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See detailPRINS: Scalable Model Inference for Component-based System Logs
Shin, Donghwan UL; Bianculli, Domenico UL; Briand, Lionel UL

in Empirical Software Engineering (2022)

Behavioral software models play a key role in many software engineering tasks; unfortunately, these models either are not available during software development or, if available, quickly become outdated as ... [more ▼]

Behavioral software models play a key role in many software engineering tasks; unfortunately, these models either are not available during software development or, if available, quickly become outdated as implementations evolve. Model inference techniques have been proposed as a viable solution to extract finite state models from execution logs. However, existing techniques do not scale well when processing very large logs that can be commonly found in practice. In this paper, we address the scalability problem of inferring the model of a component-based system from large system logs, without requiring any extra information. Our model inference technique, called PRINS, follows a divide-and-conquer approach. The idea is to first infer a model of each system component from the corresponding logs; then, the individual component models are merged together taking into account the flow of events across components, as reflected in the logs. We evaluated PRINS in terms of scalability and accuracy, using nine datasets composed of logs extracted from publicly available benchmarks and a personal computer running desktop business applications. The results show that PRINS can process large logs much faster than a publicly available and well-known state-of-the-art tool, without significantly compromising the accuracy of inferred models. [less ▲]

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See detailSustainability and Circular Economy in Learning Factories – Case Studies
Weyand, Astrid; Thiede, Sebastian; Mangers, Jeff UL et al

in SSRN (2022, April 11)

Since the mitigation of climate change is one of the biggest challenges to face on a global scale, the topic has become more relevant also in industrial context. Learning factories have proven to be ... [more ▼]

Since the mitigation of climate change is one of the biggest challenges to face on a global scale, the topic has become more relevant also in industrial context. Learning factories have proven to be suitable environments to address and convey competencies to tackle industrial challenges in an interactive way. Hence, several learning factories are already dealing with sustainability topics in various use cases. This paper strives to present a state of the art of sustainability and circular economy in learning factories. Therefore, a classification framework is developed based on the state of the art of several learning factories and existing literature regarding the topic. This framework is then used to systematically describe the different activities regarding sustainability and circular economy that are currently ongoing in learning factories worldwide. This can be used to get an idea about the different aspects of the topic and how to address them, but furthermore also offers assistance to identify “blind spots” which could and should be addressed in learning factories in the future. [less ▲]

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See detailUnsichtbares sichtbar machen
Scuto, Denis UL; Harnoncourt, Julia UL

Article for general public (2022)

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See detailCreating positive learning experiences with technology: A field study on the effects of user experience for digital concept mapping
Rohles, Björn UL; Backes, Susanne UL; Fischbach, Antoine UL et al

in Heliyon (2022), 8(4),

Learning and assessment are increasingly mediated by digital technologies. Thus, learners’ experiences with these digital technologies are growing in importance, as they might affect learning and ... [more ▼]

Learning and assessment are increasingly mediated by digital technologies. Thus, learners’ experiences with these digital technologies are growing in importance, as they might affect learning and assessment. The present paper explores the impact of user experience on digital concept mapping. It builds on user experience theory to explain variance in the intention to use digital concept mapping tools and in concept map-based assessment scores. Furthermore, it identifies fulfillment of psychological needs as an important driver of positive experiences. In a field study in three schools and a university (N = 71), we tested two concept mapping prototypes on computers and tablets. We found that user experience is a significant factor explaining variance in intention to use. User experience also explained variance in three out of four concept mapping scores on tablets, potentially related to the lower pragmatic quality of the tablet prototypes. Fulfillment of psychological needs strongly affected perceptions of different qualities of user experience with digital concept mapping. These results indicate that user experience needs to be considered in digital concept mapping to provide a positive and successful environment for learning and assessment. Finally, we discuss implications for designers of digital learning and assessment tools. [less ▲]

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See detailHistoricising online virality
Schafer, Valerie UL

Presentation (2022, April 08)

This presentation aims to questions the methodologies and challenges related to an historical study of European online virality.

