Per Boström-Rost, Daniel Axehill, Gustaf Hendeby, "On Global Optimization for Informative Path Planning", IEEE Control Systems Letters, 2(4): 833-838, 2018.
The problem of path planning for mobilesensors with the task of target monitoring is considered. A receding horizon optimal control approach based on the information filter is presented, where the limited field of view of the sensor can be modeled by introducing binary variables. The resulting nonlinear mixed integer problem to be solved in each sample, with no apparent tractable solution, is shown to be equivalent to a problem that robustly can be solved to global optimality using off-the-shelf optimization tools.
Michael Roth, Gustaf Hendeby, Carsten Fritsche, Fredrik Gustafsson, "The Ensemble Kalman filter: a signal processing perspective", EURASIP Journal on Advances in Signal Processing, 2017.
The ensemble Kalman filter (EnKF) is a Monte Carlo-based implementation of the Kalman filter (KF) for extremely high-dimensional, possibly nonlinear, and non-Gaussian state estimation problems. Its ability to handle state dimensions in the order of millions has made the EnKF a popular algorithm in different geoscientific disciplines. Despite a similarly vital need for scalable algorithms in signal processing, e.g., to make sense of the ever increasing amount of sensor data, the EnKF is hardly discussed in our field. This self-contained review is aimed at signal processing researchers and provides all the knowledge to get started with the EnKF. The algorithm is derived in a KF framework, without the often encountered geoscientific terminology. Algorithmic challenges and required extensions of the EnKF are provided, as well as relations to sigma point KF and particle filters. The relevant EnKF literature is summarized in an extensive survey and unique simulation examples, including popular benchmark problems, complement the theory with practical insights. The signal processing perspective highlights new directions of research and facilitates the exchange of potentially beneficial ideas, both for the EnKF and high-dimensional nonlinear and non-Gaussian filtering in general.
Gustaf Hendeby, Fredrik Gustafsson, Niklas Wahlström, Svante Gunnarsson, "Platform for Teaching Sensor Fusion Using a Smartphone", International journal of engineering education, 33(2B): 781-789, 2017.
A platform for sensor fusion consisting of a standard smartphone equipped with the specially developed Sensor Fusion appis presented. The platform enables real-time streaming of data over WiFi to a computer where signal processingalgorithms, e.g., the Kalman filter, can be developed and executed in a Matlab framework. The platform is an excellenttool for educational purposes and enables learning activities where methods based on advanced theory can be implementedand evaluated at low cost. The article describes the app and a laboratory exercise developed around these new technologicalpossibilities. The laboratory session is part of a course in sensor fusion, a signal processing continuation course focused onmultiple sensor signal applications, where the goal is to give the students hands on experience of the subject. This is done byestimating the orientation of the smartphone, which can be easily visualized and also compared to the built-in filters in thesmartphone. The filter can accept any combination of sensor data from accelerometers, gyroscopes, and magnetometers toexemplify their importance. This way different tunings and tricks of important methods are easily demonstrated andevaluated on-line. The presented framework facilitates this in a way previously impossible.
Giuseppe Bianco, Mihaela Ilieva, Clas Veibäck, Kristoffer Öfjäll, Alicja Gadomska, Gustaf Hendeby, Michael Felsberg, Fredrik Gustafsson, Susanne Åkesson, "Emlen funnel experiments revisited: methods update for studying compass orientation in songbirds", Ecology and Evolution, 6(19): 6930-6942, 2016.
1 Migratory songbirds carry an inherited capacity to migrate several thousand kilometers each year crossing continental landmasses and barriers between distant breeding sites and wintering areas. How individual songbirds manage with extreme precision to find their way is still largely unknown. The functional characteristics of biological compasses used by songbird migrants has mainly been investigated by recording the birds directed migratory activity in circular cages, so-called Emlen funnels. This method is 50 years old and has not received major updates over the past decades. The aim of this work was to compare the results from newly developed digital methods with the established manual methods to evaluate songbird migratory activity and orientation in circular cages. 2 We performed orientation experiments using the European robin (Erithacus rubecula) using modified Emlen funnels equipped with thermal paper and simultaneously recorded the songbird movements from above. We evaluated and compared the results obtained with five different methods. Two methods have been commonly used in songbirds orientation experiments; the other three methods were developed for this study and were based either on evaluation of the thermal paper using automated image analysis, or on the analysis of videos recorded during the experiment. 3 The methods used to evaluate scratches produced by the claws of birds on the thermal papers presented some differences compared with the video analyses. These differences were caused mainly by differences in scatter, as any movement of the bird along the sloping walls of the funnel was recorded on the thermal paper, whereas video evaluations allowed us to detect single takeoff attempts by the birds and to consider only this behavior in the orientation analyses. Using computer vision, we were also able to identify and separately evaluate different behaviors that were impossible to record by the thermal paper. 4 The traditional Emlen funnel is still the most used method to investigate compass orientation in songbirds under controlled conditions. However, new numerical image analysis techniques provide a much higher level of detail of songbirds migratory behavior and will provide an increasing number of possibilities to evaluate and quantify specific behaviors as new algorithms will be developed.
