TY  - JOUR
A1  - Angeleska, Angela
A1  - Omranian, Sara
A1  - Nikoloski, Zoran
T1  - Coherent network partitions
BT  - Characterizations with cographs and prime graphs
JF  - Theoretical computer science : the journal of the EATCS
N2  - We continue to study coherent partitions of graphs whereby the vertex set is partitioned into subsets that induce biclique spanned subgraphs. The problem of identifying the minimum number of edges to obtain biclique spanned connected components (CNP), called the coherence number, is NP-hard even on bipartite graphs. Here, we propose a graph transformation geared towards obtaining an O (log n)-approximation algorithm for the CNP on a bipartite graph with n vertices. The transformation is inspired by a new characterization of biclique spanned subgraphs. In addition, we study coherent partitions on prime graphs, and show that finding coherent partitions reduces to the problem of finding coherent partitions in a prime graph. Therefore, these results provide future directions for approximation algorithms for the coherence number of a given graph.
KW  - Graph partitions
KW  - Network clustering
KW  - Cographs
KW  - Coherent partition
KW  - Prime graphs
Y1  - 2021
U6  - https://doi.org/10.1016/j.tcs.2021.10.002
SN  - 0304-3975
VL  - 894
SP  - 3
EP  - 11
PB  - Elsevier
CY  - Amsterdam [u.a.]
ER  - 
TY  - JOUR
A1  - Chen, Junchao
A1  - Lange, Thomas
A1  - Andjelkovic, Marko
A1  - Simevski, Aleksandar
A1  - Lu, Li
A1  - Krstić, Miloš
T1  - Solar particle event and single event upset prediction from SRAM-based monitor and supervised machine learning
JF  - IEEE transactions on emerging topics in computing / IEEE Computer Society, Institute of Electrical and Electronics Engineers
N2  - The intensity of cosmic radiation may differ over five orders of magnitude within a few hours or days during the Solar Particle Events (SPEs), thus increasing for several orders of magnitude the probability of Single Event Upsets (SEUs) in space-borne electronic systems. Therefore, it is vital to enable the early detection of the SEU rate changes in order to ensure timely activation of dynamic radiation hardening measures. In this paper, an embedded approach for the prediction of SPEs and SRAM SEU rate is presented. The proposed solution combines the real-time SRAM-based SEU monitor, the offline-trained machine learning model and online learning algorithm for the prediction. With respect to the state-of-the-art, our solution brings the following benefits: (1) Use of existing on-chip data storage SRAM as a particle detector, thus minimizing the hardware and power overhead, (2) Prediction of SRAM SEU rate one hour in advance, with the fine-grained hourly tracking of SEU variations during SPEs as well as under normal conditions, (3) Online optimization of the prediction model for enhancing the prediction accuracy during run-time, (4) Negligible cost of hardware accelerator design for the implementation of selected machine learning model and online learning algorithm. The proposed design is intended for a highly dependable and self-adaptive multiprocessing system employed in space applications, allowing to trigger the radiation mitigation mechanisms before the onset of high radiation levels.
KW  - Machine learning
KW  - Single event upsets
KW  - Random access memory
KW  - monitoring
KW  - machine learning algorithms
KW  - predictive models
KW  - space missions
KW  - solar particle event
KW  - single event upset
KW  - machine learning
KW  - online learning
KW  - hardware accelerator
KW  - reliability
KW  - self-adaptive multiprocessing system
Y1  - 2022
U6  - https://doi.org/10.1109/TETC.2022.3147376
SN  - 2168-6750
VL  - 10
IS  - 2
SP  - 564
EP  - 580
PB  - Institute of Electrical and Electronics Engineers
CY  - [New York, NY]
ER  - 
TY  - JOUR
A1  - Hagemann, Linus
A1  - Abramova, Olga
T1  - Emotions and information diffusion on social media
BT  - a replication in the context of political communication on Twitter
JF  - AIS transactions on replication research
N2  - This paper presents a methodological and conceptual replication of Stieglitz and Dang-Xuan’s (2013) investigation of the role of sentiment in information-sharing behavior on social media. Whereas Stieglitz and Dang-Xuan (2013) focused on Twitter communication prior to the state parliament elections in the German states Baden-Wurttemberg, Rheinland-Pfalz, and Berlin in 2011, we test their theoretical propositions in the context of the state parliament elections in Saxony-Anhalt (Germany) 2021. We confirm the positive link between sentiment in a political Twitter message and its number of retweets in a methodological replication. In a conceptual replication, where sentiment was assessed with the alternative dictionary-based tool LIWC, the sentiment was negatively associated with the retweet volume. In line with the original study, the strength of association between sentiment and retweet time lag insignificantly differs between tweets with negative sentiment and tweets with positive sentiment. We also found that the number of an author’s followers was an essential determinant of sharing behavior. However, two hypotheses supported in the original study did not hold for our sample. Precisely, the total amount of sentiments was insignificantly linked to the time lag to the first retweet. Finally, in our data, we do not observe that the association between the overall sentiment and retweet quantity is stronger for tweets with negative sentiment than for those with positive sentiment.
