TY - JOUR
A1 - Nordmeyer, Sarah
A1 - Kraus, Milena
A1 - Ziehm, Matthias
A1 - Kirchner, Marieluise
A1 - Schafstedde, Marie
A1 - Kelm, Marcus
A1 - Niquet, Sylvia
A1 - Stephen, Mariet Mathew
A1 - Baczko, Istvan
A1 - Knosalla, Christoph
A1 - Schapranow, Matthieu-Patrick
A1 - Dittmar, Gunnar
A1 - Gotthardt, Michael
A1 - Falcke, Martin
A1 - Regitz-Zagrosek, Vera
A1 - Kuehne, Titus
A1 - Mertins, Philipp
T1 - Disease- and sex-specific differences in patients with heart valve disease
BT - a proteome study
JF - Life Science Alliance
N2 - Pressure overload in patients with aortic valve stenosis and volume overload in mitral valve regurgitation trigger specific forms of cardiac remodeling; however, little is known about similarities and differences in myocardial proteome regulation. We performed proteome profiling of 75 human left ventricular myocardial biopsies (aortic stenosis = 41, mitral regurgitation = 17, and controls = 17) using high-resolution tandem mass spectrometry next to clinical and hemodynamic parameter acquisition. In patients of both disease groups, proteins related to ECM and cytoskeleton were more abundant, whereas those related to energy metabolism and proteostasis were less abundant compared with controls. In addition, disease group-specific and sex-specific differences have been observed. Male patients with aortic stenosis showed more proteins related to fibrosis and less to energy metabolism, whereas female patients showed strong reduction in proteostasis-related proteins. Clinical imaging was in line with proteomic findings, showing elevation of fibrosis in both patient groups and sex differences. Disease-and sex-specific proteomic profiles provide insight into cardiac remodeling in patients with heart valve disease and might help improve the understanding of molecular mechanisms and the development of individualized treatment strategies.
Y1 - 2023
U6 - https://doi.org/10.26508/lsa.202201411
SN - 2575-1077
VL - 6
IS - 3
PB - EMBO Press
CY - Heidelberg
ER -
TY - JOUR
A1 - Zhou, Lin
A1 - Fischer, Eric
A1 - Brahms, Clemens Markus
A1 - Granacher, Urs
A1 - Arnrich, Bert
T1 - DUO-GAIT
BT - a gait dataset for walking under dual-task and fatigue conditions with inertial measurement units
JF - Scientific data
N2 - In recent years, there has been a growing interest in developing and evaluating gait analysis algorithms based on inertial measurement unit (IMU) data, which has important implications, including sports, assessment of diseases, and rehabilitation. Multi-tasking and physical fatigue are two relevant aspects of daily life gait monitoring, but there is a lack of publicly available datasets to support the development and testing of methods using a mobile IMU setup. We present a dataset consisting of 6-minute walks under single- (only walking) and dual-task (walking while performing a cognitive task) conditions in unfatigued and fatigued states from sixteen healthy adults. Especially, nine IMUs were placed on the head, chest, lower back, wrists, legs, and feet to record under each of the above-mentioned conditions. The dataset also includes a rich set of spatio-temporal gait parameters that capture the aspects of pace, symmetry, and variability, as well as additional study-related information to support further analysis. This dataset can serve as a foundation for future research on gait monitoring in free-living environments.
Y1 - 2023
U6 - https://doi.org/10.1038/s41597-023-02391-w
SN - 2052-4463
VL - 10
IS - 1
PB - Nature Publ. Group
CY - London
ER -
TY - JOUR
A1 - Konak, Orhan
A1 - van de Water, Robin
A1 - Döring, Valentin
A1 - Fiedler, Tobias
A1 - Liebe, Lucas
A1 - Masopust, Leander
A1 - Postnov, Kirill
A1 - Sauerwald, Franz
A1 - Treykorn, Felix
A1 - Wischmann, Alexander
A1 - Gjoreski, Hristijan
A1 - Luštrek, Mitja
A1 - Arnrich, Bert
T1 - HARE
BT - unifying the human activity recognition engineering workflow
JF - Sensors
N2 - Sensor-based human activity recognition is becoming ever more prevalent. The increasing importance of distinguishing human movements, particularly in healthcare, coincides with the advent of increasingly compact sensors. A complex sequence of individual steps currently characterizes the activity recognition pipeline. It involves separate data collection, preparation, and processing steps, resulting in a heterogeneous and fragmented process. To address these challenges, we present a comprehensive framework, HARE, which seamlessly integrates all necessary steps. HARE offers synchronized data collection and labeling, integrated pose estimation for data anonymization, a multimodal classification approach, and a novel method for determining optimal sensor placement to enhance classification results. Additionally, our framework incorporates real-time activity recognition with on-device model adaptation capabilities. To validate the effectiveness of our framework, we conducted extensive evaluations using diverse datasets, including our own collected dataset focusing on nursing activities. Our results show that HARE’s multimodal and on-device trained model outperforms conventional single-modal and offline variants. Furthermore, our vision-based approach for optimal sensor placement yields comparable results to the trained model. Our work advances the field of sensor-based human activity recognition by introducing a comprehensive framework that streamlines data collection and classification while offering a novel method for determining optimal sensor placement.