Michael Roth, Gustaf Hendeby, Fredrik Gustafsson, "Nonlinear Kalman Filters Explained: A Tutorial on Moment Computations and Sigma Point Methods", Journal of Advances in Information Fusion, 11(1): 47-70, 2016.
Svante Björklund, Henrik Petersson, Gustaf Hendeby, "Features for micro-Doppler based activity classification", IET radar, sonar & navigation, 9(9): 1181-1187, 2015.
Cesur Karabacak, Sevgi Z. Gurbuz, Ali C. Gurbuz, Mehmet B. Guldogan, Gustaf Hendeby, Fredrik Gustafsson, "Knowledge Exploitation for Human Micro-Doppler Classification", IEEE Geoscience and Remote Sensing Letters, 12(10): 2125-2129, 2015.
Micro-Doppler radar signatures have great potential for classifying pedestrians and animals, as well as their motion pattern, in a variety of surveillance applications. Due to the many degrees of freedom involved, real data need to be complemented with accurate simulated radar data to be able to successfully design and test radar signal processing algorithms. In many cases, the ability to collect real data is limited by monetary and practical considerations, whereas in a simulated environment, any desired scenario may be generated. Motion capture (MOCAP) has been used in several works to simulate the human micro-Doppler signature measured by radar; however, validation of the approach has only been done based on visual comparisons of micro-Doppler signatures. This work validates and, more importantly, extends the exploitation of MOCAP data not just to simulate micro-Doppler signatures but also to use the simulated signatures as a source of a priori knowledge to improve the classification performance of real radar data, particularly in the case when the total amount of data is small.
Gabriele Bleser, Dima Damen, Ardhendu Behera, Gustaf Hendeby, Katharina Mura, Markus Miezal, Andrew Gee, Nils Petersen, Gustavo Maçães, Hugo Domingues, Dominic Gorecky, Luis Almeida, Walterio Mayol-Cuevas, Andrew Calway, Anthony G. Cohn, David C. Hogg, Didier Stricker, "Cognitive Learning, Monitoring and Assistance of Industrial Workflows Using Egocentric Sensor Networks", PLoS ONE, 10(6), 2015.
Today, the workflows that are involved in industrial assembly and production activities are becoming increasingly complex. To efficiently and safely perform these workflows is demanding on the workers, in particular when it comes to infrequent or repetitive tasks. This burden on the workers can be eased by introducing smart assistance systems. This article presents a scalable concept and an integrated system demonstrator designed for this purpose. The basic idea is to learn workflows from observing multiple expert operators and then transfer the learnt workflow models to novice users. Being entirely learning-based, the proposed system can be applied to various tasks and domains. The above idea has been realized in a prototype, which combines components pushing the state of the art of hardware and software designed with interoperability in mind. The emphasis of this article is on the algorithms developed for the prototype: 1) fusion of inertial and visual sensor information from an on-body sensor network (BSN) to robustly track the user's pose in magnetically polluted environments; 2) learning-based computer vision algorithms to map the workspace, localize the sensor with respect to the workspace and capture objects, even as they are carried; 3) domain-independent and robust workflow recovery and monitoring algorithms based on spatiotemporal pairwise relations deduced from object and user movement with respect to the scene; and 4) context-sensitive augmented reality (AR) user feedback using a head-mounted display (HMD). A distinguishing key feature of the developed algorithms is that they all operate solely on data from the on-body sensor network and that no external instrumentation is needed. The feasibility of the chosen approach for the complete action-perception-feedback loop is demonstrated on three increasingly complex datasets representing manual industrial tasks. These limited size datasets indicate and highlight the potential of the chosen technology as a combined entity as well as point out limitations of the system.
