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 -