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Validating daily social media macroscopes of emotions

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arXiv 2021年

作者： Pellert, Max Metzler, Hannah Matzenberger, Michael Garcia, David Sony Computer Science Laboratories 6 Rue Amyot Paris75005 France Institute of Interactive Systems and Data Science Graz University of Technology Inffeldgasse 16C Graz8010 Austria Complexity Science Hub Vienna Josefstädter Straße 39 Vienna1080 Austria Section for Science of Complex Systems Center for Medical Statistics Informatics and Intelligent Systems Medical University of Vienna Spitalgasse 23 Vienna1090 Austria Institute of Globally Distributed Open Research and Education Sweden Der Standard Vordere Zollamtsstraße 13 Vienna1030 Austria

Measuring sentiment in social media text has become an important practice in studying emotions at the macroscopic level. However, this approach can suffer from methodological issues like sampling biases and measurement errors. To date, it has not been validated if social media sentiment can actually measure the temporal dynamics of mood and emotions aggregated at the level of communities. We ran a large-scale survey at an online newspaper to gather daily mood self-reports from its users, and compare these with aggregated results of sentiment analysis of user discussions. We find strong correlations between text analysis results and levels of self-reported feelings, as well as between inter-day changes of both measurements. We replicate these results using sentiment data from Twitter. We show that a combination of supervised text analysis methods based on novel deep learning architectures and unsupervised dictionary-based methods have high agreement with the time series of aggregated mood measured with self-reports. Our findings indicate that macro level dynamics of feelings expressed on an online platform can be tracked with social media text, especially in situations of high mood variability. © 2021, CC BY.

关键词： Sentiment analysis

Have It Your Way: Generating Customized Log Data Sets with a Model-driven Simulation Testbed

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Have It Your Way: Generating Customized Log Data Sets with a...

IEEE International Conference on software Quality, Reliability and Security (QRS)

作者： Max Landauer Florian Skopik Markus Wurzenberger Wolfgang Hotwagner Andreas Rauber Center for Digital Safety & Security Austrian Institute of Technology Vienna Austria Institute of Information Systems Engineering Vienna University of Technology Vienna Austria

ISBN: (数字)9781728189130

ISBN: (纸本)9781728189147

Evaluations of intrusion detection systems (IDS) require log data sets collected in realistic system environments. Ex-isting testbeds therefore offer user simulations and attack scenarios that target specific use-cases. However, not only does the preparation of such testbeds require domain knowledge and time-consuming work, but also maintenance and modifications for other use-cases involve high manual efforts and repeated execution of tasks. We therefore propose to generate testbeds for IDS evaluation using strategies from model-driven engineering. In particular, our approach models system infrastructure, simulated normal behavior, and attack scenarios as testbed-independent modules. A transformation engine then automatically generates arbitrary numbers of testbeds, each with a particular set of characteristics and capable of running in parallel. Our approach greatly improves configurability and flexibility of testbeds and allows to reuse components across multiple scenarios. We use our proof-of-concept implementation to generate a labeled data set for IDS evaluation that is published with this paper.

关键词： software quality Manuals Data models Model driven engineering software reliability Security Task analysis

ARCH-COMP21 Category Report: Stochastic Models 8th

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ARCH-COMP21 Category Report: Stochastic Models

8th International Workshop on Applied Verification of Continuous and Hybrid systems, ARCH 2021

作者： Abate, Alessandro Blom, Henk Bouissou, Marc Cauchi, Nathalie Chraibi, Hassane Delicaris, Joanna Haesaert, Sofie Hartmanns, Arnd Khaled, Mahmoud Lavaei, Abolfazl Ma, Hao Mallik, Kaushik Niehage, Mathis Remke, Anne Schupp, Stefan Shmarov, Fedor Soudjani, Sadegh Thorpe, Adam Turcuman, Vlad Zuliani, Paolo University of Oxford Oxford United Kingdom Delft University of Technology Delft Netherlands France University of Münster Germany TU Eindhoven Eindhoven Netherlands University of Twente Enschede Netherlands Technical University of Munich Germany ETH Zurich Switzerland Max Planck Institute for Software Systems Germany TU Wien Vienna Austria University of Manchester Manchester United Kingdom Newcastle University Newcastle upon Tyne United Kingdom University of New Mexico United States

This report presents the results of a friendly competition for formal verification and policy synthesis of stochastic models. It also introduces new benchmarks within this category, and recommends next steps for this category towards next year’s edition of the competition. The friendly competition took place as part of the workshop Applied Verification for Continuous and Hybrid systems (ARCH) in Spring/Summer 2021. © 2021, EasyChair. All rights reserved.