David Lindgren, Gustaf Hendeby, Fredrik Gustafsson, "Distributed localization using acoustic Doppler", Signal Processing, 107: 43-53, 2015.
It is well-known that the motion of an acoustic source can be estimated from Doppler shift observations. It is however not obvious how to design a sensor network to efficiently deliver the localization service. In this work a rather simplistic motion model is proposed that is aimed at sensor networks with realistic numbersof sensor nodes. It is also described how to efficiently solve the associated least squares optimization problem by Gauss-Newton variable projection techniques, and how to initiate the numerical search from simple features extracted from the observed frequency series. The methods are evaluated by Monte Carlo simulations and demonstrated on real data by localizing an all-terrain vehicle. Itis concluded that the processing components included are fairly mature for practical implementations in sensor networks.
Attila Reiss, Gustaf Hendeby, Didier Stricker, "A novel confidence-based multiclass boosting algorithm for mobile physical activity monitoring", Personal and Ubiquitous Computing, 19(1): 105-121, 2015.
This paper addresses one of the main challenges in physical activity monitoring, as indicated by recent benchmark results: The difficulty of the complex classification problems exceeds the potential of existing classifiers. Therefore, this paper proposes the ConfAdaBoost.M1 algorithm. This algorithm is a variant of the AdaBoost.M1 that incorporates well-established ideas for confidence-based boosting. ConfAdaBoost.M1 is compared to the most commonly used boosting methods using benchmark datasets from the UCI machine learning repository. Moreover, it is evaluated on an activity recognition and an intensity estimation problem, including a large number of physical activities from the recently released PAMAP2 dataset. The presented results indicate that the proposed ConfAdaBoost.M1 algorithm significantly improves the classification performance on most of the evaluated datasets, especially for larger and more complex classification tasks. Finally, two empirical studies are designed and carried out to investigate the feasibility of ConfAdaBoost.M1 for physical activity monitoring applications in mobile systems.
Gabriele Bleser, Daniel Steffen, Markus Weber, Gustaf Hendeby, Didier Stricker, Laetitia Fradet, Frédéric Marin, Nathalie Ville, Francois Carré, "A personalized exercise trainer for the elderly", Journal of Ambient Intelligence and Smart Environments, 5(6): 547-562, 2013.
Regular and moderate physical activity practice provides many physiological benefits. It reduces the risk of disease outcomes and is the basis for proper rehabilitation after a severe disease. Aerobic activity and strength exercises are strongly recommended in order to maintain autonomy with ageing. Balanced activity of both types is important, especially to the elderly population. Several methods have been proposed to monitor aerobic activities. However, no appropriate method is available for controlling more complex parameters of strength exercises. Within this context, the present article introduces a personalized, home-based strength exercise trainer designed for the elderly. The system guides a user at home through a personalized exercise program. Using a network of wearable sensors the user's motions are captured. These are evaluated by comparing them to prescribed exercises, taking both exercise load and technique into account. Moreover, the evaluation results are immediately translated into appropriate feedback to the user in order to assist the correct exercise execution. Besides the direct feedback, a major novelty of the system is its generic personalization by means of a supervised teach-in phase, where the program is performed once under supervision of a physical activity specialist. This teach-in phase allows the system to record and learn the correct execution of exercises for the individual user and to provide personalized monitoring. The user-driven design process, the system development and its underlying activity monitoring methodology are described. Moreover, technical evaluation results as well as results concerning the usability of the system for ageing people are presented. The latter has been assessed in a clinical study with thirty participants of 60 years or older, some of them showing usual diseases or functional limitations observed in elderly population.
Fredrik Gustafsson, Gustaf Hendeby, "Some Relations Between Extended and Unscented Kalman Filters", IEEE Transactions on Signal Processing, 60(2): 545-555, 2012.
The unscented Kalman filter (UKF) has become a popular alternative to the extended Kalman filter (EKF) during the last decade. UKF propagates the so called sigma points by function evaluations using the unscented transformation (UT), and this is at first glance very different from the standard EKF algorithm which is based on a linearized model. The claimed advantages with UKF are that it propagates the first two moments of the posterior distribution and that it does not require gradients of the system model. We point out several less known links between EKF and UKF in terms of two conceptually different implementations of the Kalman filter: the standard one based on the discrete Riccati equation, and one based on a formula on conditional expectations that does not involve an explicit Riccati equation. First, it is shown that the sigma point function evaluations can be used in the classical EKF rather than an explicitly linearized model. Second, a less cited version of the EKF based on a second-order Taylor expansion is shown to be quite closely related to UKF. The different algorithms and results are illustrated with examples inspired by core observation models in target tracking and sensor network applications.
