural review JF - Journal of Manufacturing Systems N2 - Nowadays, production planning and control must cope with mass customization, increased fluctuations in demand, and high competition pressures. Despite prevailing market risks, planning accuracy and increased adaptability in the event of disruptions or failures must be ensured, while simultaneously optimizing key process indicators. To manage that complex task, neural networks that can process large quantities of high-dimensional data in real time have been widely adopted in recent years. Although these are already extensively deployed in production systems, a systematic review of applications and implemented agent embeddings and architectures has not yet been conducted. The main contribution of this paper is to provide researchers and practitioners with an overview of applications and applied embeddings and to motivate further research in neural agent-based production. Findings indicate that neural agents are not only deployed in diverse applications, but are also increasingly implemented in multi-agent environments or in combination with conventional methods — leveraging performances compared to benchmarks and reducing dependence on human experience. This not only implies a more sophisticated focus on distributed production resources, but also broadening the perspective from a local to a global scale. Nevertheless, future research must further increase scalability and reproducibility to guarantee a simplified transfer of results to reality. KW - production planning and control KW - machine learning KW - neural networks KW - systematic literature review KW - taxonomy Y1 - 2022 U6 - https://doi.org/10.1016/j.jmsy.2022.10.019 SN - 0278-6125 SN - 1878-6642 VL - 65 SP - 743 EP - 766 PB - Elsevier CY - Amsterdam ER - TY - GEN A1 - Monti, Remo A1 - Rautenstrauch, Pia A1 - Ghanbari, Mahsa A1 - Rani James, Alva A1 - Kirchler, Matthias A1 - Ohler, Uwe A1 - Konigorski, Stefan A1 - Lippert, Christoph T1 - Identifying interpretable gene-biomarker associations with functionally informed kernel-based tests in 190,000 exomes T2 - Zweitveröffentlichungen der Universität Potsdam : Reihe der Digital Engineering Fakultät N2 - Here we present an exome-wide rare genetic variant association study for 30 blood biomarkers in 191,971 individuals in the UK Biobank. We compare gene- based association tests for separate functional variant categories to increase interpretability and identify 193 significant gene-biomarker associations. Genes associated with biomarkers were ~ 4.5-fold enriched for conferring Mendelian disorders. In addition to performing weighted gene-based variant collapsing tests, we design and apply variant-category-specific kernel-based tests that integrate quantitative functional variant effect predictions for mis- sense variants, splicing and the binding of RNA-binding proteins. For these tests, we present a computationally efficient combination of the likelihood- ratio and score tests that found 36% more associations than the score test alone while also controlling the type-1 error. Kernel-based tests identified 13% more associations than their gene-based collapsing counterparts and had advantages in the presence of gain of function missense variants. We introduce local collapsing by amino acid position for missense variants and use it to interpret associations and identify potential novel gain of function variants in PIEZO1. Our results show the benefits of investigating different functional mechanisms when performing rare-variant association tests, and demonstrate pervasive rare-variant contribution to biomarker variability. T3 - Zweitveröffentlichungen der Universität Potsdam : Reihe der Digital Engineering Fakultät - 16 Y1 - 2022 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:kobv:517-opus4-586078 IS - 16 ER - TY - JOUR A1 - Monti, Remo A1 - Rautenstrauch, Pia A1 - Ghanbari, Mahsa A1 - Rani James, Alva A1 - Kirchler, Matthias A1 - Ohler, Uwe A1 - Konigorski, Stefan A1 - Lippert, Christoph T1 - Identifying interpretable gene-biomarker associations with functionally informed kernel-based tests in 190,000 exomes JF - Nature Communications N2 - Here we present an exome-wide rare genetic variant association study for 30 blood biomarkers in 191,971 individuals in the UK