KW - human activity recognition
KW - multimodal classification
KW - privacy preservation
KW - real-time classification
KW - sensor placement
Y1 - 2023
U6 - https://doi.org/10.3390/s23239571
SN - 1424-8220
VL - 23
IS - 23
PB - MDPI
CY - Basel
ER -
TY - JOUR
A1 - Kastius, Alexander
A1 - Schlosser, Rainer
T1 - Dynamic pricing under competition using reinforcement learning
JF - Journal of revenue and pricing management
N2 - Dynamic pricing is considered a possibility to gain an advantage over competitors in modern online markets. The past advancements in Reinforcement Learning (RL) provided more capable algorithms that can be used to solve pricing problems. In this paper, we study the performance of Deep Q-Networks (DQN) and Soft Actor Critic (SAC) in different market models. We consider tractable duopoly settings, where optimal solutions derived by dynamic programming techniques can be used for verification, as well as oligopoly settings, which are usually intractable due to the curse of dimensionality. We find that both algorithms provide reasonable results, while SAC performs better than DQN. Moreover, we show that under certain conditions, RL algorithms can be forced into collusion by their competitors without direct communication.
KW - Dynamic pricing
KW - Competition
KW - Reinforcement learning
KW - E-commerce
KW - Price collusion
Y1 - 2021
U6 - https://doi.org/10.1057/s41272-021-00285-3
SN - 1476-6930
SN - 1477-657X
VL - 21
IS - 1
SP - 50
EP - 63
PB - Springer Nature Switzerland AG
CY - Cham
ER -
TY - JOUR
A1 - Mattis, Toni
A1 - Beckmann, Tom
A1 - Rein, Patrick
A1 - Hirschfeld, Robert
T1 - First-class concepts
BT - Reified architectural knowledge beyond dominant decompositions
JF - Journal of object technology : JOT / ETH Zürich, Department of Computer Science
N2 - Ideally, programs are partitioned into independently maintainable and understandable modules. As a system grows, its architecture gradually loses the capability to accommodate new concepts in a modular way. While refactoring is expensive and not always possible, and the programming language might lack dedicated primary language constructs to express certain cross-cutting concerns, programmers are still able to explain and delineate convoluted concepts through secondary means: code comments, use of whitespace and arrangement of code, documentation, or communicating tacit knowledge.
Secondary constructs are easy to change and provide high flexibility in communicating cross-cutting concerns and other concepts among programmers. However, such secondary constructs usually have no reified representation that can be explored and manipulated as first-class entities through the programming environment.
In this exploratory work, we discuss novel ways to express a wide range of concepts, including cross-cutting concerns, patterns, and lifecycle artifacts independently of the dominant decomposition imposed by an existing architecture. We propose the representation of concepts as first-class objects inside the programming environment that retain the capability to change as easily as code comments. We explore new tools that allow programmers to view, navigate, and change programs based on conceptual perspectives. In a small case study, we demonstrate how such views can be created and how the programming experience changes from draining programmers' attention by stretching it across multiple modules toward focusing it on cohesively presented concepts. Our designs are geared toward facilitating multiple secondary perspectives on a system to co-exist in symbiosis with the original architecture, hence making it easier to explore, understand, and explain complex contexts and narratives that are hard or impossible to express using primary modularity constructs.