KW  - Twitter
KW  - information diffusion
KW  - sentiment
KW  - elections
Y1  - 2023
U6  - https://doi.org/10.17705/1atrr.00079
SN  - 2473-3458
VL  - 9
IS  - 1
SP  - 1
EP  - 19
PB  - AIS
CY  - Atlanta
ER  - 
TY  - JOUR
A1  - Steinrötter, Björn
T1  - Das Konzept einer datenaltruistischen Organisation
JF  - Datenschutz und Datensicherheit
N2  - Dass Technologien wie Machine Learning-Anwendungen oder Big bzw. Smart Data- Verfahren unbedingt Daten in ausreichender Menge und Güte benötigen, erscheint inzwischen als Binsenweisheit. Vor diesem Hintergrund hat insbesondere der EU-Gesetzgeber für sich zuletzt ein neues Betätigungsfeld entdeckt, indem er versucht, auf unterschiedlichen Wegen Anreize zum Datenteilen zu schaffen, um Innovation zu kreieren. Hierzu zählt auch eine geradezu wohltönend mit ,,Datenaltruismus‘‘ verschlagwortete Konstellation. Der Beitrag stellt die diesbezüglichen Regulierungserwägungen auf supranationaler Ebene dar und nimmt eine erste Analyse vor.
KW  - coding and information theory
KW  - computer science
KW  - general
KW  - cryptology
KW  - data structures and information theory
Y1  - 2021
U6  - https://doi.org/10.1007/s11623-021-1539-6
SN  - 1862-2607
SN  - 1614-0702
VL  - 45
IS  - 12
SP  - 794
EP  - 798
PB  - Springer
CY  - Berlin
ER  - 
TY  - JOUR
A1  - Puri, Manish
A1  - Varde, Aparna S.
A1  - Melo, Gerard de
T1  - Commonsense based text mining on urban policy
JF  - Language resources and evaluation
N2  - Local laws on urban policy, i.e., ordinances directly affect our daily life in various ways (health, business etc.), yet in practice, for many citizens they remain impervious and complex. This article focuses on an approach to make urban policy more accessible and comprehensible to the general public and to government officials, while also addressing pertinent social media postings. Due to the intricacies of the natural language, ranging from complex legalese in ordinances to informal lingo in tweets, it is practical to harness human judgment here. To this end, we mine ordinances and tweets via reasoning based on commonsense knowledge so as to better account for pragmatics and semantics in the text. Ours is pioneering work in ordinance mining, and thus there is no prior labeled training data available for learning. This gap is filled by commonsense knowledge, a prudent choice in situations involving a lack of adequate training data. The ordinance mining can be beneficial to the public in fathoming policies and to officials in assessing policy effectiveness based on public reactions. This work contributes to smart governance, leveraging transparency in governing processes via public involvement. We focus significantly on ordinances contributing to smart cities, hence an important goal is to assess how well an urban region heads towards a smart city as per its policies mapping with smart city characteristics, and the corresponding public satisfaction.
KW  - Commonsense reasoning
KW  - Opinion mining
KW  - Ordinances
KW  - Smart cities
KW  - Social
KW  - media
KW  - Text mining
Y1  - 2022
U6  - https://doi.org/10.1007/s10579-022-09584-6
SN  - 1574-020X
SN  - 1574-0218
VL  - 57
SP  - 733
EP  - 763
PB  - Springer
CY  - Dordrecht [u.a.]
ER  - 
TY  - JOUR
A1  - Kurpiers, Jona
A1  - Neher, Dieter
T1  - Dispersive Non-Geminate Recombination in an Amorphous Polymer:Fullerene Blend
JF  - Scientific reports
N2  - Recombination of free charge is a key process limiting the performance of solar cells. For low mobility materials, such as organic semiconductors, the kinetics of non-geminate recombination (NGR) is strongly linked to the motion of charges. As these materials possess significant disorder, thermalization of photogenerated carriers in the inhomogeneously broadened density of state distribution is an unavoidable process. Despite its general importance, knowledge about the kinetics of NGR in complete organic solar cells is rather limited. We employ time delayed collection field (TDCF) experiments to study the recombination of photogenerated charge in the high-performance polymer:fullerene blend PCDTBT:PCBM. NGR in the bulk of this amorphous blend is shown to be highly dispersive, with a continuous reduction of the recombination coefficient throughout the entire time scale, until all charge carriers have either been extracted or recombined. Rapid, contact-mediated recombination is identified as an additional loss channel, which, if not properly taken into account, would erroneously suggest a pronounced field dependence of charge generation. These findings are in stark contrast to the results of TDCF experiments on photovoltaic devices made from ordered blends, such as P3HT:PCBM, where non-dispersive recombination was proven to dominate the charge carrier dynamics under application relevant conditions.
Y1  - 2016
U6  - https://doi.org/10.1038/srep26832
SN  - 2045-2322
VL  - 6
PB  - Nature Publishing Group
CY  - London
ER  - 
TY  - JOUR
A1  - Neher, Dieter
A1  - Kniepert, Juliane
A1  - Elimelech, Arik
A1  - Koster, L. Jan Anton
T1  - A New Figure of Merit for Organic Solar Cells with Transport-limited Photocurrents
JF  - Scientific reports
N2  - Compared to their inorganic counterparts, organic semiconductors suffer from relatively low charge carrier mobilities. Therefore, expressions derived for inorganic solar cells to correlate characteristic performance parameters to material properties are prone to fail when applied to organic devices. This is especially true for the classical Shockley-equation commonly used to describe current-voltage (JV)-curves, as it assumes a high electrical conductivity of the charge transporting material. Here, an analytical expression for the JV-curves of organic solar cells is derived based on a previously published analytical model. This expression, bearing a similar functional dependence as the Shockley-equation, delivers a new figure of merit α to express the balance between free charge recombination and extraction in low mobility photoactive materials. This figure of merit is shown to determine critical device parameters such as the apparent series resistance and the fill factor.
