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International Conference on Acoustics, Speech, and Signal Processing (ICASSP)

作者： Ferdinand Jost Vassillen Chizhov Joachim Weickert Mathematical Image Analysis Group Faculty of Mathematics and Computer Science Campus E1.7 Saarland University Saarbrücken Germany

Inpainting-based image compression is a promising alternative to classical transform-based lossy codecs. Typically it stores a carefully selected subset of all pixel locations and their colour values. In the decoding phase the missing information is reconstructed by an inpainting process such as homogeneous diffusion inpainting. Optimising the stored data is the key for achieving good performance. A few heuristic approaches also advocate alternative feature types such as derivative data and construct dedicated inpainting concepts. However, one still lacks a general approach that allows to optimise and inpaint the data simultaneously w.r.t. a collection of different feature types, their locations, and their values. Our paper closes this gap. We introduce a generalised inpainting process that can handle arbitrary features which can be expressed as linear equality constraints. This includes e.g. colour values and derivatives of any order. We propose a fully automatic algorithm that aims at finding the optimal features from a given collection as well as their locations and their function values within a specified total feature density. Its performance is demonstrated with a novel set of features that also includes local averages. Our experiments show that it clearly outperforms the popular inpainting with optimised colour data with the same density.

关键词： Image coding Codecs Image color analysis Signal processing algorithms Signal processing Image representation Acoustics

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Process Mining and Perceived Privacy Violations: A Pilot-Study 25

Process Mining and Perceived Privacy Violations: A Pilot-Stu...

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25th International Conference on Enterprise Information Systems, ICEIS 2023

作者： Zuidema-Tempel, Evelyn Bukhsh, Faiza Allah Effing, Robin van Hillegersberg, Jos Research Group Digital Intelligence & Business Saxion University of Applied Sciences M. H. Tromplaan 28 Enschede Netherlands Faculty of Electrical Engineering Mathematics and Computer Science University of Twente Drienerlolaan 5 Enschede Netherlands Faculty of Behavioural Management and Social Sciences University of Twente Drienerlolaan 5 Enschede Netherlands

ISBN: (纸本)9789897586484

Despite the existence of various methods and abstraction techniques to reduce the privacy risk of process models generated by process mining algorithms, it is unclear how process mining stakeholders perceive privacy violations. In this pilot-study various process model visualisations were shown to 6 stakeholders of a travel expense claim process. While changing the abstraction levels of these visualisations, the stakeholders were asked whether they perceived a violation of their privacy. The results show that there are differences in how individual stakeholders perceive privacy violations of process models generated via process mining algorithms. Results differ per type of visualization, type of privacy risk reducing methods, changes of abstraction level and stakeholder role. To reduce the privacy risk, the interviewees suggested to include an authorization table in the process mining tool, communicate the goal of the analysis with all stakeholders, and validate the analysis with a privacy officer. It is suggested that future research focuses on discussing and validating process visualisations and privacy risk reducing methods and techniques with various process mining stakeholders in organisations. This is expected to reduce perceived violations and prevents developing techniques that are aimed at reducing privacy risk but are not considered as such by stakeholders. Copyright © 2023 by SCITEPRESS – science and Technology Publications, Lda. Under CC license (CC BY-NC-ND 4.0)

关键词： Visualization

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Co-Designing a Multidomain Digital Toolkit to Support Cognitive Health in the Aging Dutch Population: Schouderklopje 13

Co-Designing a Multidomain Digital Toolkit to Support Cognit...

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13th International Workshop on Behavior Change Support Systems, BCSS 2025

作者： Sharma, Nikita Muijzer, Frodo Ludden, G.D.S. Group Faculty of Engineering Technology University of Twente Drienerlolaan 5 Enschede7522 NB Netherlands Faculty of Electrical Engineering Mathematics and Computer Science University of Twente Drienerlolaan 5 Enschede7522 NB Netherlands

The increasing prevalence of cognitive decline among older adults, coupled with the limited availability of accessible treatments, underscores the need for self-managed digital interventions to help mitigate the risk factors associated with cognitive decline. In that regard, this study explores the perceived challenges, motivations, needs, and key design features to inform the development of Schouderklopje, a user-centered, self-managed multidomain digital toolkit, from the perspective of domain experts. Challenges such as evolving and dynamic personal circumstances, limited awareness of brain health, and a lack of resources or support after the evaluation phase can affect the adoption of Schouderklopje. The motivation to adopt such lifestyle interventions was from a desire to improve overall health and social contribution. Furthermore, to ensure the toolkit is both self-managed and user-centered, importance of incorporating features supporting autonomy, personalization, education, skill development, and trustworthiness was noted. © 2025 Copyright for this paper by its authors.

