@article{34614, abstract = {{Mit steigenden Optimierungsanforderungen an das Individuum wächst auch das indivi- duelle Bedürfnis nach Kontrolle. Dieses kann u. a. durch self tracking-Technologien erfüllt werden. Anhand von drei Fallbeispielen – der Personenwaage, dem Wearable und dem habit tracker – zeigt dieser Aufsatz, wie sich medienbasierte Selbsttechnologien im historischen Verlauf intensiviert und stärker in den Alltag integriert haben. Ein besonderer Fokus liegt dabei auf der Ambivalenz dieser Medien: Ermöglichen sie auf der einen Seite zwar eine Selbstkontrolle und stellen so potenziell sta- bilisierende Ressourcen für das Individuum dar, schaffen sie auf der anderen Seite auch neue Anforderungen, die es zu erfüllen gilt.}}, author = {{Schloots, Franziska Margarete}}, journal = {{ffk Journal}}, keywords = {{self-tracking, Selbsttechnologien, Wearable, Bullet Journal, Personenwaage, Selbstvermessung}}, number = {{7}}, pages = {{74--91}}, title = {{{‚Understand what’s happening within‘. Selbstkontrolle mit Personenwaage, Wearable und habit tracker}}}, doi = {{10.25969/MEDIAREP/18238}}, volume = {{6}}, year = {{2022}}, } @article{34640, author = {{Schloots, Franziska Margarete}}, issn = {{2192-5445}}, journal = {{Rabbit Eye - Zeitschrift für Filmforschung}}, keywords = {{Wearable, selft-tracking, Selbstvermessung, Animation, Tamagotchi, Anschaulichkeit}}, pages = {{65--77}}, title = {{{Die Tamagotchisierung des Selbst. Zur Anschaulichkeit von animierten Körperdaten}}}, volume = {{12}}, year = {{2022}}, } @article{36083, author = {{Constantiou, Ioanna and Mukkamala, Alivelu and Sjöklint, Mimmi and Trier, Matthias}}, issn = {{0960-085X}}, journal = {{European Journal of Information Systems}}, keywords = {{Library and Information Sciences, Information Systems, Self-Tracking, User Behaviour, Discontinuance}}, pages = {{1--21}}, publisher = {{Informa UK Limited}}, title = {{{Engaging with self-tracking applications: how do users respond to their performance data?}}}, doi = {{10.1080/0960085x.2022.2081096}}, year = {{2022}}, } @inproceedings{24547, abstract = {{Over the last years, several approaches for the data-driven estimation of expected possession value (EPV) in basketball and association football (soccer) have been proposed. In this paper, we develop and evaluate PIVOT: the first such framework for team handball. Accounting for the fast-paced, dynamic nature and relative data scarcity of hand- ball, we propose a parsimonious end-to-end deep learning architecture that relies solely on tracking data. This efficient approach is capable of predicting the probability that a team will score within the near future given the fine-grained spatio-temporal distribution of all players and the ball over the last seconds of the game. Our experiments indicate that PIVOT is able to produce accurate and calibrated probability estimates, even when trained on a relatively small dataset. We also showcase two interactive applications of PIVOT for valuing actual and counterfactual player decisions and actions in real-time.}}, author = {{Müller, Oliver and Caron, Matthew and Döring, Michael and Heuwinkel, Tim and Baumeister, Jochen}}, booktitle = {{8th Workshop on Machine Learning and Data Mining for Sports Analytics (ECML PKDD 2021)}}, keywords = {{expected possession value, handball, tracking data, time series classification, deep learning}}, location = {{Online}}, title = {{{PIVOT: A Parsimonious End-to-End Learning Framework for Valuing Player Actions in Handball using Tracking Data}}}, year = {{2021}}, } @article{28015, abstract = {{Background Understanding changes in dietary intake during puberty could aid the mapping of dietary interventions for primary prevention. The present study describes dietary changes from childhood to adolescence, and their associations with parental education, family income, child education, body mass index (BMI), pubertal onset and screen-time sedentary behaviour. Methods Dietary data (n = 1232) were obtained from food frequency questionnaires at the 10- and 15-year follow-ups of the GINIplus birth cohort study. Intakes of 17 food groups, macronutrients and antioxidant vitamins, were described by a) paired Wilcoxon rank sum tests, comparing average intakes at each time-point, and b) Cohen’s kappa “tracking” coefficients, measuring stability of intakes (maintenance of relative tertile positions across time). Further, associations of changes (tertile position increase or decrease vs. tracking) with parental education, family income, child education, pubertal onset, BMI, and screen-time, were assessed by logistic regression and multinomial logistic regression models stratified by baseline intake tertile. Results Both sexes increased average intakes of water and decreased starchy