Biobank. We compare gene- based association tests for separate functional variant categories to increase interpretability and identify 193 significant gene-biomarker associations. Genes associated with biomarkers were ~ 4.5-fold enriched for conferring Mendelian disorders. In addition to performing weighted gene-based variant collapsing tests, we design and apply variant-category-specific kernel-based tests that integrate quantitative functional variant effect predictions for mis- sense variants, splicing and the binding of RNA-binding proteins. For these tests, we present a computationally efficient combination of the likelihood- ratio and score tests that found 36% more associations than the score test alone while also controlling the type-1 error. Kernel-based tests identified 13% more associations than their gene-based collapsing counterparts and had advantages in the presence of gain of function missense variants. We introduce local collapsing by amino acid position for missense variants and use it to interpret associations and identify potential novel gain of function variants in PIEZO1. Our results show the benefits of investigating different functional mechanisms when performing rare-variant association tests, and demonstrate pervasive rare-variant contribution to biomarker variability. Y1 - 2022 U6 - https://doi.org/10.1038/s41467-022-32864-2 SN - 2041-1723 VL - 13 PB - Nature Publishing Group UK CY - London ER - TY - JOUR A1 - Tavakoli, Hamad A1 - Alirezazadeh, Pendar A1 - Hedayatipour, Ava A1 - Nasib, A. H. Banijamali A1 - Landwehr, Niels T1 - Leaf image-based classification of some common bean cultivars using discriminative convolutional neural networks JF - Computers and electronics in agriculture : COMPAG online ; an international journal N2 - 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. KW - Bean KW - Plant identification KW - Digital image analysis KW - VGG16 KW - Loss KW - functions Y1 - 2021 U6 - https://doi.org/10.1016/j.compag.2020.105935 SN - 0168-1699 SN - 1872-7107 VL - 181 PB - Elsevier CY - Amsterdam [u.a.] ER - TY - THES A1 - Morozov, Alexei T1 - Optimierung von Fehlererkennungsschaltungen auf der Grundlage von komplementären Ergänzungen für 1-aus-3 und Berger Codes T1 - Optimisation of Error-Detection Circuits by Complementary Circuits for 1-out-of-3 and Berger Codes N2 - Die Dissertation stellt eine neue Herangehensweise an die Lösung der Aufgabe der funktionalen Diagnostik digitaler Systeme vor. In dieser Arbeit wird eine neue Methode für die Fehlererkennung vorgeschlagen, basierend auf der Logischen Ergänzung und der Verwendung von Berger-Codes und dem 1-aus-3 Code. Die neue Fehlererkennungsmethode der Logischen Ergänzung gestattet einen hohen Optimierungsgrad der benötigten Realisationsfläche der konstruierten Fehlererkennungsschaltungen. Außerdem ist eins der wichtigen in dieser Dissertation gelösten Probleme die Synthese vollständig selbstprüfender Schaltungen. N2 - In this dissertation concurrent checking by use of a complementary circuit for an 1-out-of-n Codes and Berger-Code is investigated. For an arbitrarily given combinational circuit necessary and sufficient conditions for the existence of a totally self-checking checker are derived for the first time. KW - logische Ergänzung KW - neue Online-Fehlererkennungsmethode KW - selbstprüfende Schaltungen KW - Complementary Circuits KW - New On-Line Error-Detection Methode KW - Error-Detection Circuits KW - Self-Checking Circuits Y1 - 2005 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:kobv:517-opus-5360 ER - TY - JOUR A1 - Pfitzner, Bjarne A1 - Steckhan, Nico A1 - Arnrich, Bert T1 - Federated learning in a medical context BT - a systematic literature review JF - ACM transactions on internet technology : TOIT / Association for Computing N2 - Data privacy is a very important issue. Especially in fields like medicine, it is paramount to abide by the existing privacy regulations to preserve patients' anonymity. However, data is required for research and training machine learning models that could help gain insight into complex correlations or personalised treatments that may otherwise stay undiscovered. Those models generally scale with the amount of data available, but the current situation often prohibits building large databases