KW  - Electronic and spintronic devices
KW  - Semiconductors
Y1  - 2016
U6  - https://doi.org/10.1038/srep24861
SN  - 2045-2322
VL  - 6
PB  - Nature Publishing Group
CY  - London
ER  - 
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. <br /> 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  - 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  - 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  - 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  - 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  - 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  - 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. <br /> 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  - 
TY  - JOUR
A1  - Taleb, Aiham
A1  - Rohrer, Csaba
A1  - Bergner, Benjamin
A1  - De Leon, Guilherme
A1  - Rodrigues, Jonas Almeida
A1  - Schwendicke, Falk
A1  - Lippert, Christoph
A1  - Krois, Joachim
T1  - Self-supervised learning methods for label-efficient dental caries classification
JF  - Diagnostics : open access journal
N2  - High annotation costs are a substantial bottleneck in applying deep learning architectures to clinically relevant use cases, substantiating the need for algorithms to learn from unlabeled data. 

In this work, we propose employing self-supervised methods. To that end, we trained with three self-supervised algorithms on a large corpus of unlabeled dental images, which contained 38K bitewing radiographs (BWRs). We then applied the learned neural network representations on tooth-level dental caries classification, for which we utilized labels extracted from electronic health records (EHRs). Finally, a holdout test-set was established, which consisted of 343 BWRs and was annotated by three dental professionals and approved by a senior dentist. 

This test-set was used to evaluate the fine-tuned caries classification models. Our experimental results demonstrate the obtained gains by pretraining models using self-supervised algorithms. These include improved caries classification performance (6 p.p. increase in sensitivity) and, most importantly, improved label-efficiency. 
In other words, the resulting models can be fine-tuned using few labels (annotations). 

Our results show that using as few as 18 annotations can produce >= 45% sensitivity, which is comparable to human-level diagnostic performance. 
This study shows that self-supervision can provide gains in medical image analysis, particularly when obtaining labels is costly and expensive.
KW  - unsupervised methods
KW  - self-supervised learning
KW  - representation learning
KW  - dental caries classification
KW  - data driven approaches
KW  - annotation
KW  - efficient deep learning
Y1  - 2022
U6  - https://doi.org/10.3390/diagnostics12051237
SN  - 2075-4418
VL  - 12
IS  - 5
PB  - MDPI
CY  - Basel
ER  - 
TY  - JOUR
A1  - Vitagliano, Gerardo
A1  - Hameed, Mazhar
A1  - Jiang, Lan
A1  - Reisener, Lucas
A1  - Wu, Eugene
A1  - Naumann, Felix
T1  - Pollock: a data loading benchmark
JF  - Proceedings of the VLDB Endowment
N2  - Any system at play in a data-driven project has a fundamental requirement: the ability to load data. The de-facto standard format to distribute and consume raw data is CSV. Yet, the plain text and flexible nature of this format make such files often difficult to parse and correctly load their content, requiring cumbersome data preparation steps. We propose a benchmark to assess the robustness of systems in loading data from non-standard CSV formats and with structural inconsistencies. First, we formalize a model to describe the issues that affect real-world files and use it to derive a systematic lpollutionz process to generate dialects for any given grammar. Our benchmark leverages the pollution framework for the csv format. To guide pollution, we have surveyed thousands of real-world, publicly available csv files, recording the problems we encountered. We demonstrate the applicability of our benchmark by testing and scoring 16 different systems: popular csv parsing frameworks, relational database tools, spreadsheet systems, and a data visualization tool.
Y1  - 2023
U6  - https://doi.org/10.14778/3594512.3594518
SN  - 2150-8097
VL  - 16
IS  - 8
SP  - 1870
EP  - 1882
PB  - Association for Computing Machinery
CY  - New York
ER  - 
TY  - JOUR
A1  - Nguyen, Dong Hai Phuong
A1  - Georgie, Yasmin Kim
A1  - Kayhan, Ezgi
A1  - Eppe, Manfred
A1  - Hafner, Verena Vanessa
A1  - Wermter, Stefan
T1  - Sensorimotor representation learning for an "active self" in robots
BT  - a model survey
JF  - Künstliche Intelligenz : KI ; Forschung, Entwicklung, Erfahrungen ; Organ des Fachbereichs 1 Künstliche Intelligenz der Gesellschaft für Informatik e.V., GI / Fachbereich 1 der Gesellschaft für Informatik e.V
N2  - Safe human-robot interactions require robots to be able to learn how to behave appropriately in spaces populated by people and thus to cope with the challenges posed by our dynamic and unstructured environment, rather than being provided a rigid set of rules for operations. In humans, these capabilities are thought to be related to our ability to perceive our body in space, sensing the location of our limbs during movement, being aware of other objects and agents, and controlling our body parts to interact with them intentionally. Toward the next generation of robots with bio-inspired capacities, in this paper, we first review the developmental processes of underlying mechanisms of these abilities: The sensory representations of body schema, peripersonal space, and the active self in humans. Second, we provide a survey of robotics models of these sensory representations and robotics models of the self; and we compare these models with the human counterparts. Finally, we analyze what is missing from these robotics models and propose a theoretical computational framework, which aims to allow the emergence of the sense of self in artificial agents by developing sensory representations through self-exploration.