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See detailReplicating the Kinora: 3D Modelling and Printing as Heuristics in Digital Media History
Wolf, Claude UL; van der Heijden, Tim

Computer development (2022)

The Kinora replica 3D model was produced in the context of the project "Doing Experimental Media Archaeology: Practice and Theory (DEMA)", funded by the Fonds National de la Recherche, Luxembourg (FNR ... [more ▼]

The Kinora replica 3D model was produced in the context of the project "Doing Experimental Media Archaeology: Practice and Theory (DEMA)", funded by the Fonds National de la Recherche, Luxembourg (FNR) (C18/SC/12703137): https://dema.uni.lu/. The Kinora replica project was the result of a collaboration between the Luxembourg Centre for Contemporary and Digital History (C2DH) and the Department of Engineering (DoE) of the University of Luxembourg. See for more information the article "Replicating the Kinora: 3D modelling and printing as heuristics in digital media history", published in the Journal of Digital History: https://journalofdigitalhistory.org/en/article/33pRxE2dtUHP [less ▲]

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See detailSEMKIS: A CONTRIBUTION TO SOFTWARE ENGINEERING METHODOLOGIES FOR NEURAL NETWORK DEVELOPMENT
Jahic, Benjamin UL

Doctoral thesis (2022)

Today, there is a high demand for neural network-based software systems supporting humans during their daily activities. Neural networks are computer programs that simulate the behaviour of simplified ... [more ▼]

Today, there is a high demand for neural network-based software systems supporting humans during their daily activities. Neural networks are computer programs that simulate the behaviour of simplified human brains. These neural networks can be deployed on various devices e.g. cars, phones, medical devices...) in many domains (e.g. automotive industry, medicine...). To meet the high demand, software engineers require methods and tools to engineer these software systems for their customers. Neural networks acquire their recognition skills e.g. recognising voice, image content...) from large datasets during a training process. Therefore, neural network engineering (NNE) shall not be only about designing and implementing neural network models, but also about dataset engineering (DSE). In the literature, there are no software engineering methodologies supporting DSE with precise dataset selection criteria for improving neural networks. Most traditional approaches focus only on improving the neural network’s architecture or follow crafted approaches based on augmenting datasets with randomly gathered data. Moreover, they do not consider a comparative evaluation of the neural network’s recognition skills and customer’s requirements for building appropriate datasets. In this thesis, we introduce a software engineering methodology (called SEMKIS) supported by a tool for engineering datasets with precise data selection criteria to improve neural networks. Our method considers mainly the improvement of neural networks through augmenting datasets with synthetic data. SEMKIS has been designed as a rigorous iterative process for guiding software engineers during their neural network-based projects. The SEMKIS process is composed of many activities covering different development phases: requirements’ specification; dataset and neural network engineering; recognition skills specification; dataset augmentation with synthetized data. We introduce the notion of key-properties, used all along the process in cooperation with a customer, to describe the recognition skills. We define a domain-specific language (called SEMKIS-DSL) for the specification of the requirements and recognition skills. The SEMKIS-DSL grammar has been designed to support a comparative evaluation of the customer’s requirements with the key-properties. We define a method for interpreting the specification and defining a dataset augmentation. Lastly, we apply the SEMKIS process to a complete case study on the recognition of a meter counter. Our experiment shows a successful application of our process in a concrete example. [less ▲]

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See detailCybermemorials: Remembrance and Places of Memory in the Digital Age
Camarda, Sandra UL

in Noiret, Serge; Tebeau, Mark; Zaagsma, Gerben (Eds.) Handbook of Digital Public History (2022)

Detailed reference viewed: 48 (1 UL)
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See detailLeveraging Graph Machine Learning for Social Network Analysis
Zhong, Zhiqiang UL

Postdoctoral thesis (2022)

As a ubiquitous complex system in quotidian life around everyone, online social networks (OSNs) provide a rich source of information about billions of users worldwide. To some extent, OSNs have mirrored ... [more ▼]