across sites. So it would be beneficial to be able to combine similar or related data from different sites all over the world while still preserving data privacy. Federated learning has been proposed as a solution for this, because it relies on the sharing of machine learning models, instead of the raw data itself. That means private data never leaves the site or device it was collected on. Federated learning is an emerging research area, and many domains have been identified for the application of those methods. This systematic literature review provides an extensive look at the concept of and research into federated learning and its applicability for confidential healthcare datasets. KW - Federated learning Y1 - 2021 U6 - https://doi.org/10.1145/3412357 SN - 1533-5399 SN - 1557-6051 VL - 21 IS - 2 SP - 1 EP - 31 PB - Association for Computing Machinery CY - New York ER - TY - JOUR A1 - Garrels, Tim A1 - Khodabakhsh, Athar A1 - Renard, Bernhard Y. A1 - Baum, Katharina T1 - LazyFox: fast and parallelized overlapping community detection in large graphs JF - PEERJ Computer Science N2 - The detection of communities in graph datasets provides insight about a graph's underlying structure and is an important tool for various domains such as social sciences, marketing, traffic forecast, and drug discovery. While most existing algorithms provide fast approaches for community detection, their results usually contain strictly separated communities. However, most datasets would semantically allow for or even require overlapping communities that can only be determined at much higher computational cost. We build on an efficient algorithm, FOX, that detects such overlapping communities. FOX measures the closeness of a node to a community by approximating the count of triangles which that node forms with that community. We propose LAZYFOX, a multi-threaded adaptation of the FOX algorithm, which provides even faster detection without an impact on community quality. This allows for the analyses of significantly larger and more complex datasets. LAZYFOX enables overlapping community detection on complex graph datasets with millions of nodes and billions of edges in days instead of weeks. As part of this work, LAZYFOX's implementation was published and is available as a tool under an MIT licence at https://github.com/TimGarrels/LazyFox. KW - Overlapping community detection KW - Large networks KW - Weighted clustering coefficient KW - Heuristic triangle estimation KW - Parallelized algorithm KW - C++ tool KW - Runtime improvement KW - Open source KW - Graph algorithm KW - Community analysis Y1 - 2023 U6 - https://doi.org/10.7717/peerj-cs.1291 SN - 2376-5992 VL - 9 PB - PeerJ Inc. CY - London ER - TY - JOUR A1 - Bonnet, Philippe A1 - Dong, Xin Luna A1 - Naumann, Felix A1 - Tözün, Pınar T1 - VLDB 2021 BT - Designing a hybrid conference JF - SIGMOD record N2 - The 47th International Conference on Very Large Databases (VLDB'21) was held on August 16-20, 2021 as a hybrid conference. It attracted 180 in-person attendees in Copenhagen and 840 remote attendees. In this paper, we describe our key decisions as general chairs and program committee chairs and share the lessons we learned. Y1 - 2021 U6 - https://doi.org/10.1145/3516431.3516447 SN - 0163-5808 SN - 1943-5835 VL - 50 IS - 4 SP - 50 EP - 53 PB - Association for Computing Machinery CY - New York ER - TY - CHAP A1 - Hagemann, Linus A1 - Abramova, Olga T1 - Crafting audience engagement in social media conversations BT - evidence from the U.S. 2020 presidential elections T2 - Proceedings of the 55th Hawaii International Conference on System Sciences N2 - Observing inconsistent results in prior studies, this paper applies the elaboration likelihood model to investigate the impact of affective and cognitive cues embedded in social media messages on audience engagement during a political event. Leveraging a rich dataset in the context of the 2020 U.S. presidential elections containing more than 3 million tweets, we found the prominence of both cue types. For the overall sample, positivity and sentiment are negatively related to engagement. In contrast, the post-hoc sub-sample analysis of tweets from famous users shows that emotionally charged content is more engaging. The role of sentiment decreases when