关键词： User centered design

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TopoMortar: A dataset to evaluate image segmentation methods focused on topology accuracy

arXiv

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arXiv 2025年

作者： Valverde, Juan Miguel Koga, Motoya Otsuka, Nijihiko Dahl, Anders Bjorholm Department of Applied Mathematics and Computer Science Technical University of Denmark Denmark A.I. Virtanen Institute University of Eastern Finland Finland Department of Architecture Faculty of Engineering Sojo University Japan

We present TopoMortar, a brick wall dataset that is the first dataset specifically designed to evaluate topology-focused image segmentation methods, such as topology loss functions. TopoMortar enables to investigate in two ways whether methods incorporate prior topological knowledge. First, by eliminating challenges seen in real-world data, such as small training set, noisy labels, and out-of-distribution test-set images, that, as we show, impact the effectiveness of topology loss functions. Second, by allowing to assess in the same dataset (TopoMortar) topology accuracy across dataset challenges, isolating dataset-related effects from the effect of incorporating prior topological knowledge. In these two experiments, it is deliberately difficult to improve topology accuracy without actually leveraging topology information, thus, permitting to attribute an improvement in topology accuracy to the incorporation of prior topological knowledge. To this end, TopoMortar includes three types of labels (accurate, pseudo-labels, noisy labels), two fixed training sets (large and small), and in-distribution and out-of-distribution test-set images. We compared eight loss functions on TopoMortar, and we found that clDice generally achieved the most topologically accurate segmentations, Skeleton Recall loss performed best particularly with noisy labels, and the relative advantageousness of the other loss functions depended on the experimental setting. Additionally, we show that simple methods, such as data augmentation and self-distillation, can elevate Cross entropy Dice loss to surpass most topology loss functions, and that those simple methods can enhance topology loss functions as well. clDice and Skeleton Recall loss, both skeletonization-based loss functions, were also the fastest to train, making this type of loss function a promising research direction. TopoMortar and our code can be found at https://***/jmlipman/TopoMortar. © 2025, CC BY.

关键词： Musculoskeletal system

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The Societal Impact of a Virtual Companionship Programme for People with Chronic Obstructive Pulmonary Disease

SSRN

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SSRN 2023年

作者： Jansen-Kosterink, Stephanie M. Hurmuz, Marian Z.M. Roessingh Research and Development Enschede Netherlands University of Twente Faculty of Electrical Engineering Mathematics and Computer Science Enschede Netherlands eHealth Group

Introduction: The Social Return on Investment, or SROI methodology, is an alternative to traditional economic evaluation methodologies and is suitable to assess the societal impact of Digital Health Technologies, even in an early stage of development. Our aim is to present the SROI methodology and to assess the societal impact (forecast) of a Virtual Companionship Programme developed in the European RE-SAMPLE project for people suffering from Chronic Obstructive Pulmonary *** and methods: To assess the societal impact of the RE-SAMPLE Virtual Companionship Programme, the principles and phases of the SROI methodology are followed. The SROI process leads to two clear products: an impact map and an SROI ratio (benchmark).Results: Based on the final impact map, established together with consortium partners and a group from the Dutch pilot site, we were able to calculate the forecast SROI of the RE-SAMPLE Virtual Companionship Programme. The total input of this SROI is € 622k and the total outcome is € 746k, resulting in an SROI ratio of ***: The RE-SAMPLE Virtual Companionship Programme forecast SROI demonstrates what alternations are necessary to increase the societal impact to a more acceptable level, such as including more participants or lowering the costs for the hospital. Given our experience, we are enthusiastic about this pragmatic methodology and its potential to assess the social impact of Digital Health Technologies, due toits multi stakeholder perspective and practicality. It is hoped this paper will encourage other academics to use this methodology to assess the societal impact of Digital Health Technologies and to publish their work. © 2023, The Authors. All rights reserved.