As a ubiquitous complex system in quotidian life around everyone, online social networks (OSNs) provide a rich source of information about billions of users worldwide. To some extent, OSNs have mirrored our real society: people perform a multitude of different activities in OSNs as they do in the offline world, such as establishing social relations, sharing life moments, and expressing opinions about various topics. Therefore, understanding OSNs is of immense importance. One key characteristic of human social behaviour in OSNs is their inter-relational nature, which can be represented as graphs. Due to sparsity and complex structure, analysing these graphs is quite challenging and expensive. Over the past several decades, many expert-designed approaches to graphs have been proposed with elegant theoretical properties and successfully addressed numerous practical problems. Nevertheless, most of them are either not data-driven or do not benefit from the rapidly growing scale of data. Recently, in the light of remarkable achievements of artificial intelligence, especially deep neural networks techniques, graph machine learning (GML) has emerged to provide us with novel perspectives to understanding and analysing graphs. However, the current efforts of GML are relatively immature and lack attention to specific scenarios and characteristics of OSNs. Based on the pros and cons of GML, this thesis discusses several aspects of how to build advanced approaches to better simplify and ameliorate OSN analytic tasks. Specifically: 1) Overcoming flat message-passing graph neural networks. One of the most widely pursued branches in GML research, graph neural networks (GNNs), follows a similar flat message-passing principle for representation learning. Precisely, information is iteratively passed between adjacent nodes along observed edges via non-linear transformation and aggregation functions. Its effectiveness has been widely proved; however, two limitations need to be tackled: (i) they are costly in encoding long-range information spanning the graph structure; (ii) they are failing to encode features in the high-order neighbourhood in the graphs as they only perform information aggregation across the observed edges in the original graph. To fill up the gap, we propose a novel hierarchical message-passing framework to facilitate the existing GNN mechanism. Following this idea, we design two practical implementations, i.e., HC-GNN and AdamGNN, to demonstrate the framework's superiority. 2) Extending graph machine learning to heterophilous graphs. The existing GML approaches implicitly hold a homophily assumption that nodes of the same class tend to be connected. However, previous expert studies have shown the enormous importance of addressing the heterophily scenario, where ``opposites attract'', is essential for network analysis and fairness study. We demonstrate the possibility of extending GML to heterophilous graphs by simplifying supervised node classification models on heterophilous graphs (CLP) and designing an unsupervised heterophilous graph representation learning model (Selene). 3) Online social network analysis with graph machine learning. As GML approaches have demonstrated significant effectiveness over general graph analytic tasks, we perform two practical OSN analysis projects to illustrate the possibility of employing GML in practice. Specifically, we propose a semantic image graph embedding (SiGraph) to improve OSN image recognition task with the associated hashtags semantics and a simple GNN-based neural link prediction framework (NeuLP) to boost the performance with tiny change. Keywords: Graph machine learning, Social network analysis, Graph neural networks, Hierarchical structure, Homophily/Heterophily graphs, Link prediction, Online image content understanding. [less ▲]

Detailed reference viewed: 63 (5 UL)
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See detailSocial Media: Snapshots in Public History
Armaselu, Florentina UL

in Zaagsma, Gerben; Noiret, Serge; Tebeau, Mark (Eds.) Handbook of Digital Public History (2022)

This chapter provides an overview of how social media foster the application of public history and communication with the public, and what types of institutions, projects, and communities are involved in ... [more ▼]

This chapter provides an overview of how social media foster the application of public history and communication with the public, and what types of institutions, projects, and communities are involved in the process. Without claiming to be exhaustive or referring to a representative selection, the study is based on an exploration of seventy-three public history websites and the methods they use to engage audiences via social media [less ▲]

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See detailARGUMENT MINING AND ITS APPLICATIONS IN POLITICAL DEBATES
Haddadan, Shohreh UL

Doctoral thesis (2022)

Presidential debates are significant moments in the history of presidential campaigns. In these debates, candidates are challenged to discuss the main contemporary and historical issues in the country and ... [more ▼]