the number of followers grows and ultimately becomes insignificant for Twitter participants with a vast number of followers. Prosocial orientation (“we-talk”) is consistently associated with more likes, comments, and retweets in the overall sample and sub-samples. KW - mediated conversation KW - big data KW - engagement KW - sentiment analysis KW - social media Y1 - 2022 SN - 978-0-9981331-5-7 SP - 3222 EP - 3231 PB - HICSS Conference Office University of Hawaii at Manoa CY - Honolulu ER - TY - CHAP A1 - Abramova, Olga T1 - Does a smile open all doors? BT - understanding the impact of appearance disclosure on accommodation sharing platforms T2 - Proceedings of the 53rd Hawaii International Conference on System Sciences N2 - Online photographs govern an individual’s choices across a variety of contexts. In sharing arrangements, facial appearance has been shown to affect the desire to collaborate, interest to explore a listing, and even willingness to pay for a stay. Because of the ubiquity of online images and their influence on social attitudes, it seems crucial to be able to control these aspects. The present study examines the effect of different photographic self-disclosures on the provider’s perceptions and willingness to accept a potential co-sharer. The findings from our experiment in the accommodation-sharing context suggest social attraction mediates the effect of photographic self-disclosures on willingness to host. Implications of the results for IS research and practitioners are discussed. KW - The Sharing Economy KW - airbnb KW - online photographs KW - self-disclosure KW - sharing economy KW - social attraction Y1 - 2020 SN - 978-0-9981331-3-3 SP - 831 EP - 840 PB - HICSS Conference Office University of Hawaii at Manoa CY - Honolulu ER - TY - GEN A1 - Hägele, Claudia A1 - Schlagenhauf, Florian A1 - Rapp, Michael A. A1 - Sterzer, Philipp A1 - Beck, Anne A1 - Bermpohl, Felix A1 - Stoy, Meline A1 - Ströhle, Andreas A1 - Wittchen, Hans-Ulrich A1 - Dolan, Raymond J. A1 - Heinz, Andreas T1 - Dimensional psychiatry BT - reward dysfunction and depressive mood across psychiatric disorders T2 - Postprints der Universität Potsdam : Humanwissenschaftliche Reihe N2 - A dimensional approach in psychiatry aims to identify core mechanisms of mental disorders across nosological boundaries. We compared anticipation of reward between major psychiatric disorders, and investigated whether reward anticipation is impaired in several mental disorders and whether there is a common psychopathological correlate (negative mood) of such an impairment. We used functional magnetic resonance imaging (fMRI) and a monetary incentive delay (MID) task to study the functional correlates of reward anticipation across major psychiatric disorders in 184 subjects, with the diagnoses of alcohol dependence (n = 26), schizophrenia (n = 44), major depressive disorder (MDD, n = 24), bipolar disorder (acute manic episode, n = 13), attention deficit/hyperactivity disorder (ADHD, n = 23), and healthy controls (n = 54). Subjects' individual Beck Depression Inventory-and State-Trait Anxiety Inventory-scores were correlated with clusters showing significant activation during reward anticipation. During reward anticipation, we observed significant group differences in ventral striatal (VS) activation: patients with schizophrenia, alcohol dependence, and major depression showed significantly less ventral striatal activation compared to healthy controls. Depressive symptoms correlated with dysfunction in reward anticipation regardless of diagnostic entity. There was no significant correlation between anxiety symptoms and VS functional activation. Our findings demonstrate a neurobiological dysfunction related to reward prediction that transcended disorder categories and was related to measures of depressed mood. The findings underline the potential of a dimensional approach in psychiatry and strengthen the hypothesis that neurobiological research in psychiatric disorders can be targeted at core mechanisms that are likely to be implicated in a range of clinical entities. T3 - Zweitveröffentlichungen der Universität Potsdam : Humanwissenschaftliche Reihe - 653 KW - dimensional KW - fMRI KW - reward system KW - ventral striatum KW - monetary incentive delay task KW - depressive symptoms Y1 - 2020 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:kobv:517-opus4-431064 SN - 1866-8364 IS - 653 SP - 331 EP - 341 ER - TY - THES A1 - Jiang, Lan T1 - Discovering metadata in data files N2 - It is estimated that data scientists spend up to 80% of the time exploring, cleaning, and transforming their data. A major reason for that expenditure is the lack of knowledge about the used data, which are often from different sources and have heterogeneous structures. As a means to describe various properties of data, metadata can help data scientists understand and prepare their data, saving time for innovative and valuable data analytics. However, metadata do not always exist: some data file formats are not capable of storing them; metadata were deleted for privacy concerns; legacy data may have been produced by systems that were not designed to store and handle meta- data. As data are being produced at an unprecedentedly fast pace and stored in diverse formats, manually creating metadata is not only impractical but also error-prone, demanding automatic approaches for metadata detection. In this thesis, we are focused on detecting metadata in CSV files – a type of plain-text file that, similar to spreadsheets, may contain different types of content at arbitrary positions. We propose a taxonomy of metadata in CSV files and specifically address the discovery of three different metadata: line and cell type, aggregations, and primary keys and foreign keys. Data are organized in an ad-hoc manner in CSV files, and do not follow a fixed structure, which is assumed by common data processing tools. Detecting the structure of such files is a prerequisite of extracting information from them, which can be addressed by detecting the semantic type, such as header, data, derived, or footnote, of each line or each cell. We propose the supervised- learning approach Strudel to detect the type of lines and cells. CSV files may also include aggregations. An aggregation represents the arithmetic relationship between a numeric cell and a set of other numeric cells. Our proposed AggreCol algorithm is capable of detecting aggregations of five arithmetic functions in CSV files. Note that stylistic features, such as font style and cell background color, do not exist in CSV files. Our proposed algorithms address the respective problems by using only content, contextual, and computational features. Storing a relational table is also a common usage of CSV files. Primary keys and foreign keys are important metadata for relational databases, which are usually not present for database instances dumped as plain-text files. We propose the HoPF algorithm to holistically detect both constraints in relational databases. Our approach is capable of distinguishing true primary and foreign keys from a great amount of spurious unique column combinations and inclusion dependencies, which can be detected by state-of-the-art data profiling algorithms. N2 - Schätzungen zufolge verbringen Datenwissenschaftler bis zu 80% ihrer Zeit mit der Erkundung, Bereinigung und Umwandlung ihrer Daten. Ein Hauptgrund für diesen Aufwand ist das fehlende Wissen über die verwendeten Daten, die oft aus unterschiedlichen Quellen stammen und heterogene Strukturen aufweisen. Als Mittel zur Beschreibung verschiedener Dateneigenschaften können Metadaten Datenwissenschaftlern dabei helfen, ihre Daten zu verstehen und aufzubereiten, und so wertvolle Zeit die Datenanalysen selbst sparen. Metadaten sind jedoch nicht immer vorhanden: Zum Beispiel sind einige Dateiformate nicht in der Lage, sie zu speichern; Metadaten können aus Datenschutzgründen gelöscht worden sein; oder ältere Daten wurden möglicherweise von Systemen erzeugt, die nicht für die Speicherung und Verarbeitung von Metadaten konzipiert waren. Da Daten in einem noch nie dagewesenen Tempo produziert und in verschiedenen Formaten gespeichert werden, ist die manuelle Erstellung von Metadaten nicht nur unpraktisch, sondern auch fehleranfällig, so dass automatische Ansätze zur Metadatenerkennung erforderlich sind. In dieser Arbeit konzentrieren wir uns auf die Erkennung von Metadaten in CSV-Dateien - einer Art von Klartextdateien, die, ähnlich wie Tabellenkalkulationen, verschiedene Arten von Inhalten an beliebigen