KW  - Developmental robotics
KW  - Body schema
KW  - Peripersonal space
KW  - Agency
KW  - Robot learning
Y1  - 2021
U6  - https://doi.org/10.1007/s13218-021-00703-z
SN  - 0933-1875
SN  - 1610-1987
VL  - 35
IS  - 1
SP  - 9
EP  - 35
PB  - Springer
CY  - Berlin
ER  - 
TY  - JOUR
A1  - Wiemker, Veronika
A1  - Bunova, Anna
A1  - Neufeld, Maria
A1  - Gornyi, Boris
A1  - Yurasova, Elena
A1  - Konigorski, Stefan
A1  - Kalinina, Anna
A1  - Kontsevaya, Anna
A1  - Ferreira-Borges, Carina
A1  - Probst, Charlotte
T1  - Pilot study to evaluate usability and acceptability of the 'Animated Alcohol Assessment Tool' in Russian primary healthcare
JF  - Digital health
N2  - Background and aims: Accurate and user-friendly assessment tools quantifying alcohol consumption are a prerequisite to effective prevention and treatment programmes, including Screening and Brief Intervention. Digital tools offer new potential in this field. We developed the ‘Animated Alcohol Assessment Tool’ (AAA-Tool), a mobile app providing an interactive version of the World Health Organization's Alcohol Use Disorders Identification Test (AUDIT) that facilitates the description of individual alcohol consumption via culturally informed animation features. This pilot study evaluated the Russia-specific version of the Animated Alcohol Assessment Tool with regard to (1) its usability and acceptability in a primary healthcare setting, (2) the plausibility of its alcohol consumption assessment results and (3) the adequacy of its Russia-specific vessel and beverage selection. Methods: Convenience samples of 55 patients (47% female) and 15 healthcare practitioners (80% female) in 2 Russian primary healthcare facilities self-administered the Animated Alcohol Assessment Tool and rated their experience on the Mobile Application Rating Scale – User Version. Usage data was automatically collected during app usage, and additional feedback on regional content was elicited in semi-structured interviews. Results: On average, patients completed the Animated Alcohol Assessment Tool in 6:38 min (SD = 2.49, range = 3.00–17.16). User satisfaction was good, with all subscale Mobile Application Rating Scale – User Version scores averaging >3 out of 5 points. A majority of patients (53%) and practitioners (93%) would recommend the tool to ‘many people’ or ‘everyone’. Assessed alcohol consumption was plausible, with a low number (14%) of logically impossible entries. Most patients reported the Animated Alcohol Assessment Tool to reflect all vessels (78%) and all beverages (71%) they typically used. Conclusion: High acceptability ratings by patients and healthcare practitioners, acceptable completion time, plausible alcohol usage assessment results and perceived adequacy of region-specific content underline the Animated Alcohol Assessment Tool's potential to provide a novel approach to alcohol assessment in primary healthcare. After its validation, the Animated Alcohol Assessment Tool might contribute to reducing alcohol-related harm by facilitating Screening and Brief Intervention implementation in Russia and beyond.
KW  - Alcohol use assessment
KW  - Alcohol Use Disorders Identification Test
KW  - screening tools
KW  - digital health
KW  - mobile applications
KW  - Russia
KW  - primary healthcare
KW  - usability
KW  - acceptability
Y1  - 2022
U6  - https://doi.org/10.1177/20552076211074491
SN  - 2055-2076
VL  - 8
PB  - Sage Publications
CY  - London
ER  - 
TY  - JOUR
A1  - Omranian, Sara
A1  - Angeleska, Angela
A1  - Nikoloski, Zoran
T1  - PC2P
BT  - parameter-free network-based prediction of protein complexes
JF  - Bioinformatics
N2  - Motivation: 
Prediction of protein complexes from protein-protein interaction (PPI) networks is an important problem in systems biology, as they control different cellular functions. The existing solutions employ algorithms for network community detection that identify dense subgraphs in PPI networks. However, gold standards in yeast and human indicate that protein complexes can also induce sparse subgraphs, introducing further challenges in protein complex prediction. 

Results: 
To address this issue, we formalize protein complexes as biclique spanned subgraphs, which include both sparse and dense subgraphs. We then cast the problem of protein complex prediction as a network partitioning into biclique spanned subgraphs with removal of minimum number of edges, called coherent partition. Since finding a coherent partition is a computationally intractable problem, we devise a parameter-free greedy approximation algorithm, termed Protein Complexes from Coherent Partition (PC2P), based on key properties of biclique spanned subgraphs. Through comparison with nine contenders, we demonstrate that PC2P: (i) successfully identifies modular structure in networks, as a prerequisite for protein complex prediction, (ii) outperforms the existing solutions with respect to a composite score of five performance measures on 75% and 100% of the analyzed PPI networks and gold standards in yeast and human, respectively, and (iii,iv) does not compromise GO semantic similarity and enrichment score of the predicted protein complexes. Therefore, our study demonstrates that clustering of networks in terms of biclique spanned subgraphs is a promising framework for detection of complexes in PPI networks.
Y1  - 2021
U6  - https://doi.org/10.1093/bioinformatics/btaa1089
SN  - 1367-4811
VL  - 37
IS  - 1
SP  - 73
EP  - 81
PB  - Oxford Univ. Press
CY  - Oxford
ER  - 
TY  - JOUR
A1  - Ulrich, Jens-Uwe
A1  - Lutfi, Ahmad
A1  - Rutzen, Kilian
A1  - Renard, Bernhard Y.
T1  - ReadBouncer
BT  - precise and scalable adaptive sampling for nanopore sequencing
JF  - Bioinformatics
N2  - Motivation: 
Nanopore sequencers allow targeted sequencing of interesting nucleotide sequences by rejecting other sequences from individual pores. This feature facilitates the enrichment of low-abundant sequences by depleting overrepresented ones in-silico. Existing tools for adaptive sampling either apply signal alignment, which cannot handle human-sized reference sequences, or apply read mapping in sequence space relying on fast graphical processing units (GPU) base callers for real-time read rejection. Using nanopore long-read mapping tools is also not optimal when mapping shorter reads as usually analyzed in adaptive sampling applications. 

Results: 
Here, we present a new approach for nanopore adaptive sampling that combines fast CPU and GPU base calling with read classification based on Interleaved Bloom Filters. ReadBouncer improves the potential enrichment of low abundance sequences by its high read classification sensitivity and specificity, outperforming existing tools in the field. It robustly removes even reads belonging to large reference sequences while running on commodity hardware without GPUs, making adaptive sampling accessible for in-field researchers. Readbouncer also provides a user-friendly interface and installer files for end-users without a bioinformatics background.