vegetables, margarine and dairy. Females decreased meat and retinol intakes and increased vegetables, grains, oils and tea. Males decreased fruit and carbohydrates and increased average intakes of meat, caloric drinks, water, protein, fat, polyunsaturated fatty acids (PUFAs), vitamin C and alpha-tocopherol. Both sexes presented mainly “fair” tracking levels [κw = 0.21–0.40]. Females with high (vs. low) parental education were more likely to increase their nut intake [OR = 3.8; 95 % CI = (1.7;8.8)], and less likely to decrease vitamin C intakes [0.2 (0.1;0.5)], while males were less likely to increase egg consumption [0.2 (0.1;0.5)] and n3 PUFAs [0.2 (0.1;0.5)]. Females with a higher (vs. low) family income were more likely to maintain medium wholegrain intakes [0.2 (0.1;0.7) for decrease vs. tracking, and 0.1 (0.0;0.5) for increase vs. tracking], and were less likely to decrease vitamin C intakes [0.2 (0.1;0.6)]. Males with high education were less likely to increase sugar-sweetened foods [0.1 (0.1;0.4)]. Finally, BMI in females was negatively associated with decreasing protein intakes [0.7 (0.6;0.9)]. In males BMI was positively associated with increasing margarine [1.4 (1.1;1.6)] and vitamin C intakes [1.4 (1.1;1.6)], and negatively associated with increasing n3 PUFA. Conclusions Average dietary intakes changed significantly, despite fair tracking levels, suggesting the presence of trends in dietary behaviour during puberty. Family income and parental education predominantly influenced intake changes. Our results support the rationale for dietary interventions targeting children, and suggest that sex-specific subpopulations, e.g. low socio-economic status, should be considered for added impact.}}, author = {{Harris, Carla and Flexeder, Claudia and Thiering, Elisabeth and Buyken, Anette and Berdel, Dietrich and Koletzko, Sibylle and Bauer, Carl-Peter and Brüske, Irene and Koletzko, Berthold and Standl, Marie}}, journal = {{BMC Public Health}}, keywords = {{Puberty, Dietary intake, Dietary changes, Tracking, Determinants, Epidemiology}}, pages = {{841}}, title = {{{Changes in dietary intake during puberty and their determinants: results from the GINIplus birth cohort study}}}, volume = {{15}}, year = {{2015}}, } @inproceedings{11739, abstract = {{Noise tracking is an important component of speech enhancement algorithms. Of the many noise trackers proposed, Minimum Statistics (MS) is a particularly popular one due to its simple parameterization and at the same time excellent performance. In this paper we propose to further reduce the number of MS parameters by giving an alternative derivation of an optimal smoothing constant. At the same time the noise tracking performance is improved as is demonstrated by experiments employing speech degraded by various noise types and at different SNR values.}}, author = {{Chinaev, Aleksej and Haeb-Umbach, Reinhold}}, booktitle = {{Interspeech 2015}}, keywords = {{speech enhancement, noise tracking, optimal smoothing}}, pages = {{1785--1789}}, title = {{{On Optimal Smoothing in Minimum Statistics Based Noise Tracking}}}, year = {{2015}}, } @article{11850, abstract = {{In this paper, we present a novel blocking matrix and fixed beamformer design for a generalized sidelobe canceler for speech enhancement in a reverberant enclosure. They are based on a new method for estimating the acoustical transfer function ratios in the presence of stationary noise. The estimation method relies on solving a generalized eigenvalue problem in each frequency bin. An adaptive eigenvector tracking utilizing the power iteration method is employed and shown to achieve a high convergence speed. Simulation results demonstrate that the proposed beamformer leads to better noise and interference reduction and reduced speech distortions compared to other blocking matrix designs from the literature.}}, author = {{Krueger, Alexander and Warsitz, Ernst and Haeb-Umbach, Reinhold}}, journal = {{IEEE Transactions on Audio, Speech, and Language Processing}}, keywords = {{acoustical transfer function ratio, adaptive eigenvector tracking, array signal processing, beamformer design, blocking matrix, eigenvalues and eigenfunctions, eigenvector-based transfer function ratios estimation, generalized sidelobe canceler, interference reduction, iterative methods, power iteration method, reduced speech distortions, reverberant enclosure, reverberation, speech enhancement, stationary noise}}, number = {{1}}, pages = {{206--219}}, title = {{{Speech Enhancement With a GSC-Like Structure Employing Eigenvector-Based Transfer Function Ratios Estimation}}}, doi = {{10.1109/TASL.2010.2047324}}, volume = {{19}}, year = {{2011}}, } @inproceedings{11723, abstract = {{In this paper we present a novel vehicle tracking