Positionen enthalten können. Wir schlagen eine Taxonomie der Metadaten in CSV-Dateien vor und befassen uns speziell mit der Erkennung von drei verschiedenen Metadaten: Zeile und Zellensemantischer Typ, Aggregationen sowie Primärschlüssel und Fremdschlüssel. Die Daten sind in CSV-Dateien ad-hoc organisiert und folgen keiner festen Struktur, wie sie von gängigen Datenverarbeitungsprogrammen angenommen wird. Die Erkennung der Struktur solcher Dateien ist eine Voraussetzung für die Extraktion von Informationen aus ihnen, die durch die Erkennung des semantischen Typs jeder Zeile oder jeder Zelle, wie z. B. Kopfzeile, Daten, abgeleitete Daten oder Fußnote, angegangen werden kann. Wir schlagen den Ansatz des überwachten Lernens, genannt „Strudel“ vor, um den strukturellen Typ von Zeilen und Zellen zu klassifizieren. CSV-Dateien können auch Aggregationen enthalten. Eine Aggregation stellt die arithmetische Beziehung zwischen einer numerischen Zelle und einer Reihe anderer numerischer Zellen dar. Der von uns vorgeschlagene „Aggrecol“-Algorithmus ist in der Lage, Aggregationen von fünf arithmetischen Funktionen in CSV-Dateien zu erkennen. Da stilistische Merkmale wie Schriftart und Zellhintergrundfarbe in CSV-Dateien nicht vorhanden sind, die von uns vorgeschlagenen Algorithmen die entsprechenden Probleme, indem sie nur die Merkmale Inhalt, Kontext und Berechnungen verwenden. Die Speicherung einer relationalen Tabelle ist ebenfalls eine häufige Verwendung von CSV-Dateien. Primär- und Fremdschlüssel sind wichtige Metadaten für relationale Datenbanken, die bei Datenbankinstanzen, die als reine Textdateien gespeichert werden, normalerweise nicht vorhanden sind. Wir schlagen den „HoPF“-Algorithmus vor, um beide Constraints in relationalen Datenbanken ganzheitlich zu erkennen. Unser Ansatz ist in der Lage, echte Primär- und Fremdschlüssel von einer großen Menge an falschen eindeutigen Spaltenkombinationen und Einschlussabhängigkeiten zu unterscheiden, die von modernen Data-Profiling-Algorithmen erkannt werden können. KW - data preparation KW - metadata detection KW - data wrangling KW - Datenaufbereitung KW - Datentransformation KW - Erkennung von Metadaten Y1 - 2022 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:kobv:517-opus4-566204 ER - TY - JOUR A1 - Rosin, Paul L. A1 - Lai, Yu-Kun A1 - Mould, David A1 - Yi, Ran A1 - Berger, Itamar A1 - Doyle, Lars A1 - Lee, Seungyong A1 - Li, Chuan A1 - Liu, Yong-Jin A1 - Semmo, Amir A1 - Shamir, Ariel A1 - Son, Minjung A1 - Winnemöller, Holger T1 - NPRportrait 1.0: A three-level benchmark for non-photorealistic rendering of portraits JF - Computational visual media N2 - Recently, there has been an upsurge of activity in image-based non-photorealistic rendering (NPR), and in particular portrait image stylisation, due to the advent of neural style transfer (NST). However, the state of performance evaluation in this field is poor, especially compared to the norms in the computer vision and machine learning communities. Unfortunately, the task of evaluating image stylisation is thus far not well defined, since it involves subjective, perceptual, and aesthetic aspects. To make progress towards a solution, this paper proposes a new structured, three-level, benchmark dataset for the evaluation of stylised portrait images. Rigorous criteria were used for its construction, and its consistency was validated by user studies. Moreover, a new methodology has been developed for evaluating portrait stylisation algorithms, which makes use of the different benchmark levels as well as annotations provided by user studies regarding the characteristics of the faces. We perform evaluation for a wide variety of image stylisation methods (both portrait-specific and general purpose, and also both traditional NPR approaches and NST) using the new benchmark dataset. KW - non-photorealistic rendering (NPR) KW - image stylization KW - style transfer KW - portrait KW - evaluation KW - benchmark Y1 - 2022 U6 - https://doi.org/10.1007/s41095-021-0255-3 SN - 2096-0433 SN - 2096-0662 VL - 8 IS - 3 SP - 445 EP - 465 PB - Springer Nature CY - London ER - TY - CHAP A1 - Rojahn, Marcel A1 - Gronau, Norbert ED - Bui, Tung X. T1 - Openness indicators for the evaluation of digital platforms between the launch and maturity phase T2 - Proceedings