关键词： Stochastic systems

Field Experiments with an Automated Utility Platform for Transportation and Work Processes

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Field Experiments with an Automated Utility Platform for Tra...

IEEE International Conference on Autonomous Robot systems and Competitions (ICARSC)

作者： Raimund Edlinger Stefan Dumberger Roman Froschauer Wolfgang Pointner Marcel Zeilinger Andreas Nü chter Smart Automation and Robotics University of Applied Sciences Upper Austria Wels Austria Assistive &#x0026 Autonomous Systems AIT &#x2013 Austrian Institute of Technology Vienna Austria Informatics VII - Robotics and Telematics Julius-Maximilians-University W&#x00FC rzburg W&#x00FC rzburg Germany

The automation of transport and work tasks in various application domains continues to be a major challenge. The proposed paper presents key technologies within a process from sensing to reasoning and includes: (i) understanding the scene and its relations through new approaches in object classification and pose estimation based on machine learning, as well as methods for reliable detection of objects and object features; (ii) reliable and safe outdoor localization and mapping based on multi-modal approaches and innovative camera-based methods. The fusion of different sensor data is used for reliable obstacle detection and collision avoidance. The investigation of suitable system architectures, data processing platforms and communication mechanisms taking into account safety requirements is a prerequisite for the operation in a safety-critical environment. The paper provides a proof of concept for an automated platform to demonstrate and evaluate application scenario provided by the Linz Airport in the form of an automated transport process for air freight between a terminal and the aircraft.

关键词： Navigation Transportation systems architecture Switches Robot sensing systems software software reliability

HybridoNet-Adapt: A Domain-Adapted Framework for Accurate Lithium-Ion Battery RUL Prediction

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arXiv 2025年

作者： Tran, Khoa Huynh, Bao Le, Tri Pham, Lam Nguyen, Vy-Rin Trinh, Hung-Cuong Anh, Duong Tran AIWARE Limited Company 17 Huynh Man Dat Street Hoa Cuong Bac Ward Hai Chau District Da Nang550000 Viet Nam AIT Austrian Institute of Technology GmbH Giefinggasse 4 Vienna1210 Austria Software Engineering Department FPT University Da Nang550000 Viet Nam Faculty of Information Technology Ton Duc Thang University Ho Chi Minh City700000 Viet Nam Laboratory of Environmental Sciences and Climate Change Institute for Computational Science and Artificial Intelligence Van Lang University Ho Chi Minh City700000 Viet Nam Faculty of Environment School of Technology Van Lang University Ho Chi Minh City700000 Viet Nam

Accurate prediction of the Remaining Useful Life (RUL) in Lithium-ion battery (LIB) health management systems is essential for ensuring operational reliability and safety. However, many existing methods assume that training and testing data follow the same distribution, limiting their ability to learn domain-invariant features and generalize effectively to unseen target domains. To approach this opportunity, we propose a novel RUL prediction framework and incorporates an domain adaptation (DA) technique. Our framework integrates a comprehensive signal preprocessing pipeline—including noise-reduction, feature extraction, and normalization—with a robust deep learning model named HybridoNet-Adapt. The model comprises a feature extraction block built from Long Short-Term Memory (LSTM), Multihead Attention, and Neural Ordinary Differential Equation (NODE) layers, followed by two predictor modules implemented using linear layers. These predictors are balanced using trainable trade-off parameters. To enhance generalization to unseen data distributions, we introduce a domain adaptation strategy inspired by the Domain-Adversarial Neural Network (DANN) framework, replacing adversarial loss with Maximum Mean Discrepancy (MMD) to learn domain-invariant features. This approach enables effective transfer learning from source to target domains using cycling data. Experimental results demonstrate that our proposed method significantly outperforms traditional machine learning models such as XGBoost and Elastic Net, as well as deep learning baselines like Dual-input DNN, in predicting RUL. These findings highlight the potential of HybridoNet-Adapt for reliable and scalable Battery Health Management (BHM). Copyright © 2025, The Authors. All rights reserved.

关键词： Lithium-ion batteries

Expert sourcing to support the identification of model elements in system descriptions 10th

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Expert sourcing to support the identification of model eleme...