algorithm, which is based on multi-level sensor fusion of GPS (global positioning system) with Inertial Measurement Unit sensor data. It is shown that the robustness of the system to temporary dropouts of the GPS signal, which may occur due to limited visibility of satellites in narrow street canyons or tunnels, is greatly improved by sensor fusion. We further demonstrate how the observation and state noise covariances of the employed Kalman filters can be estimated alongside the filtering by an application of the Expectation-Maximization algorithm. The proposed time-variant multi-level Kalman filter is shown to outperform an Interacting Multiple Model approach while at the same time being computationally less demanding.}}, author = {{Bevermeier, Maik and Peschke, Sven and Haeb-Umbach, Reinhold}}, booktitle = {{6th Workshop on Positioning Navigation and Communication (WPNC 2009)}}, keywords = {{covariance matrices, expectation-maximisation algorithm, expectation-maximization algorithm, global positioning system, Global Positioning System, GPS, inertial measurement unit, interacting multiple model approach, Kalman filters, multilevel sensor fusion, narrow street canyons, narrow tunnels, online parameter estimation, parameter estimation, road vehicles, robust vehicle localization, sensor fusion, state noise covariances, time-variant multilevel Kalman filter, vehicle tracking algorithm}}, pages = {{235--242}}, title = {{{Robust vehicle localization based on multi-level sensor fusion and online parameter estimation}}}, doi = {{10.1109/WPNC.2009.4907833}}, year = {{2009}}, } @inproceedings{11724, abstract = {{In this paper we present a novel vehicle tracking method which is based on multi-stage Kalman filtering of GPS and IMU sensor data. After individual Kalman filtering of GPS and IMU measurements the estimates of the orientation of the vehicle are combined in an optimal manner to improve the robustness towards drift errors. The tracking algorithm incorporates the estimation of time-variant covariance parameters by using an iterative block Expectation-Maximization algorithm to account for time-variant driving conditions and measurement quality. The proposed system is compared to an interacting multiple model approach (IMM) and achieves improved localization accuracy at lower computational complexity. Furthermore we show how the joint parameter estimation and localizaiton can be conducted with streaming input data to be able to track vehicles in a real driving environment.}}, author = {{Bevermeier, Maik and Peschke, Sven and Haeb-Umbach, Reinhold}}, booktitle = {{IEEE 69th Vehicular Technology Conference (VTC 2009 Spring)}}, keywords = {{computational complexity, expectation-maximisation algorithm, Global Positioning System, inertial measurement unit, inertial navigation, interacting multiple model, iterative block expectation-maximization algorithm, Kalman filters, multi-stage Kalman filter, parameter estimation, road vehicles, vehicle positioning, vehicle tracking}}, pages = {{1--5}}, title = {{{Joint Parameter Estimation and Tracking in a Multi-Stage Kalman Filter for Vehicle Positioning}}}, doi = {{10.1109/VETECS.2009.5073634}}, year = {{2009}}, } @inproceedings{11931, abstract = {{The paper is concerned with binaural signal processing for a bimodal human-robot interface with hearing and vision. The two microphone signals are processed to obtain an enhanced single-channel input signal for the subsequent speech recognizer and to localize the acoustic source, an important information for establishing a natural human-robot communication. We utilize a robust adaptive algorithm for filter-and-sum beamforming (FSB) and extract speaker direction information from the resulting FIR filter coefficients. Further, particle filtering is applied which conducts a nonlinear Bayesian tracking of speaker movement. Good location accuracy can be achieved even in highly reverberant environments. The results obtained outperform the conventional generalized cross correlation (GCC) method.}}, author = {{Warsitz, Ernst and Haeb-Umbach, Reinhold}}, booktitle = {{IEEE Workshop on Multimedia Signal Processing (MMSP 2004)}}, keywords = {{bimodal human-robot interface, binaural signal processing, enhanced single-channel input signal, filter-and-sum beamforming, filtering theory, FIR filter coefficient, generalized cross correlation method, microphones, microphone signal, nonlinear Bayesian tracking, particle filtering, robust adaptive algorithm, robust speaker direction estimation, signal processing, speech enhancement, speech recognition, speech recognizer, user interfaces}}, pages = {{367--370}}, title = {{{Robust speaker direction estimation with particle filtering}}}, doi = {{10.1109/MMSP.2004.1436569}}, year = {{2004}}, }