Gustaf Hendeby, Rickard Karlsson, Fredrik Gustafsson, "The Rao-Blackwellized Particle Filter: A Filter Bank Implementation", EURASIP Journal on Advances in Signal Processing, 2010(724087), 2010.
Gustaf Hendeby, Rickard Karlsson, Fredrik Gustafsson, "Particle Filtering: The Need for Speed", EURASIP Journal on Advances in Signal Processing, 2010(181403), 2010.
The particle filter (PF) has during the last decade been proposed for a wide range of localization and tracking applications. There is a general need in such embedded system to have a platform for efficient and scalable implementation of the PF. One such platform is the graphics processing unit (GPU), originally aimed to be used for fast rendering of graphics. To achieve this, GPUs are equipped with a parallel architecture which can be exploited for general-purpose computing on GPU (GPGPU) as a complement to the central processing unit (CPU). In this paper, GPGPU techniques are used to make a parallel recursive Bayesian estimation implementation using particle filters. The modifications made to obtain a parallel particle filter, especially for the resampling step, are discussed and the performance of the resulting GPU implementation is compared to the one achieved with a traditional CPU implementation. The comparison is made using a minimal sensor network with bearings-only sensors. The resulting GPU filter, which is the first complete GPU implementation of a PF published to this date, is faster than the CPU filter when many particles are used, maintaining the same accuracy. The parallelization utilizes ideas that can be applicable for other applications.
Fredrik Gustafsson, Gustaf Hendeby, "Exploring New Localization Applications Using a Smartphone", Sensing and Control for Autonomous Vehicles, Lecture Notes in Control and Information Sciences, No. 474, 161-179, 2017.
Localization is an enabling technology in many applications and services today and in the future. Satellite navigation often works fine for navigation, infotainment and location based services, and it is today the dominating solution in commercial products. A nice exception is the localization in Google Maps, where radio signal strength from WiFi and cellular networks are used as complementary information to increase accuracy and integrity. With the on-going trend with more autonomous functions being introduced in our vehicles and with all our connected devices, most of them operated in indoor enviroments where satellite signals are not available,there is an acute need for new solutions.
At the same time, our smartphones are getting more sophisticated in their sensor configuration. Therefore, in this chapter we present a freely available Sensor Fusion app developed in-house, how it works, how it has been used, and how it can be used based on a variety of applications in our research and student projects.
Saikat Saha, Gustaf Hendeby, Fredrik Gustafsson, "Mixture Kalman Filters and Beyond", Current Trends in Bayesian Methodology with Applications, 537-562, 2015.
Gabriele Bleser, Daniel Steffen, Attila Reiss, Markus Weber, Gustaf Hendeby, Laetitia Fradet, "Personalized Physical Activity Monitoring Using Wearable Sensors", Smart Health, Lecture Notes in Computer Science, No. 8700, 99-124, 2015.
Per Boström-Rost, Daniel Axehill, Gustaf Hendeby, "Informative Path Planning for Active Tracking of Agile Targets", Proceedings of 2019 IEEE Aerospace Conference, 2019.
This paper proposes a method to generate informative trajectories for a mobile sensor that tracks agile targets.The goal is to generate a sensor trajectory that maximizes the tracking performance, captured by a measure of the covariance matrix of the target state estimate. The considered problem is acombination of estimation and control, and is often referred to as informative path planning (IPP). When using nonlinear sensors, the tracking performance depends on the actual measurements, which are naturally unavailable in the planning stage.The planning problem hence becomes a stochastic optimization problem, where the expected tracking performance is used inthe objective function. The main contribution of this work is anapproximation of the problem based on deterministic sampling of the predicted target distribution. This is in contrast to prior work, where only the most likely target trajectory is considered.It is shown that the proposed method greatly improves the ability to track agile targets, compared to a baseline approach.
Jonas Nygårds, Viktor Deleskog, Gustaf Hendeby, "Decentralized Tracking in Sensor Networks with Varying Coverage", 2018 21st International Conference on Information Fusion (FUSION), 1661-1667, 2018.