Y1  - 2022
U6  - https://doi.org/10.1093/bioinformatics/btac223
SN  - 1367-4803
SN  - 1367-4811
VL  - 38
IS  - SUPPL 1
SP  - 153
EP  - 160
PB  - Oxford Univ. Press
CY  - Oxford
ER  - 
TY  - JOUR
A1  - Wittig, Alice
A1  - Miranda, Fabio Malcher
A1  - Hölzer, Martin
A1  - Altenburg, Tom
A1  - Bartoszewicz, Jakub Maciej
A1  - Beyvers, Sebastian
A1  - Dieckmann, Marius Alfred
A1  - Genske, Ulrich
A1  - Giese, Sven Hans-Joachim
A1  - Nowicka, Melania
A1  - Richard, Hugues
A1  - Schiebenhoefer, Henning
A1  - Schmachtenberg, Anna-Juliane
A1  - Sieben, Paul
A1  - Tang, Ming
A1  - Tembrockhaus, Julius
A1  - Renard, Bernhard Y.
A1  - Fuchs, Stephan
T1  - CovRadar
BT  - continuously tracking and filtering SARS-CoV-2 mutations for genomic surveillance
JF  - Bioinformatics
N2  - The ongoing pandemic caused by SARS-CoV-2 emphasizes the importance of genomic surveillance to understand the evolution of the virus, to monitor the viral population, and plan epidemiological responses. Detailed analysis, easy visualization and intuitive filtering of the latest viral sequences are powerful for this purpose. We present CovRadar, a tool for genomic surveillance of the SARS-CoV-2 Spike protein. CovRadar consists of an analytical pipeline and a web application that enable the analysis and visualization of hundreds of thousand sequences. First, CovRadar extracts the regions of interest using local alignment, then builds a multiple sequence alignment, infers variants and consensus and finally presents the results in an interactive app, making accessing and reporting simple, flexible and fast.
Y1  - 2022
U6  - https://doi.org/10.1093/bioinformatics/btac411
SN  - 1367-4803
SN  - 1367-4811
VL  - 38
IS  - 17
SP  - 4223
EP  - 4225
PB  - Oxford Univ. Press
CY  - Oxford
ER  - 
TY  - JOUR
A1  - Trautmann, Justin
A1  - Zhou, Lin
A1  - Brahms, Clemens Markus
A1  - Tunca, Can
A1  - Ersoy, Cem
A1  - Granacher, Urs
A1  - Arnrich, Bert
T1  - TRIPOD
BT  - A treadmill walking dataset with IMU, pressure-distribution  and photoelectric data for gait analysis
JF  - Data : open access ʻData in scienceʼ journal
N2  - Inertial measurement units (IMUs) enable easy to operate and low-cost data recording for gait analysis. When combined with treadmill walking, a large number of steps can be collected in a controlled environment without the need of a dedicated gait analysis laboratory. In order to evaluate existing and novel IMU-based gait analysis algorithms for treadmill walking, a reference dataset that includes IMU data as well as reliable ground truth measurements for multiple participants and walking speeds is needed. This article provides a reference dataset consisting of 15 healthy young adults who walked on a treadmill at three different speeds. Data were acquired using seven IMUs placed on the lower body, two different reference systems (Zebris FDMT-HQ and OptoGait), and two RGB cameras. Additionally, in order to validate an existing IMU-based gait analysis algorithm using the dataset, an adaptable modular data analysis pipeline was built. Our results show agreement between the pressure-sensitive Zebris and the photoelectric OptoGait system (r = 0.99), demonstrating the quality of our reference data. As a use case, the performance of an algorithm originally designed for overground walking was tested on treadmill data using the data pipeline. The accuracy of stride length and stride time estimations was comparable to that reported in other studies with overground data, indicating that the algorithm is equally applicable to treadmill data. The Python source code of the data pipeline is publicly available, and the dataset will be provided by the authors upon request, enabling future evaluations of IMU gait analysis algorithms without the need of recording new data.
KW  - inertial measurement unit
KW  - gait analysis algorithm
KW  - OptoGait
KW  - Zebris
KW  - data pipeline
KW  - public dataset
Y1  - 2021
U6  - https://doi.org/10.3390/data6090095
SN  - 2306-5729
VL  - 6
IS  - 9
PB  - MDPI
CY  - Basel
ER  - 
TY  - JOUR
A1  - De Freitas, Jessica K.
A1  - Johnson, Kipp W.
A1  - Golden, Eddye
A1  - Nadkarni, Girish N.
A1  - Dudley, Joel T.
A1  - Böttinger, Erwin
A1  - Glicksberg, Benjamin S.
A1  - Miotto, Riccardo
T1  - Phe2vec
BT  - Automated disease phenotyping based on unsupervised embeddings from electronic health records
JF  - Patterns
N2  - Robust phenotyping of patients from electronic health records (EHRs) at scale is a challenge in clinical informatics. Here, we introduce Phe2vec, an automated framework for disease phenotyping from EHRs based on unsupervised learning and assess its effectiveness against standard rule-based algorithms from Phenotype KnowledgeBase (PheKB). Phe2vec is based on pre-computing embeddings of medical concepts and patients' clinical history. Disease phenotypes are then derived from a seed concept and its neighbors in the embedding space. Patients are linked to a disease if their embedded representation is close to the disease phenotype. Comparing Phe2vec and PheKB cohorts head-to-head using chart review, Phe2vec performed on par or better in nine out of ten diseases. Differently from other approaches, it can scale to any condition and was validated against widely adopted expert-based standards. Phe2vec aims to optimize clinical informatics research by augmenting current frameworks to characterize patients by condition and derive reliable disease cohorts.