KW - software engineering
KW - modularity
KW - exploratory programming
KW - program
KW - comprehension
KW - remodularization
KW - architecture recovery
Y1 - 2022
U6 - https://doi.org/10.5381/jot.2022.21.2.a6
SN - 1660-1769
VL - 21
IS - 2
SP - 1
EP - 15
PB - ETH Zürich, Department of Computer Science
CY - Zürich
ER -
TY - JOUR
A1 - Schmidl, Sebastian
A1 - Papenbrock, Thorsten
T1 - Efficient distributed discovery of bidirectional order dependencies
JF - The VLDB journal
N2 - Bidirectional order dependencies (bODs) capture order relationships between lists of attributes in a relational table. They can express that, for example, sorting books by publication date in ascending order also sorts them by age in descending order. The knowledge about order relationships is useful for many data management tasks, such as query optimization, data cleaning, or consistency checking. Because the bODs of a specific dataset are usually not explicitly given, they need to be discovered. The discovery of all minimal bODs (in set-based canonical form) is a task with exponential complexity in the number of attributes, though, which is why existing bOD discovery algorithms cannot process datasets of practically relevant size in a reasonable time. In this paper, we propose the distributed bOD discovery algorithm DISTOD, whose execution time scales with the available hardware. DISTOD is a scalable, robust, and elastic bOD discovery approach that combines efficient pruning techniques for bOD candidates in set-based canonical form with a novel, reactive, and distributed search strategy. Our evaluation on various datasets shows that DISTOD outperforms both single-threaded and distributed state-of-the-art bOD discovery algorithms by up to orders of magnitude; it can, in particular, process much larger datasets.
KW - Bidirectional order dependencies
KW - Distributed computing
KW - Actor
KW - programming
KW - Parallelization
KW - Data profiling
KW - Dependency discovery
Y1 - 2021
U6 - https://doi.org/10.1007/s00778-021-00683-4
SN - 1066-8888
SN - 0949-877X
VL - 31
IS - 1
SP - 49
EP - 74
PB - Springer
CY - Berlin ; Heidelberg ; New York
ER -
TY - JOUR
A1 - Schlosser, Rainer
T1 - Heuristic mean-variance optimization in Markov decision processes using state-dependent risk aversion
JF - IMA journal of management mathematics / Institute of Mathematics and Its Applications
N2 - In dynamic decision problems, it is challenging to find the right balance between maximizing expected rewards and minimizing risks. In this paper, we consider NP-hard mean-variance (MV) optimization problems in Markov decision processes with a finite time horizon. We present a heuristic approach to solve MV problems, which is based on state-dependent risk aversion and efficient dynamic programming techniques. Our approach can also be applied to mean-semivariance (MSV) problems, which particularly focus on the downside risk. We demonstrate the applicability and the effectiveness of our heuristic for dynamic pricing applications. Using reproducible examples, we show that our approach outperforms existing state-of-the-art benchmark models for MV and MSV problems while also providing competitive runtimes. Further, compared to models based on constant risk levels, we find that state-dependent risk aversion allows to more effectively intervene in case sales processes deviate from their planned paths. Our concepts are domain independent, easy to implement and of low computational complexity.
KW - risk aversion
KW - mean-variance optimization
KW - Markov decision process;
KW - dynamic programming
KW - dynamic pricing
KW - heuristics
Y1 - 2021
U6 - https://doi.org/10.1093/imaman/dpab009
SN - 1471-678X
SN - 1471-6798
VL - 33
IS - 2
SP - 181
EP - 199
PB - Oxford Univ. Press
CY - Oxford
ER -
TY - JOUR
A1 - Andree, Kerstin
A1 - Ihde, Sven
A1 - Weske, Mathias
A1 - Pufahl, Luise
T1 - An exception handling framework for case management
JF - Software and Systems Modeling
N2 - In order to achieve their business goals, organizations heavily rely on the operational excellence of their business processes. In traditional scenarios, business processes are usually well-structured, clearly specifying when and how certain tasks have to be executed. Flexible and knowledge-intensive processes are gathering momentum, where a knowledge worker drives the execution of a process case and determines the exact process path at runtime. In the case of an exception, the knowledge worker decides on an appropriate handling. While there is initial work on exception handling in well-structured business processes, exceptions in case management have not been sufficiently researched. This paper proposes an exception handling framework for stage-oriented case management languages, namely Guard Stage Milestone Model, Case Management Model and Notation, and Fragment-based Case Management. The effectiveness of the framework is evaluated with two real-world use cases showing that it covers all relevant exceptions and proposed handling strategies.