关键词： Economic and social effects

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On the Additional Properties of Fuzzy Polynomial Implications of Degree 4 19th

On the Additional Properties of Fuzzy Polynomial Implication...

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19th International Conference on Information Processing and Management of Uncertainty in Knowledge-Based Systems, IPMU 2022

作者： Baczyński, Michal Fernandez-Peralta, Raquel Massanet, Sebastia Mir, Arnau Riera, Juan Vicente Faculty of Science and Technology University of Silesia in Katowice Bankowa 14 Katowice40-007 Poland Research Group Department of Mathematics and Computer Science University of the Balearic Islands Balearic Islands Palma07122 Spain Palma07010 Spain

ISBN: (纸本)9783031089701

It is well known that fuzzy implication functions have a very flexible definition that encompasses lots of different potential families. Therefore, the additional properties that the family members fulfill define the behavior these operators will have when modeling fuzzy conditionals or applied to any other application. In this way, in this paper, we study the additional properties of fuzzy polynomial implications of degree 4, a recent family of fuzzy implications which has been recently introduced as a family whose members have a simple expression, appealing for applied researchers. It is proved that members of this family fulfill some of the additional essential properties of fuzzy implication functions. © 2022, Springer Nature Switzerland AG.

关键词： Polynomials

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ReGammend: A method for personalized recommendation of gamification designs 6

ReGammend: A method for personalized recommendation of gamif...

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6th International GamiFIN Conference, GamiFIN 2022

作者： Vasconcelos, Gabriel Oliveira, Wilk Santos, Ana Cláudia Guimarães Hamari, Juho Institute of Mathematics and Computer Science University of São Paulo São Paulo São Carlos Brazil Gamification Group Faculty of Information Technology and Communication Sciences Tampere University Tampere Finland

Gamification personalization has been increasingly investigated as an avenue to improve the effects of gamification. While currently, empirical data exist to start making evidence-based gamification design, current guidelines and methods to bridge the gap of evidence and design is lacking. To start facing this challenge, we outline a point of departure proposing the recommendation system ReGammend (recommendation system for gamification designs). The system tailor gamification design based on users’ traits, contextual factors, goals, and other relevant moderating factors. The recommendation system uses information from the previous literature to recommend gamification designs with multiple game elements aiming to positively affect the positive outcomes stemming from gamification. The proposed system contributes to researchers and practitioners, providing a practical way to personalize gamification designs. © 2022 Copyright for this paper by its authors. Use permitted under Creative Commons License Attribution 4.0 International (CC BY 4.0).

关键词： Gamification design recommendation system user experience user modeling user-centered design

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Implementation of a Geographical Information System (GIS) for E-commerce 4th

Implementation of a Geographical Information System (GIS) fo...

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4th Doctoral Symposium on Computational Intelligence, DoSCI 2023

作者： Mohamed, Shili Sethom, Kaouthar Obaid, Ahmed J. Alkhafaji, Mohammed Ayad Mohsen, Karrar Shareef Innov’COM at Sup’Com Laboratory University of Carthage Carthage Tunisia Faculty of Computer Science and Mathematics University of Kufa Kufa Iraq College of Engineering Technology National University of Science and Technology Dhi Qar Iraq Information and Communication Technology Research Group Scientific Research Center Al-Ayen University Thi-Qar Iraq

ISBN: (纸本)9789819937158

Nowadays Geographic information systems (GIS) have developed quickly in recent years and are now utilized in a wide range of industries, including e-health, agriculture, and more. However, compared to other industries, the application of GIS in electronic commerce lags far behind. This paper consists of a web GIS application that aims to help businesses reduce driving time and costs by generating an optimal route between the delivery drivers and the customer’s locations. Using the programmable APIs provided by Google maps, we built an online shopping system with map features to research the potential of GIS in online commerce. The system incorporates Google maps into the system website using the Google maps API and adheres to the three-tier architectural paradigm. The geographical data is based on Google maps data, and the system data is stored in a MySQL database. The system MySQL database and the spatial data from Google maps are connected by latitude and longitude. These can drastically reduce the work and cost of development while simultaneously greatly increasing the system's extensibility. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2023.