Y1  - 2021
U6  - https://doi.org/10.1016/j.patter.2021.100337
SN  - 2666-3899
VL  - 2
IS  - 9
PB  - Elsevier
CY  - Amsterdam
ER  - 
TY  - JOUR
A1  - Freitas da Cruz, Harry
A1  - Pfahringer, Boris
A1  - Martensen, Tom
A1  - Schneider, Frederic
A1  - Meyer, Alexander
A1  - Böttinger, Erwin
A1  - Schapranow, Matthieu-Patrick
T1  - Using interpretability approaches to update "black-box" clinical prediction models
BT  - an external validation study in nephrology
JF  - Artificial intelligence in medicine : AIM
N2  - Despite advances in machine learning-based clinical prediction models, only few of such models are actually deployed in clinical contexts. Among other reasons, this is due to a lack of validation studies. In this paper, we present and discuss the validation results of a machine learning model for the prediction of acute kidney injury in cardiac surgery patients initially developed on the MIMIC-III dataset when applied to an external cohort of an American research hospital. To help account for the performance differences observed, we utilized interpretability methods based on feature importance, which allowed experts to scrutinize model behavior both at the global and local level, making it possible to gain further insights into why it did not behave as expected on the validation cohort. The knowledge gleaned upon derivation can be potentially useful to assist model update during validation for more generalizable and simpler models. We argue that interpretability methods should be considered by practitioners as a further tool to help explain performance differences and inform model update in validation studies.
KW  - Clinical predictive modeling
KW  - Nephrology
KW  - Validation
KW  - Interpretability
KW  - methods
Y1  - 2021
U6  - https://doi.org/10.1016/j.artmed.2020.101982
SN  - 0933-3657
SN  - 1873-2860
VL  - 111
PB  - Elsevier
CY  - Amsterdam
ER  - 
TY  - JOUR
A1  - Borchert, Florian
A1  - Mock, Andreas
A1  - Tomczak, Aurelie
A1  - Hügel, Jonas
A1  - Alkarkoukly, Samer
A1  - Knurr, Alexander
A1  - Volckmar, Anna-Lena
A1  - Stenzinger, Albrecht
A1  - Schirmacher, Peter
A1  - Debus, Jürgen
A1  - Jäger, Dirk
A1  - Longerich, Thomas
A1  - Fröhling, Stefan
A1  - Eils, Roland
A1  - Bougatf, Nina
A1  - Sax, Ulrich
A1  - Schapranow, Matthieu-Patrick
T1  - Knowledge bases and software support for variant interpretation in precision oncology
JF  - Briefings in bioinformatics
N2  - Precision oncology is a rapidly evolving interdisciplinary medical specialty. Comprehensive cancer panels are becoming increasingly available at pathology departments worldwide, creating the urgent need for scalable cancer variant annotation and molecularly informed treatment recommendations. A wealth of mainly academia-driven knowledge bases calls for software tools supporting the multi-step diagnostic process. We derive a comprehensive list of knowledge bases relevant for variant interpretation by a review of existing literature followed by a survey among medical experts from university hospitals in Germany. In addition, we review cancer variant interpretation tools, which integrate multiple knowledge bases. We categorize the knowledge bases along the diagnostic process in precision oncology and analyze programmatic access options as well as the integration of knowledge bases into software tools. The most commonly used knowledge bases provide good programmatic access options and have been integrated into a range of software tools. For the wider set of knowledge bases, access options vary across different parts of the diagnostic process. Programmatic access is limited for information regarding clinical classifications of variants and for therapy recommendations. The main issue for databases used for biological classification of pathogenic variants and pathway context information is the lack of standardized interfaces. There is no single cancer variant interpretation tool that integrates all identified knowledge bases. Specialized tools are available and need to be further developed for different steps in the diagnostic process.
KW  - HiGHmed
KW  - personalized medicine
KW  - molecular tumor board
KW  - data integration
KW  - cancer therapy
Y1  - 2021
U6  - https://doi.org/10.1093/bib/bbab134
SN  - 1467-5463
SN  - 1477-4054
VL  - 22
IS  - 6
PB  - Oxford Univ. Press
CY  - Oxford
ER  - 
TY  - JOUR
A1  - XinYing, Chew
A1  - Tiberius, Victor
A1  - Alnoor, Alhamzah
A1  - Camilleri, Mark
A1  - Khaw, Khai Wah
T1  - The dark side of metaverse: a multi-perspective of deviant behaviors from PLS-SEM and fsQCA findings
JF  - International journal of human–computer interaction
N2  - The metaverse has created a huge buzz of interest because such a phenomenon is emerging. The behavioral aspect of the metaverse includes user engagement and deviant behaviors in the metaverse. Such technology has brought various dangers to individuals and society. There are growing cases reported of sexual abuse, racism, harassment, hate speech, and bullying because of online disinhibition make us feel more relaxed. This study responded to the literature call by investigating the effect of technical and social features through mediating roles of security and privacy on deviant behaviors in the metaverse. The data collected from virtual network users reached 1121 respondents. Partial Least Squares based structural equation modeling (PLS-SEM) and fuzzy set Qualitative Comparative Analysis (fsQCA) were used. PLS-SEM results revealed that social features such as user-to-user interaction, homophily, social ties, and social identity, and technical design such as immersive experience and invisibility significantly affect users’ deviant behavior in the metaverse. The fsQCA results provided insights into the multiple causal solutions and configurations. This study is exceptional because it provided decisive results by understanding the deviant behavior of users based on the symmetrical and asymmetrical approach to virtual networks.