KW - Exception handling
KW - Knowledge-intensive processes
KW - Flexible processes;
KW - Case management
Y1 - 2022
U6 - https://doi.org/10.1007/s10270-022-00993-3
SN - 1619-1366
SN - 1619-1374
VL - 21
IS - 3
SP - 939
EP - 962
PB - Springer
CY - Heidelberg
ER -
TY - JOUR
A1 - Bano, Dorina
A1 - Michael, Judith
A1 - Rumpe, Bernhard
A1 - Varga, Simon
A1 - Weske, Mathias
T1 - Process-aware digital twin cockpit synthesis from event logs
JF - Journal of computer languages
N2 - The engineering of digital twins and their user interaction parts with explicated processes, namely processaware digital twin cockpits (PADTCs), is challenging due to the complexity of the systems and the need for information from different disciplines within the engineering process. Therefore, it is interesting to investigate how to facilitate their engineering by using already existing data, namely event logs, and reducing the number of manual steps for their engineering. Current research lacks systematic, automated approaches to derive process-aware digital twin cockpits even though some helpful techniques already exist in the areas of process mining and software engineering. Within this paper, we present a low-code development approach that reduces the amount of hand-written code needed and uses process mining techniques to derive PADTCs. We describe what models could be derived from event log data, which generative steps are needed for the engineering of PADTCs, and how process mining could be incorporated into the resulting application. This process is evaluated using the MIMIC III dataset for the creation of a PADTC prototype for an automated hospital transportation system. This approach can be used for early prototyping of PADTCs as it needs no hand-written code in the first place, but it still allows for the iterative evolvement of the application. This empowers domain experts to create their PADTC prototypes.
KW - process-aware digital twin cockpit
KW - low-code development approaches
KW - sensor data
KW - event log
KW - process mining
KW - process-awareness
Y1 - 2022
U6 - https://doi.org/10.1016/j.cola.2022.101121
SN - 2590-1184
SN - 2665-9182
VL - 70
PB - Elsevier
CY - Amsterdam [u.a.]
ER -
TY - JOUR
A1 - Bläsius, Thomas
A1 - Freiberger, Cedric
A1 - Friedrich, Tobias
A1 - Katzmann, Maximilian
A1 - Montenegro-Retana, Felix
A1 - Thieffry, Marianne
T1 - Efficient Shortest Paths in Scale-Free Networks with Underlying Hyperbolic Geometry
JF - ACM Transactions on Algorithms
N2 - A standard approach to accelerating shortest path algorithms on networks is the bidirectional search, which explores the graph from the start and the destination, simultaneously. In practice this strategy performs particularly well on scale-free real-world networks. Such networks typically have a heterogeneous degree distribution (e.g., a power-law distribution) and high clustering (i.e., vertices with a common neighbor are likely to be connected themselves). These two properties can be obtained by assuming an underlying hyperbolic geometry.
To explain the observed behavior of the bidirectional search, we analyze its running time on hyperbolic random graphs and prove that it is (O) over tilde (n(2-1/alpha) + n(1/(2 alpha)) + delta(max)) with high probability, where alpha is an element of (1/2, 1) controls the power-law exponent of the degree distribution, and dmax is the maximum degree. This bound is sublinear, improving the obvious worst-case linear bound. Although our analysis depends on the underlying geometry, the algorithm itself is oblivious to it.
KW - Random graphs
KW - hyperbolic geometry
KW - scale-free networks
KW - bidirectional shortest path
Y1 - 2022
U6 - https://doi.org/10.1145/3516483
SN - 1549-6325
SN - 1549-6333
VL - 18
IS - 2
SP - 1
EP - 32
PB - Association for Computing Machinery
CY - New York
ER -
TY - JOUR
A1 - Bonifati, Angela
A1 - Mior, Michael J.
A1 - Naumann, Felix
A1 - Noack, Nele Sina
T1 - How inclusive are we?
BT - an analysis of gender diversity in database venues
JF - SIGMOD record / Association for Computing Machinery, Special Interest Group on Management of Data
N2 - ACM SIGMOD, VLDB and other database organizations have committed to fostering an inclusive and diverse community, as do many other scientific organizations. Recently, different measures have been taken to advance these goals, especially for underrepresented groups. One possible measure is double-blind reviewing, which aims to hide gender, ethnicity, and other properties of the authors.
We report the preliminary results of a gender diversity analysis of publications of the database community across several peer-reviewed venues, and also compare women's authorship percentages in both single-blind and double-blind venues along the years. We also obtained a cross comparison of the obtained results in data management with other relevant areas in Computer Science.