Presidential debates are significant moments in the history of presidential campaigns. In these debates, candidates are challenged to discuss the main contemporary and historical issues in the country and attempt to persuade the voters to their benefit. These debates offer a legitimate ground for argumentative analysis to investigate political discourse argument structure and strategy. The recent advances in machine learning and Natural Language Processing (NLP) algorithms with the rise of deep learning have revolutionized many natural language applications, and argument analysis from textual resources is no exception. This dissertation targets argument mining from political debates data, a platform rifled with the arguments put forward by politicians to convince a general public in voting for them and discourage them from being appealed by the other candidates. The main contributions of the thesis are: i) Creation, release and reliability assessment of a valuable resource for argumentation research. ii) Implementation of a complete argument mining pipeline applying cutting-edge technologies in NLP research. iii) Launching of a demo tool for argumentative analysis of political debates. The original dataset is composed of the transcripts of 41 presidential election debates in the U.S. from 1960 to 2016. Beside argument extraction from political debates, this research also aims at investigating the practical applications of argument structure extraction, such as fallacious argument classification and argument retrieval. In order to apply supervised machine learning and NLP methods to the data, an excessive annotation study has been conducted on the data and led to the creation of a unique dataset with argument structures composed of argument components (i.e., claim and premise) and argument relations (i.e., support and attack). This dataset includes also another annotation layer with six fallacious argument categories and 14 sub-categories annotated on the debates. The final dataset is annotated with 32,296 argument components (i.e., 16,982 claims and 15,314 premises) and 25,012 relations (i.e., 3,723 attacks and 21,289 supports), and 1628 fallacious arguments. As the methodological approach, a complete argument mining pipeline is designed and implemented, composed of the two main stages of argument component detection and argument relation prediction. Each stage takes advantage of various NLP models outperforming standard baselines in the area, with an average F-score of 0.63 for argument components classification and 0.68 for argument relation classification. Additionally, DISPUTool, an argumentative analysis online tool, is developed as proof-of-concept. DISPUTool incorporates two main functionalities. Firstly, it provides the possibility of exploring the arguments which exist in the dataset. And secondly, it allows for extracting arguments from text segments inserted by the user leveraging the embedded trained model. [less ▲]

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See detailExecutive functions in birds
Bobrowicz, Katarzyna UL; Greiff, Samuel UL

in Birds (2022)

Executive functions comprise of top-down cognitive processes that exert control over information processing, from acquiring information to issuing a behavioral response. These cogni- tive processes of ... [more ▼]

Executive functions comprise of top-down cognitive processes that exert control over information processing, from acquiring information to issuing a behavioral response. These cogni- tive processes of inhibition, working memory, and cognitive flexibility underpin complex cognitive skills, such as episodic memory and planning, which have been repeatedly investigated in several bird species in recent decades. Until recently, avian executive functions were studied in relatively few bird species but have gained traction in comparative cognitive research following MacLean and colleagues’ large-scale study from 2014. Therefore, in this review paper, the relevant previous findings are collected and organized to facilitate further investigations of these core cognitive processes in birds. This review can assist in integrating findings from avian and mammalian cognitive research and further the current understanding of executive functions’ significance and evolution. [less ▲]

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See detailGeneral Principles of Procedural Justice
Demkova, Simona UL; Hofmann, Herwig UL

in Ziegler, Katja S.; Jennings, Sir Robert; Neuvonen, Päivi J. (Eds.) et al Research Handbook on General Principles in EU Law: Constructing Legal Orders in Europe (2022)

This chapter addresses general principles of EU law concerning procedural justice. It does so using two sets of procedural rights: first, the right to good administration, and, second, the right to an ... [more ▼]