10th International Conference on software Quality Days, SWQD 2018

作者： Sabou, Marta Winkler, Dietmar Petrovic, Sanja Institute of Software Technology and Interactive Systems Vienna University of Technology Vienna Austria

ISBN: (纸本)9783319714394

Context. Expert sourcing is a novel approach to support quality assurance: it relies on methods and tooling from crowdsourcing research to split model quality assurance tasks and parallelize task execution across several expert users. Typical quality assurance tasks focus on checking an inspection object, e.g., a model, towards a reference document, e.g., a requirements specification, that is considered to be correct. For example, given a text-based system description and a corresponding model such as an Extended Entity Relationship (EER) diagram, experts are guided towards inspecting the model based on so-called expected model elements (EMEs). EMEs are entities, attributes and relations that appear in text and are reflected by the corresponding model. In common inspection tasks, EMEs are not explicitly expressed but implicitly available via textual descriptions. Thus, a main improvement is to make EMEs explicit by using crowdsourcing mechanisms to drive model quality assurance among experts. Objective and Method. In this paper, we investigate the effectiveness of identifying the EMEs through expert sourcing. To that end, we perform a feasibility study in which we compare EMEs identified through expert sourcing with EMEs provided by a task owner who has a deep knowledge of the entire system specification text. Conclusions. Results of the data analysis show that the effectiveness of the crowdsourcing-style EME acquisition is influenced by the complexity of these EMEs: entity EMEs can be harvested with high recall and precision, but the lexical and semantic variations of attribute EMEs hamper their automatic aggregation and reaching consensus (these EMEs are harvested with high precisions but limited recall). Based on these lessons learned we propose a new task design for expert sourcing EMEs. © Springer International Publishing AG 2018.

关键词： Quality assurance

Assessing the integration of software agents and industrial automation systems with ISO/IEC 25010

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arXiv 2021年

作者： Karnouskos, Stamatis Sinha, Roopak Leitão, Paulo Ribeiro, Luis Strasser, Thomas I. SAP Walldorf Germany IT & Software Engineering Auckland University of Technology New Zealand Instituto Politécnico de Bragança Campus de Santa Apolónia Bragança5300-253 Portugal Linköping University LinköpingSE-58 183 Sweden Center for Energy AIT Austrian Institute of Technology Institute of Mechanics and Mechatronics Vienna University of Technology Vienna Austria

Agent-technologies have been used for higher-level decision making in addition to carrying out lower-level automation and control functions in industrial systems. Recent research has identified a number of architectural patterns for the use of agents in industrial automation systems but these practices vary in several ways, including how closely agents are coupled with physical systems and their control functions. Such practices may play a pivotal role in the Cyber-Physical System integration and interaction. Hence, there is a clear need for a common set of criteria for assessing available practices and identifying a best- fit practice for a given industrial use case. Unfortunately, no such common criteria exist currently. This work proposes an assessment criteria approach as well as a methodology to enable the use case based selection of a best practice for integrating agents and industrial systems. The software product quality model proposed by the ISO/IEC 25010 family of standards is used as starting point and is put in the industrial automation context. Subsequently, the proposed methodology is applied, and a survey of experts in the domain is carried out, in order to reveal some insights on the key characteristics of the subject matter. Copyright © 2021, The Authors. All rights reserved.

关键词： software agents

The applicability of ISO/IEC 25023 measures to the integration of agents and automation systems

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arXiv 2021年

The integration of industrial automation systems and software agents has been practiced for many years. However, such an integration is usually done by experts and there is no consistent way to assess these practices and to optimally select one for a specific system. Standards such as the ISO/IEC 25023 propose measures that could be used to obtain a quantification on the characteristics of such integration. In this work, the suitability of these characteristics and their proposed calculation for assessing the connection of industrial automation systems with software agents is discussed. Results show that although most of the measures are relevant for the integration of agents and industrial automation systems, some are not relevant in this context. Additionally, it was noticed that some measures, especially those of a more technical nature, were either very difficult to computed in the automation system integration, or did not provide sufficient guidance to identify a practice to be used. Copyright © 2021, The Authors. All rights reserved.

关键词： software agents

Fragile, yet resilient: Adaptive decline in a collaboration network of firms

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arXiv 2020年

作者： Schweitzer, Frank Casiraghi, Giona Tomasello, Mario V. Garcia, David ETH Zurich Switzerland Complexity Science Hub Vienna Austria Institute of Interactive Systems and Data Science Graz University of Technology Austria

The dynamics of collaboration networks of firms follow a life-cycle of growth and decline. That does not imply they also become less resilient. Instead, declining collaboration networks may still have the ability to mitigate shocks from firms leaving, and to recover from these losses by adapting to new partners. To demonstrate this, we analyze 21.500 R&D collaborations of 14.500 firms in six different industrial sectors over 25 years. We calculate time-dependent probabilities of firms leaving the network and simulate drop-out cascades, to determine the expected dynamics of decline. We then show that deviations from these expectations result from the adaptivity of the network, which mitigates the decline. These deviations can be used as a measure of network resilience. Copyright © 2020, The Authors. All rights reserved.

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