Y1 - 2022
U6 - https://doi.org/10.1145/3516431.3516438
SN - 0163-5808
SN - 1943-5835
VL - 50
IS - 4
SP - 30
EP - 35
PB - Association for Computing Machinery
CY - New York
ER -
TY - JOUR
A1 - Verweij, Marco
A1 - Ney, Steven
A1 - Thompson, Michael
T1 - Cultural Theory’s contributions to climate science
BT - reply to Hansson
JF - European journal for philosophy of science
N2 - In his article, 'Social constructionism and climate science denial', Hansson claims to present empirical evidence that the cultural theory developed by Dame Mary Douglas, Aaron Wildavsky and ourselves (among others) leads to (climate) science denial. In this reply, we show that there is no validity to these claims. First, we show that Hansson's empirical evidence that cultural theory has led to climate science denial falls apart under closer inspection. Contrary to Hansson's claims, cultural theory has made significant contributions to understanding and addressing climate change. Second, we discuss various features of Douglas' cultural theory that differentiate it from other constructivist approaches and make it compatible with the scientific method. Thus, we also demonstrate that cultural theory cannot be accused of epistemic relativism.
KW - Mary Douglas
KW - Aaron Wildavsky
KW - Cultural theory
KW - Climate change
Y1 - 2022
U6 - https://doi.org/10.1007/s13194-022-00464-y
SN - 1879-4912
SN - 1879-4920
VL - 12
IS - 2
PB - Springer
CY - Dordrecht
ER -
TY - JOUR
A1 - Doerr, Benjamin
A1 - Kötzing, Timo
T1 - Lower bounds from fitness levels made easy
JF - Algorithmica
N2 - One of the first and easy to use techniques for proving run time bounds for evolutionary algorithms is the so-called method of fitness levels by Wegener. It uses a partition of the search space into a sequence of levels which are traversed by the algorithm in increasing order, possibly skipping levels. An easy, but often strong upper bound for the run time can then be derived by adding the reciprocals of the probabilities to leave the levels (or upper bounds for these). Unfortunately, a similarly effective method for proving lower bounds has not yet been established. The strongest such method, proposed by Sudholt (2013), requires a careful choice of the viscosity parameters gamma(i), j, 0 <= i < j <= n. In this paper we present two new variants of the method, one for upper and one for lower bounds. Besides the level leaving probabilities, they only rely on the probabilities that levels are visited at all. We show that these can be computed or estimated without greater difficulties and apply our method to reprove the following known results in an easy and natural way. (i) The precise run time of the (1+1) EA on LEADINGONES. (ii) A lower bound for the run time of the (1+1) EA on ONEMAX, tight apart from an O(n) term. (iii) A lower bound for the run time of the (1+1) EA on long k-paths (which differs slightly from the previous result due to a small error in the latter). We also prove a tighter lower bound for the run time of the (1+1) EA on jump functions by showing that, regardless of the jump size, only with probability O(2(-n)) the algorithm can avoid to jump over the valley of low fitness.
KW - First hitting time
KW - Fitness level method
KW - Evolutionary computation
Y1 - 2022
U6 - https://doi.org/10.1007/s00453-022-00952-w
SN - 0178-4617
SN - 1432-0541
PB - Springer
CY - New York
ER -
TY - JOUR
A1 - Langenhan, Jennifer
A1 - Jaeger, Carsten
A1 - Baum, Katharina
A1 - Simon, Mareike
A1 - Lisec, Jan
T1 - A flexible tool to correct superimposed mass isotopologue distributions in GC-APCI-MS flux experiments
JF - Metabolites
N2 - The investigation of metabolic fluxes and metabolite distributions within cells by means of tracer molecules is a valuable tool to unravel the complexity of biological systems. Technological advances in mass spectrometry (MS) technology such as atmospheric pressure chemical ionization (APCI) coupled with high resolution (HR), not only allows for highly sensitive analyses but also broadens the usefulness of tracer-based experiments, as interesting signals can be annotated de novo when not yet present in a compound library. However, several effects in the APCI ion source, i.e., fragmentation and rearrangement, lead to superimposed mass isotopologue distributions (MID) within the mass spectra, which need to be corrected during data evaluation as they will impair enrichment calculation otherwise. Here, we present and evaluate a novel software tool to automatically perform such corrections. We discuss the different effects, explain the implemented algorithm, and show its application on several experimental datasets. This adjustable tool is available as an R package from CRAN.