KW  - deviant behaviors
KW  - metaverse
KW  - sociotechnical
KW  - perspective
KW  - privacy
KW  - fsQCA
Y1  - 2024
U6  - https://doi.org/10.1080/10447318.2024.2331875
SN  - 1044-7318
SN  - 1532-7590
PB  - Taylor & Francis
CY  - London
ER  - 
TY  - JOUR
A1  - Kühler, Jakob
A1  - Drathschmidt, Nicolas
A1  - Großmann, Daniela
T1  - ‘Modern talking’
BT  - narratives of agile by German public sector employees
JF  - Information polity
N2  - Despite growing interest, we lack a clear understanding of how the arguably ambiguous phenomenon of agile is perceived in government practice. This study aims to alleviate this puzzle by investigating how managers and employees in German public sector organisations make sense of agile as a spreading management fashion in the form of narratives. This is important because narratives function as innovation carriers that ultimately influence the manifestations of the concept in organisations. Based on a multi-case study of 31 interviews and 24 responses to a qualitative online survey conducted in 2021 and 2022, we provide insights into what public sector managers, employees and consultants understand (and, more importantly, do not understand) as agile and how they weave it into their existing reality of bureaucratic organisations. We uncover three meta-narratives of agile government, which we label ‘renew’, ‘complement’ and ‘integrate’. In particular, the meta-narratives differ in their positioning of how agile interacts with the characteristics of bureaucratic organisations. Importantly, we also show that agile as a management fad serves as a projection surface for what actors want from a modern and digital organisation. Thus, the vocabulary of agile government within the narratives is inherently linked to other diffusing phenomena such as new work or digitalisation.
KW  - agile government
KW  - agility
KW  - narratives
KW  - public administration
KW  - public sector organizations
KW  - fashion
KW  - digital transformation
KW  - interpretative research
Y1  - 2024
U6  - https://doi.org/10.3233/IP-230059
SN  - 1570-1255
SN  - 1875-8754
VL  - 29
IS  - 2
SP  - 199
EP  - 216
PB  - IOS Press
CY  - Amsterdam
ER  - 
TY  - JOUR
A1  - Richly, Keven
A1  - Schlosser, Rainer
A1  - Boissier, Martin
T1  - Budget-conscious fine-grained configuration optimization for spatio-temporal applications
JF  - Proceedings of the VLDB Endowment
N2  - Based on the performance requirements of modern spatio-temporal data mining applications, in-memory database systems are often used to store and process the data. To efficiently utilize the scarce DRAM capacities, modern database systems support various tuning possibilities to reduce the memory footprint (e.g., data compression) or increase performance (e.g., additional indexes). However, the selection of cost and performance balancing configurations is challenging due to the vast number of possible setups consisting of mutually dependent individual decisions. In this paper, we introduce a novel approach to jointly optimize the compression, sorting, indexing, and tiering configuration for spatio-temporal workloads. Further, we consider horizontal data partitioning, which enables the independent application of different tuning options on a fine-grained level. We propose different linear programming (LP) models addressing cost dependencies at different levels of accuracy to compute optimized tuning configurations for a given workload and memory budgets. To yield maintainable and robust configurations, we extend our LP-based approach to incorporate reconfiguration costs as well as a worst-case optimization for potential workload scenarios. Further, we demonstrate on a real-world dataset that our models allow to significantly reduce the memory footprint with equal performance or increase the performance with equal memory size compared to existing tuning heuristics.
KW  - General Earth and Planetary Sciences
KW  - Water Science and Technology
KW  - Geography, Planning and Development
Y1  - 2022
U6  - https://doi.org/10.14778/3565838.3565858
SN  - 2150-8097
VL  - 15
IS  - 13
SP  - 4079
EP  - 4092
PB  - Association for Computing Machinery (ACM)
CY  - [New York]
ER  - 
TY  - JOUR
A1  - Schladebach, Marcus
T1  - Satelliten-Megakonstellationen im Weltraumrecht
JF  - Kommunikation & Recht : K & R / Beihefter
Y1  - 2022
SN  - 1434-6354
IS  - 2
SP  - 26
EP  - 29
PB  - dfv-Mediengruppe
CY  - Frankfurt am Main
ER  - 
TY  - JOUR
A1  - Fandiño, Jorge
A1  - Laferriere, Francois
A1  - Romero, Javier
A1  - Schaub, Torsten
A1  - Son, Tran Cao
T1  - Planning with incomplete information in quantified answer set programming
JF  - Theory and practice of logic programming
N2  - We present a general approach to planning with incomplete information in Answer Set Programming (ASP). More precisely, we consider the problems of conformant and conditional planning with sensing actions and assumptions. We represent planning problems using a simple formalism where logic programs describe the transition function between states, the initial states and the goal states. For solving planning problems, we use Quantified Answer Set Programming (QASP), an extension of ASP with existential and universal quantifiers over atoms that is analogous to Quantified Boolean Formulas (QBFs). We define the language of quantified logic programs and use it to represent the solutions different variants of conformant and conditional planning. On the practical side, we present a translation-based QASP solver that converts quantified logic programs into QBFs and then executes a QBF solver, and we evaluate experimentally the approach on conformant and conditional planning benchmarks.