of the 57th Annual Hawaii International Conference on System Sciences N2 - In recent years, the evaluation of digital platforms has become an important focus in the field of information systems science. The identification of influential indicators that drive changes in digital platforms, specifically those related to openness, is still an unresolved issue. This paper addresses the challenge of identifying measurable indicators and characterizing the transition from launch to maturity in digital platforms. It proposes a systematic analytical approach to identify relevant openness indicators for evaluation purposes. The main contributions of this study are the following (1) the development of a comprehensive procedure for analyzing indicators, (2) the categorization of indicators as evaluation metrics within a multidimensional grid-box model, (3) the selection and evaluation of relevant indicators, (4) the identification and assessment of digital platform architectures during the launch-to-maturity transition, and (5) the evaluation of the applicability of the conceptualization and design process for digital platform evaluation. KW - federated industrial platform ecosystems KW - technologies KW - business models KW - data-driven artifacts KW - design-science research KW - digital platform openness KW - evaluation KW - morphological analysis Y1 - 2024 SN - 978-0-99813-317-1 SP - 4516 EP - 4525 PB - Department of IT Management Shidler College of Business University of Hawaii CY - Honolulu, HI ER - TY - GEN A1 - Fandiño, Jorge T1 - Founded (auto)epistemic equilibrium logic satisfies epistemic splitting T2 - Postprints der Universität Potsdam : Mathematisch-Naturwissenschaftliche Reihe N2 - In a recent line of research, two familiar concepts from logic programming semantics (unfounded sets and splitting) were extrapolated to the case of epistemic logic programs. The property of epistemic splitting provides a natural and modular way to understand programs without epistemic cycles but, surprisingly, was only fulfilled by Gelfond's original semantics (G91), among the many proposals in the literature. On the other hand, G91 may suffer from a kind of self-supported, unfounded derivations when epistemic cycles come into play. Recently, the absence of these derivations was also formalised as a property of epistemic semantics called foundedness. Moreover, a first semantics proved to satisfy foundedness was also proposed, the so-called Founded Autoepistemic Equilibrium Logic (FAEEL). In this paper, we prove that FAEEL also satisfies the epistemic splitting property something that, together with foundedness, was not fulfilled by any other approach up to date. To prove this result, we provide an alternative characterisation of FAEEL as a combination of G91 with a simpler logic we called Founded Epistemic Equilibrium Logic (FEEL), which is somehow an extrapolation of the stable model semantics to the modal logic S5. T3 - Zweitveröffentlichungen der Universität Potsdam : Mathematisch-Naturwissenschaftliche Reihe - 1060 KW - answer set programming KW - epistemic specifications KW - epistemic logic programs Y1 - 2020 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:kobv:517-opus4-469685 SN - 1866-8372 IS - 1060 SP - 671 EP - 687 ER - TY - JOUR A1 - Cabalar, Pedro A1 - Fandiño, Jorge A1 - Fariñas del Cerro, Luis T1 - Splitting epistemic logic programs JF - Theory and practice of logic programming / publ. for the Association for Logic Programming N2 - Epistemic logic programs constitute an extension of the stable model semantics to deal with new constructs called subjective literals. Informally speaking, a subjective literal allows checking whether some objective literal is true in all or some stable models. As it can be imagined, the associated semantics has proved to be non-trivial, since the truth of subjective literals may interfere with the set of stable models it is supposed to query. As a consequence, no clear agreement has been reached and different semantic proposals have been made in the literature. Unfortunately, comparison among these proposals has been limited to a study of their effect on individual examples, rather than identifying general properties to be checked. In this paper, we propose an extension of the well-known