KW - mass isotopologue distribution
KW - enrichment calculation
KW - flux
KW - experiments
KW - atmospheric pressure chemical ionization
KW - R package
KW - CorMID
Y1 - 2022
U6 - https://doi.org/10.3390/metabo12050408
SN - 2218-1989
VL - 12
IS - 5
PB - MDPI
CY - Basel
ER -
TY - JOUR
A1 - Sinn, Ludwig R.
A1 - Giese, Sven Hans-Joachim
A1 - Stuiver, Marchel
A1 - Rappsilber, Juri
T1 - Leveraging parameter dependencies in high-field asymmetric waveform ion-mobility spectrometry and size exclusion chromatography for proteome-wide cross-linking mass spectrometry
JF - Analytical chemistry : the authoritative voice of the analytical community
N2 - Ion-mobility spectrometry shows great promise to tackle analytically challenging research questions by adding another separation dimension to liquid chromatography-mass spectrometry.
The understanding of how analyte properties influence ion mobility has increased through recent studies, but no clear rationale for the design of customized experimental settings has emerged.
Here, we leverage machine learning to deepen our understanding of field asymmetric waveform ion-mobility spectrometry for the analysis of cross-linked peptides.
Knowing that predominantly m/z and then the size and charge state of an analyte influence the separation, we found ideal compensation voltages correlating with the size exclusion chromatography fraction number.
The effect of this relationship on the analytical depth can be substantial as exploiting it allowed us to almost double unique residue pair detections in a proteome-wide cross-linking experiment.
Other applications involving liquid- and gas-phase separation may also benefit from considering such parameter dependencies.
Y1 - 2022
U6 - https://doi.org/10.1021/acs.analchem.1c04373
SN - 0003-2700
SN - 1520-6882
VL - 94
IS - 11
SP - 4627
EP - 4634
PB - American Chemical Society
CY - Columbus, Ohio
ER -
TY - JOUR
A1 - Reimann, Max
A1 - Buchheim, Benito
A1 - Semmo, Amir
A1 - Döllner, Jürgen
A1 - Trapp, Matthias
T1 - Controlling strokes in fast neural style transfer using content transforms
JF - The Visual Computer
N2 - Fast style transfer methods have recently gained popularity in art-related applications as they make a generalized real-time stylization of images practicable. However, they are mostly limited to one-shot stylizations concerning the interactive adjustment of style elements. In particular, the expressive control over stroke sizes or stroke orientations remains an open challenge. To this end, we propose a novel stroke-adjustable fast style transfer network that enables simultaneous control over the stroke size and intensity, and allows a wider range of expressive editing than current approaches by utilizing the scale-variance of convolutional neural networks. Furthermore, we introduce a network-agnostic approach for style-element editing by applying reversible input transformations that can adjust strokes in the stylized output. At this, stroke orientations can be adjusted, and warping-based effects can be applied to stylistic elements, such as swirls or waves. To demonstrate the real-world applicability of our approach, we present StyleTune, a mobile app for interactive editing of neural style transfers at multiple levels of control. Our app allows stroke adjustments on a global and local level. It furthermore implements an on-device patch-based upsampling step that enables users to achieve results with high output fidelity and resolutions of more than 20 megapixels. Our approach allows users to art-direct their creations and achieve results that are not possible with current style transfer applications.
Y1 - 2022
U6 - https://doi.org/10.1007/s00371-022-02518-x
SN - 0178-2789
SN - 1432-2315
VL - 38
IS - 12
SP - 4019
EP - 4033
PB - Springer
CY - New York
ER -
TY - JOUR
A1 - Weinstein, Theresa Julia
A1 - Ceh, Simon Majed
A1 - Meinel, Christoph
A1 - Benedek, Mathias
T1 - What's creative about sentences?