The number of sensors used in tracking scenariosis constantly increasing, this puts high demands on the trackingmethods to handle these data streams. Central processing (ideallyoptimal) puts high demands on the central node, is sensitive toinaccurate sensor parameters, and suffers from the single pointof failure problem. Decentralizing the tracking can improve this,but may give considerable performance loss. The newly presentedinverse covariance intersection method, proven to be consistent,even under unknown track cross correlations, is benchmarkedagainst alternatives. Different track-to-track methods, includingsmoothed association over a window, are compared. A scenariowith objects tracked in multiple cameras, not necessarily opti-mized for tracking, are used to give realism to the evaluations.
Isaac Skog, Gustaf Hendeby, Fredrik Gustafsson, "Magnetic Odometry - A Model-Based Approach Using A Sensor Array", 2018 21st International Conference on Information Fusion (FUSION), 794-798, 2018.
Parinaz Kasebzadeh, Gustaf Hendeby, Carsten Fritsche, Fredrik Gunnarsson, Fredrik Gustafsson, "IMU Dataset For Motion and Device Mode Classification", 2017 INTERNATIONAL CONFERENCE ON INDOOR POSITIONING AND INDOOR NAVIGATION (IPIN), International Conference on Indoor Positioning and Indoor Navigation, 2017.
Classification of motion mode (walking, running, standing still) and device mode (hand-held, in pocket, in back-pack) is an enabler in personal navigation systems for the purpose of saving energy and design parameter settings and also for its own sake. Our main contribution is to publish one of the most extensive datasets for this problem, including inertial data from eight users, each one performing three pre-defined trajectories carrying four smartphones and seventeen inertial measurement units on the body. All kind of metadata is available such as the ground truth of all modes and position. A second contribution is the first study on a joint classifier of motion and device mode, respectively, where preliminary but promising results are presented.
Kamiar Radnosrati, Gustaf Hendeby, Carsten Fritsche, Fredrik Gunnarsson, Fredrik Gustafsson, "Performance of OTDOA Positioning in Narrowband IoT Systems", 28th Annual IEEE International Symposium on Personal, Indoor and Mobile Radio Communications (PIMRC), 2017.
Narrowband Internet of Things (NB-IoT) is an emerging cellular technology designed to target low-cost devices, high coverage, long device battery life (more than ten years), and massive capacity. We investigate opportunities for device tracking in NB-IoT systems using Observed Time Difference of Arrival (OTDOA) measurements. Reference Signal Time Difference (RSTD) reports are simulated to be sent to the mobile location center periodically or on an ondemand basis. We investigate the possibility of optimizing the number of reports per minute budget on horizontal positioning accuracy using an on-demand reporting method based on the Signal to Noise Ratio (SNR) of the measured cells received by the User Equipment (UE). Wireless channels are modeled considering multipath fading propagation conditions. Extended Pedestrian A (EPA) and Extended Typical Urban (ETU) delay profiles corresponding to low and high delay spread environments, respectively, are simulated for this purpose. To increase the robustness of the filtering method, measurement noise outliers are detected using confidence bounds estimated from filter innovations.
Andreas Bergström, Gustaf Hendeby, Fredrik Gunnarsson, Fredrik Gustafsson, "TOA Estimation Improvements in Multipath Environments by Measurement Error Models", Proceedings of the 2017 IEEE 28th Annual International Symposium on Personal, Indoor, and Mobile Radio Communications (PIMRC), Annual International Symposium on Personal, Indoor, and Mobile Radio Communications (PIMRC), Vol. 2017, 1-8, 2017.
Jonatan Olofsson, Clas Veibäck, Gustaf Hendeby, Tor Arne Johansen, "Outline of a System for Integrated Adaptive Ice Tracking and Multi-Agent Path Planning", Proceedings of the 2017 Workshop on Research, Education and Development of Unmanned Aerial Systems (RED-UAS), 13-18, 2017.
Du Ho, Jonas Linder, Gustaf Hendeby, Martin Enqvist, "Vertical modeling of a quadcopter for mass estimation and diagnosis purposes", Proceedings of the Workshop on Research, Education and Development on Unmanned Aerial Systems, RED-UAS, Linköping, Sweden, 3-5 October, 2017, 2017.
Du Ho, Jonas Linder, Gustaf Hendeby, Martin Enqvist, "Mass estimation of a quadcopter using IMU data", 2017 International Conference on Unmanned Aircraft Systems (ICUAS), June 13-16, 2017, Miami, FL, USA, 1260-1266, 2017.