splitting property for logic programs to the epistemic case. We formally define when an arbitrary semantics satisfies the epistemic splitting property and examine some of the consequences that can be derived from that, including its relation to conformant planning and to epistemic constraints. Interestingly, we prove (through counterexamples) that most of the existing approaches fail to fulfill the epistemic splitting property, except the original semantics proposed by Gelfond 1991 and a recent proposal by the authors, called Founded Autoepistemic Equilibrium Logic. KW - knowledge representation and nonmonotonic reasoning KW - logic programming methodology and applications KW - theory Y1 - 2021 U6 - https://doi.org/10.1017/S1471068420000058 SN - 1471-0684 SN - 1475-3081 VL - 21 IS - 3 SP - 296 EP - 316 PB - Cambridge Univ. Press CY - Cambridge [u.a.] ER - TY - GEN A1 - Aguado, Felicidad A1 - Cabalar, Pedro A1 - Fandiño, Jorge A1 - Pearce, David A1 - Perez, Gilberto A1 - Vidal, Concepcion T1 - Revisiting explicit negation in answer set programming T2 - Postprints der Universität Potsdam : Mathematisch-Naturwissenschaftliche Reihe N2 - A common feature in Answer Set Programming is the use of a second negation, stronger than default negation and sometimes called explicit, strong or classical negation. This explicit negation is normally used in front of atoms, rather than allowing its use as a regular operator. In this paper we consider the arbitrary combination of explicit negation with nested expressions, as those defined by Lifschitz, Tang and Turner. We extend the concept of reduct for this new syntax and then prove that it can be captured by an extension of Equilibrium Logic with this second negation. We study some properties of this variant and compare to the already known combination of Equilibrium Logic with Nelson's strong negation. T3 - Zweitveröffentlichungen der Universität Potsdam : Mathematisch-Naturwissenschaftliche Reihe - 1104 KW - Answer Set Programming KW - non-monotonic reasoning KW - Equilibrium logic KW - explicit negation Y1 - 2021 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:kobv:517-opus4-469697 SN - 1866-8372 IS - 1104 SP - 908 EP - 924 ER - TY - JOUR A1 - Göbel, Andreas A1 - Lagodzinski, Julius Albert Gregor A1 - Seidel, Karen T1 - Counting homomorphisms to trees modulo a prime JF - ACM transactions on computation theory : TOCT / Association for Computing Machinery N2 - Many important graph-theoretic notions can be encoded as counting graph homomorphism problems, such as partition functions in statistical physics, in particular independent sets and colourings. In this article, we study the complexity of #(p) HOMSTOH, the problem of counting graph homomorphisms from an input graph to a graph H modulo a prime number p. Dyer and Greenhill proved a dichotomy stating that the tractability of non-modular counting graph homomorphisms depends on the structure of the target graph. Many intractable cases in non-modular counting become tractable in modular counting due to the common phenomenon of cancellation. In subsequent studies on counting modulo 2, however, the influence of the structure of H on the tractability was shown to persist, which yields similar dichotomies.
Our main result states that for every tree H and every prime p the problem #pHOMSTOH is either polynomial time computable or #P-p-complete. This relates to the conjecture of Faben and Jerrum stating that this dichotomy holds for every graph H when counting modulo 2. In contrast to previous results on modular counting, the tractable cases of #pHOMSTOH are essentially the same for all values of the modulo when H is a tree. To prove this result, we study the structural properties of a homomorphism. As an important interim result, our study yields a dichotomy for the problem of counting weighted independent sets in a bipartite graph modulo some prime p. These results are the first suggesting that such dichotomies hold not only for the modulo 2 case but also for the modular counting functions of all primes p. KW - Graph homomorphisms KW - modular counting KW - complexity dichotomy Y1 - 2021 U6 - https://doi.org/10.1145/3460958 SN - 1942-3454 SN - 1942-3462 VL - 13 IS - 3 SP - 1 EP - 33 PB - Association for Computing Machinery CY - New York ER -