关键词： Information systems

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Comparison Model for Forecasting the Total Population in Bangkok 9

Comparison Model for Forecasting the Total Population in Ban...

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Joint 9th International Conference on Digital Arts, Media and Technology with 7th ECTI Northern Section Conference on Electrical, Electronics, computer and Telecommunications Engineering, ECTI DAMT and NCON 2024

作者： Tipwong, Nattanicha Jitpattanakul, Anuchit Phaphan, Wikanda Nontapa, Chalermrat Mekruksavanich, Sakorn King Mongkut's University of Technology North Bangkok Faculty of Applied Science Department of Applied Statistics Bangkok10800 Thailand King Mongkut's University of Technology North Bangkok Faculty of Applied Science Department of Mathematics Bangkok10800 Thailand Intelligent and Nonlinear Dynamic Innovations Research Center Thailand Chiang Mai University Faculty of Science Department of Statistics Chiang Mai50200 Thailand Research Group in Statistical Learning and Inference Thailand University of Phayao School of Information and Communication Department of Computer Engineering Phayao56000 Thailand

ISBN: (纸本)9798350318241

The primary aim of this article is to investigate, contrast, and formulate a time series model to predict Bangkok's overall population. In this study, we intend to propose a hybrid model that combines the Autoregressive Moving Integrated Average (ARIMA) model and machine learning techniques, utilizing a Multilayer Perceptron (MLP). Our data source comprises monthly data from 2002 to 2022, totaling 252 data points, obtained from the official registration statistics system of the Registration Administration Office, Department of Provincial Administration. This dataset has been divided into two subsets: the first subset covers the years from 2002 to 2021, encompassing 240 data points, which will be used for constructing predictive models. The second subset consists of the data for the year 2022, comprising 12 data points, which will serve as a means to compare the accuracy of various forecasting methods. The evaluation criteria employed for this purpose are the minimum mean absolute error (MAE), the mean square error (MSE) and the mean absolute percentage error (MAPE). Furthermore, we will utilize the Python programming language to facilitate data analysis. © 2024 IEEE.

关键词： Mean square error

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Fusion of Inertial Sensor Suit and Monocular Camera for 3D Human Pelvis Pose Estimation

Fusion of Inertial Sensor Suit and Monocular Camera for 3D H...

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IEEE International Workshop on Robot and Human Communication (ROMAN)

作者： Mihaela Popescu Kashmira Shinde Proneet Sharma Lisa Gutzeit Frank Kirchner Robotics Group Faculty of Mathematics and Computer Science University of Bremen Bremen Germany Robotics Innovation Center German Research Center for Artificial Intelligence (DFKI GmbH) Bremen Germany

ISBN: (数字)9798350375022

ISBN: (纸本)9798350375039

In real-world scenarios, robots come closer to humans in many applications, sharing the same workspace or even manipulating the same objects. To ensure safe and intuitive collaboration, it is crucial to have an accurate knowledge of the human’s 3D position in space, which should be estimated with high precision, high frequency and low latency. However, individual sensors such as inertial measurement units (IMUs) or cameras cannot meet all requirements for reliable human pose estimation under conditions such as long operating times, large distances and occlusions. In this study, we highlight the limitations of different visual pose methods and present a fused approach for real-time estimation of the 3D position of the human pelvis using machine learning-based visual pose from a monocular camera and an IMU sensor suit. The multimodal fusion is based on the Invariant Extended Kalman filter (InEKF) on Lie groups, which fuses drift-free visual poses with high-frequency inertial measurements in a loosely-coupled manner. The evaluation is performed on a recorded dataset of multiple subjects performing various experimental scenarios. The results show that the fused approach can increase the accuracy and robustness of the estimates, taking a step closer towards smooth human-robot collaboration.

关键词： Visualization Three-dimensional displays Accuracy Pose estimation Robot vision systems Sensor fusion Cameras Real-time systems Pelvis Robots

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