KW  - answer set programming
KW  - planning
KW  - quantified logics
Y1  - 2021
U6  - https://doi.org/10.1017/S1471068421000259
SN  - 1471-0684
SN  - 1475-3081
VL  - 21
IS  - 5
SP  - 663
EP  - 679
PB  - Cambridge University Press
CY  - Cambridge
ER  - 
TY  - JOUR
A1  - Brewka, Gerhard
A1  - Ellmauthaler, Stefan
A1  - Kern-Isberner, Gabriele
A1  - Obermeier, Philipp
A1  - Ostrowski, Max
A1  - Romero, Javier
A1  - Schaub, Torsten
A1  - Schieweck, Steffen
T1  - Advanced solving technology for dynamic and reactive applications
JF  - Künstliche Intelligenz
Y1  - 2018
U6  - https://doi.org/10.1007/s13218-018-0538-8
SN  - 0933-1875
SN  - 1610-1987
VL  - 32
IS  - 2-3
SP  - 199
EP  - 200
PB  - Springer
CY  - Heidelberg
ER  - 
TY  - JOUR
A1  - Dimopoulos, Yannis
A1  - Gebser, Martin
A1  - Lühne, Patrick
A1  - Romero Davila, Javier
A1  - Schaub, Torsten
T1  - plasp 3
BT  - Towards Effective ASP Planning
JF  - Theory and practice of logic programming
N2  - We describe the new version of the Planning Domain Definition Language (PDDL)-to-Answer Set Programming (ASP) translator plasp. First, it widens the range of accepted PDDL features. Second, it contains novel planning encodings, some inspired by Satisfiability Testing (SAT) planning and others exploiting ASP features such as well-foundedness. All of them are designed for handling multivalued fluents in order to capture both PDDL as well as SAS planning formats. Third, enabled by multishot ASP solving, it offers advanced planning algorithms also borrowed from SAT planning. As a result, plasp provides us with an ASP-based framework for studying a variety of planning techniques in a uniform setting. Finally, we demonstrate in an empirical analysis that these techniques have a significant impact on the performance of ASP planning.
KW  - knowledge representation and nonmonotonic reasoning
KW  - technical notes and rapid communications
KW  - answer set programming
KW  - automated planning
KW  - action and change
Y1  - 2019
U6  - https://doi.org/10.1017/S1471068418000583
SN  - 1471-0684
SN  - 1475-3081
VL  - 19
IS  - 3
SP  - 477
EP  - 504
PB  - Cambridge Univ. Press
CY  - New York
ER  - 
TY  - JOUR
A1  - Gebser, Martin
A1  - Kaminski, Roland
A1  - Kaufmann, Benjamin
A1  - Lühne, Patrick
A1  - Obermeier, Philipp
A1  - Ostrowski, Max
A1  - Romero Davila, Javier
A1  - Schaub, Torsten
A1  - Schellhorn, Sebastian
A1  - Wanko, Philipp
T1  - The Potsdam Answer Set Solving Collection 5.0
JF  - Künstliche Intelligenz
N2  - The Potsdam answer set solving collection, or Potassco for short, bundles various tools implementing and/or applying answer set programming. The article at hand succeeds an earlier description of the Potassco project published in Gebser et al. (AI Commun 24(2):107-124, 2011). Hence, we concentrate in what follows on the major features of the most recent, fifth generation of the ASP system clingo and highlight some recent resulting application systems.
Y1  - 2018
U6  - https://doi.org/10.1007/s13218-018-0528-x
SN  - 0933-1875
SN  - 1610-1987
VL  - 32
IS  - 2-3
SP  - 181
EP  - 182
PB  - Springer
CY  - Heidelberg
ER  - 
TY  - JOUR
A1  - Schaub, Torsten
A1  - Woltran, Stefan
T1  - Answer set programming unleashed!
JF  - Künstliche Intelligenz
N2  - Answer Set Programming faces an increasing popularity for problem solving in various domains. While its modeling language allows us to express many complex problems in an easy way, its solving technology enables their effective resolution. In what follows, we detail some of the key factors of its success. Answer Set Programming [ASP; Brewka et al. Commun ACM 54(12):92–103, (2011)] is seeing a rapid proliferation in academia and industry due to its easy and flexible way to model and solve knowledge-intense combinatorial (optimization) problems. To this end, ASP offers a high-level modeling language paired with high-performance solving technology. As a result, ASP systems provide out-off-the-box, general-purpose search engines that allow for enumerating (optimal) solutions. They are represented as answer sets, each being a set of atoms representing a solution. The declarative approach of ASP allows a user to concentrate on a problem’s specification rather than the computational means to solve it. This makes ASP a prime candidate for rapid prototyping and an attractive tool for teaching key AI techniques since complex problems can be expressed in a succinct and elaboration tolerant way. This is eased by the tuning of ASP’s modeling language to knowledge representation and reasoning (KRR). The resulting impact is nicely reflected by a growing range of successful applications of ASP [Erdem et al. AI Mag 37(3):53–68, 2016; Falkner et al. Industrial applications of answer set programming. K++nstliche Intelligenz (2018)]
Y1  - 2018
U6  - https://doi.org/10.1007/s13218-018-0550-z
SN  - 0933-1875
SN  - 1610-1987
VL  - 32
IS  - 2-3
SP  - 105
EP  - 108
PB  - Springer
CY  - Heidelberg
ER  - 
TY  - JOUR
A1  - Haubelt, Christian
A1  - Neubauer, Kai
A1  - Schaub, Torsten
A1  - Wanko, Philipp
T1  - Design space exploration with answer set programming
JF  - Künstliche Intelligenz
N2  - The aim of our project design space exploration with answer set programming is to develop a general framework based on Answer Set Programming (ASP) that finds valid solutions to the system design problem and simultaneously performs Design Space Exploration (DSE) to find the most favorable alternatives. We leverage recent developments in ASP solving that allow for tight integration of background theories to create a holistic framework for effective DSE.
Y1  - 2018
U6  - https://doi.org/10.1007/s13218-018-0530-3
SN  - 0933-1875
SN  - 1610-1987
VL  - 32
IS  - 2-3
SP  - 205
EP  - 206
PB  - Springer
CY  - Heidelberg
ER  -