Martin Lindfors, Gustaf Hendeby, Fredrik Gustafsson, Rickard Karlsson, "On Frequency Tracking in Harmonic Acoustic Signals", Proceedings of the 2017 20th International Conference on Information Fusion (FUSION)., 2017.
Acoustic frequency tracking of a harmonic signalwith continuously varying frequency is considered. The Rao-Blackwellized point mass filter (RBPMF), previously proposed bythe authors for mechanical vibration tracking, is applied to the problem. The RBPMF is compared with two periodogram-based methods, and the similarities and differences between them are explained. Both experimental and simulation results in a Doppler frequency tracking scenario are presented, and the results show that the RBPMF can have significantly less estimation error than the competing methods.
Jonatan Olofsson, Clas Veibäck, Gustaf Hendeby, "Sea Ice Tracking with a Spatially Indexed Labeled Multi-Bernoulli Filter", Proceedings of the 2017 20th International Conference on Information Fusion, 376-383, 2017.
In polar region operations, drift ice positioning and tracking is useful for both scientific and safety reasons. At its core is a Multi-Target Tracking (MTT) problem in which currents and winds make motion modeling difficult. One recent algorithm in the MTT field, employed in this paper, is the Labeled Multi-Bernoulli (LMB) filter. In particular, a proposed reformulation of the LMB equations exposes a structure which is exploited to propose a compact algorithm for the generation of the filter's posterior distribution. Further, spatial indexing is applied to the clustering process of the filter, allowing efficient separation of the filter into smaller, independent parts with lesser total complexity than that of an unclustered filter. Many types of sensors can be employed to generate detections of sea ice, and in this paper a recorded dataset from a Terrestrial Radar Interferometer (TRI) is used to demonstrate the application of the Spatially Indexed Labeled Multi-Bernoulli filter to estimate the currents of an observed area in Kongsfjorden, Svalbard.
Jonas Nygårds, Viktor Deleskog, Gustaf Hendeby, "Safe Fusion Compared to Established Distributed Fusion Methods", Proceedings of IEEE International Conference on Multisensor Fusion and Integration for Intelligent Systems, 2016.
The safe fusion algorithm is benchmarked againstthree other methods in distributed target tracking scenarios. Safefusion is a fairly unknown method similarly to, e.g., covarianceintersection, that can be used to fuse potentially dependentestimates without double counting data. This makes it suitablefor distributed target tracking, where dependencies are oftenunknown or difficult to derive. The results show that safe fusionis a very competitive alternative in five evaluated scenarios, whileat the same time easy to implement and compute compared tothe other evaluated methods. Hence, safe fusion is an attractivealternative in track to track fusion systems.
Hanna E. Nyqvist, Gustaf Hendeby, Fredrik Gustafsson, "On Joint Range and Velocity Estimation in Detection and Ranging Sensors", Proceedings of 19th International Conference on Information Fusion (FUSION), 1674-1681, 2016.
Radar and sonar provide information of both range and radial velocity to unknown objects. This is accomplished by emitting a signal waveform and computing the round trip time and Doppler shift. Estimation of the round trip time and Doppler shift is usually done separately without considering the couplings between these two object related quantities. The purpose of this contribution is to first model the amplitude, time shift and time scale of the returned signal in terms of the object related states range and velocity, and analyse the Cramér-Rao lower bound (CRLB) for the joint range and velocity estimation problem. One of the conclusions is that there is negative correlation between range and velocity. The maximum likelihood (ML) cost function also confirms this strong negative correlation. For target tracking applications, the use of the correct covariance matrix for the measurement vector gives a significant gain in information, compared to using the variance of range and velocity assuming independence. In other words, the knowledge of the correlation tells the tracking filter that a too large range measurement comes most likely with a too small velocity measurement, and vice versa. Experiments with sound pulses reflected in a wall indoors confirm the main conclusion of negative correlation.
Clas Veibäck, Gustaf Hendeby, Fredrik Gustafsson, "On Fusion of Sensor Measurements and Observation with Uncertain Timestamp for Target Tracking", Proceedings of the 19th International Conference on Information Fusion, 1268-1275, 2016.