This chapter addresses general principles of EU law concerning procedural justice. It does so using two sets of procedural rights: first, the right to good administration, and, second, the right to an effective remedy. These procedural rights are central to ensuring the rule of law in the EU legal system and the accountability of the exercise of public functions in the EU. General principles of EU law within this chapter are understood as principles of constitutional character applicable throughout Union policies. In addition, many specific EU policies are governed by principles, which although general in nature, are applicable only to a specific policy sector. The working definition within this chapter is that only the former are general principles of EU law and not the latter, which are merely ‘principles’. This chapter traces the development and role of procedural principles and rights in the EU in very broad strokes. It does so in three steps: the chapter starts by briefly outlining the scope of application of the procedural general principles of EU law to sketch the depth and breadth of rights protected in this context (Section II). It then undertakes a quantitative assessment of references to procedural rights in the case law of the Court of Justice of the EU (CJEU) (Section III). The chapter finally concludes by discussing some possible explanations for the rise of procedural rights in EU law as general principles of procedural justice. We discuss how some of the difficulties arising from the existing situation can be remedied by the introduction of an EU regulation on administrative procedures (Section IV). [less ▲]

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See detailStudent profiles of self-concept and interest in four domains: A latent transition analysis
Franzen, Patrick UL; Arens, A. Katrin; Greiff, Samuel UL et al

in Learning and Individual Differences (2022), 95

Dimensional comparisons lead to contrast effects between academic self-concepts, implying that students view themselves as a math-type or a verbal-type. This study examined the short-term stability of ... [more ▼]

Dimensional comparisons lead to contrast effects between academic self-concepts, implying that students view themselves as a math-type or a verbal-type. This study examined the short-term stability of these types and their generalizability to academic interest. N = 382 students completed questionnaires on self-concept and interest in math, physics, German, and English at two measurement waves over five weeks. Latent transition analyses were conducted with self-concepts and interests as indicators, revealing four profiles for both constructs. For self-concept a math + high profile, verbal + high profile, verbal + low profile and generally-moderate profile were found. For interest a math profile, verbal profile, generally-high profile, and generally-low profile were found. These profiles indicated that the formation of domain-specific self-concept and interest differs between groups of students. The profiles were stable across measurement waves. Relations to school grades and gender matched theoretical assumptions. [less ▲]

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See detailDigital Public History in the United States
Cauvin, Thomas UL

in Tebeau, Mark; Noiret, Serge; Zaagsma, Gerben (Eds.) Handbook of Digital Public History (2022)

Digital history goes, by definition, beyond national frontiers, but can one decipher national specificities in its practices and projects? This chapter explores the birth, development, and ... [more ▼]

Digital history goes, by definition, beyond national frontiers, but can one decipher national specificities in its practices and projects? This chapter explores the birth, development, and institutionalization of digital public history in the United States. Issued from a strong network of digital history practitioners, the success of digital public history in the United States stemmed from its connection with pre-existing public history academic centers and projects. Through projects like the Valley of the Shadow or, later, the 9/11 Digital Archives, digital historians re-imagined the concept of authority and relations with the public. The Center for History and New Media was created by Roy Rosenzweig in 1994 and rapidly became one of the main actors in the move from digital to digital public history. Finally, the chapter explores the future of digital public history in the United States, its institutionalization as a discipline, and its increased focus on user-generated projects. [less ▲]

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See detailDigital Personal Memories: The Archiving of the Self and Public History
Schafer, Valerie UL

in Noiret, Serge; Zaagsma, Gerben; Tebeau, Mark (Eds.) Handbook of Digital Public History (2022)

By providing a facilitated access to data storage, digital technologies seem to make expression and preservation of the self more straightforward. They reconfigure the means and forms of access to data ... [more ▼]

By providing a facilitated access to data storage, digital technologies seem to make expression and preservation of the self more straightforward. They reconfigure the means and forms of access to data, thus also affecting the relationships and participation of individuals in heritagization and history, and potentially impacting historians. This renews questions that scholars already know well, such as the place of memories in the making of history, and that of self-narratives. Examining how “ordinary voices” can/could archive digital/digitized data and documents, this chapter aims at investigating this increased interest in preserving the self and memories, the heritagization of these data, and finally the role played by user-generated contributions in Digital Public History projects and in historical research in general. [less ▲]

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See detailAnalyse des Séries Temporelles
Bourbonnais, Régis; Terraza, Virginie UL

Book published by Dunod (2022)

Detailed reference viewed: 69 (2 UL)