BT - a computational approach to assessing creativity in a sentence generation task
JF - Creativity Research Journal
N2 - Evaluating creativity of verbal responses or texts is a challenging task due to psychometric issues associated with subjective ratings and the peculiarities of textual data. We explore an approach to objectively assess the creativity of responses in a sentence generation task to 1) better understand what language-related aspects are valued by human raters and 2) further advance the developments toward automating creativity evaluations. Over the course of two prior studies, participants generated 989 four-word sentences based on a four-letter prompt with the instruction to be creative. We developed an algorithm that scores each sentence on eight different metrics including 1) general word infrequency, 2) word combination infrequency, 3) context-specific word uniqueness, 4) syntax uniqueness, 5) rhyme, 6) phonetic similarity, and similarity of 7) sequence spelling and 8) semantic meaning to the cue. The text metrics were then used to explain the averaged creativity ratings of eight human raters. We found six metrics to be significantly correlated with the human ratings, explaining a total of 16% of their variance. We conclude that the creative impression of sentences is partly driven by different aspects of novelty in word choice and syntax, as well as rhythm and sound, which are amenable to objective assessment.
Y1 - 2022
U6 - https://doi.org/10.1080/10400419.2022.2124777
SN - 1040-0419
SN - 1532-6934
VL - 34
IS - 4
SP - 419
EP - 430
PB - Routledge, Taylor & Francis Group
CY - Abingdon
ER -
TY - JOUR
A1 - Roostapour, Vahid
A1 - Neumann, Aneta
A1 - Neumann, Frank
A1 - Friedrich, Tobias
T1 - Pareto optimization for subset selection with dynamic cost constraints
JF - Artificial intelligence
N2 - We consider the subset selection problem for function f with constraint bound B that changes over time. Within the area of submodular optimization, various greedy approaches are commonly used. For dynamic environments we observe that the adaptive variants of these greedy approaches are not able to maintain their approximation quality. Investigating the recently introduced POMC Pareto optimization approach, we show that this algorithm efficiently computes a phi=(alpha(f)/2)(1 - 1/e(alpha)f)-approximation, where alpha(f) is the submodularity ratio of f, for each possible constraint bound b <= B. Furthermore, we show that POMC is able to adapt its set of solutions quickly in the case that B increases. Our experimental investigations for the influence maximization in social networks show the advantage of POMC over generalized greedy algorithms. We also consider EAMC, a new evolutionary algorithm with polynomial expected time guarantee to maintain phi approximation ratio, and NSGA-II with two different population sizes as advanced multi-objective optimization algorithm, to demonstrate their challenges in optimizing the maximum coverage problem. Our empirical analysis shows that, within the same number of evaluations, POMC is able to perform as good as NSGA-II under linear constraint, while EAMC performs significantly worse than all considered algorithms in most cases.
KW - Subset selection
KW - Submodular function
KW - Multi-objective optimization
KW - Runtime analysis
Y1 - 2022
U6 - https://doi.org/10.1016/j.artint.2021.103597
SN - 0004-3702
SN - 1872-7921
VL - 302
PB - Elsevier
CY - Amsterdam
ER -
TY - GEN
A1 - Tang, Mitchell
A1 - Nakamoto, Carter H.
A1 - Stern, Ariel Dora
A1 - Mehrotra, Ateev
T1 - Trends in remote patient monitoring use in traditional medicare
T2 - JAMA internal medicine
Y1 - 2022
U6 - https://doi.org/10.1001/jamainternmed.2022.3043
SN - 2168-6106
SN - 2168-6114
VL - 182
IS - 9
SP - 1005
EP - 1006
PB - American Medical Association
CY - Chicago, Ill.
ER -
TY - JOUR
A1 - Gevay, Gabor E.
A1 - Rabl, Tilmann
A1 - Bress, Sebastian
A1 - Maclai-Tahy, Lorand
A1 - Quiane-Ruiz, Jorge-Arnulfo
A1 - Markl, Volker
T1 - Imperative or functional control flow handling
BT - why not the best of both worlds?
JF - SIGMOD record
N2 - Modern data analysis tasks often involve control flow statements, such as the iterations in PageRank and K-means. To achieve scalability, developers usually implement these tasks in distributed dataflow systems, such as Spark and Flink. Designers of such systems have to choose between providing imperative or functional control flow constructs to users. Imperative constructs are easier to use, but functional constructs are easier to compile to an efficient dataflow job. We propose Mitos, a system where control flow is both easy to use and efficient. Mitos relies on an intermediate representation based on the static single assignment form. This allows us to abstract away from specific control flow constructs and treat any imperative control flow uniformly both when building the dataflow job and when coordinating the distributed execution.
Y1 - 2022
U6 - https://doi.org/10.1145/3542700.3542715
SN - 0163-5808
SN - 1943-5835
VL - 51
IS - 1
SP - 60
EP - 67
PB - Association for Computing Machinery
CY - New York
ER -