Kamiar Radnosrati, Carsten Fritsche, Gustaf Hendeby, Fredrik Gunnarsson, Fredrik Gustafsson, "Fusion of TOF and TDOA for 3GPP Positioning", Fusion 2016, 19th International Conference on Information Fusion, 1454-1460, 2016.
Parinaz Kasebzadeh, Carsten Fritsche, Gustaf Hendeby, Fredrik Gunnarsson, Fredrik Gustafsson, "Improved Pedestrian Dead Reckoning Positioning With Gait Parameter Learning", Proceedings of the 19th International Conference on Information Fusion, 379-385, 2016.
Bram Dil, Gustaf Hendeby, Fredrik Gustafsson, Bernhard Hoenders, "Approximate Diagonalized Covariance Matrix for Signals with Correlated Noise", Proceedings of the 19th International Conference of Information Fusion, 521-527, 2016.
Martin Lindfors, Gustaf Hendeby, Fredrik Gustafsson, Rickard Karlsson, "Vehicle Speed Tracking Using Chassis Vibrations", Proceedings of the 2016 IEEE Intelligent Vehicles Symposium (IV), 214-219, 2016.
The speed of a wheeled vehicle is usually estimatedusing wheel speed sensors (WSS) or GPS. If these signals are unavailable, other methods must be used. We propose a novelapproach exploiting the fact that vibrations from rotating axles,with fundamental frequency proportional to vehicle speed, aretransmitted via the vehicle chassis. Using an accelerometer, these vibrations can be tracked to estimate vehicle speed whileother sources of vibrations act as disturbances. A state-space model for the dynamics of the harmonics is presented andformulated such that there is a conditional linear-Gaussiansubstructure, enabling efficient Rao-Blackwellized methods. Avariant of the Rao-Blackwellized point-mass filter is derived, significantly reducing computational complexity, and reducingthe memory requirements from quadratic to linear in thenumber of grid points. It is applied to experimental data from the sensor cluster of a car and validated using therotational frequency from WSS data. The proposed methodshows improved performance and robustness in comparisonto a Rao-Blackwellized particle filter implementation and afrequency spectrum maximization method.
Yuxin Zhao, Feng Yin, Fredrik Gunnarsson, Mehdi Amirijoo, Gustaf Hendeby, "Gaussian Process for Propagation modeling and Proximity Reports Based Indoor Positioning", 2016 IEEE 83rd Vehicular Technology Conference (VTC Spring), 1-5, 2016.
Martin Skoglund, Gustaf Hendeby, Jonas Nygårds, Jouni Rantakokko, Gunnar Eriksson, "Indoor Localization Using Multi-Frequency RSS", Proceddings of the IEEE/ION Position Location and Navigation Symposium, IEEE - ION Position Location and Navigation Symposium, 177-186, 2016.
Christina Grönwall, Gustaf Hendeby, Sinivaara Kristian, "A proposal for combining mapping, localization and target recognition", ELECTRO-OPTICAL REMOTE SENSING, PHOTONIC TECHNOLOGIES, AND APPLICATIONS IX, Proceedings of SPIE, Vol. 9649, 2015.
Hanna E. Nyqvist, Martin A. Skoglund, Gustaf Hendeby, Fredrik Gustafsson, "Pose Estimation Using Monocular Vision and Inertial Sensors Aided with Ultra Wide Band", International Conference on Indoor Positioning and Indoor Navigation (IPIN), 2015, 2015.
This paper presents a method for global pose estimation using inertial sensors, monocular vision, and ultra wide band (UWB) sensors. It is demonstrated that the complementary characteristics of these sensors can be exploited to provide improved global pose estimates, without requiring the introduction of any visible infrastructure, such as fiducial markers. Instead, natural landmarks are jointly estimated with the pose of the platform using a simultaneous localization and mapping framework, supported by a small number of easy-to-hide UWB beacons with known positions. The method is evaluated with data from a controlled indoor experiment with high precision ground truth. The results show the benefit of the suggested sensor combination and suggest directions for further work.
Michael Roth, Carsten Fritsche, Gustaf Hendeby, Fredrik Gustafsson, "The Ensemble Kalman Filter and its Relations to Other Nonlinear Filters", Proceedings of the 2015 European Signal Processing Conference (EUSIPCO 2015), European Signal Processing Conference, 1236-1240, 2015.
The Ensemble Kalman filter (EnKF) is a standard algorithm in oceanography and meteorology, where it has got thousands of citations. It is in these communities appreciated since it scales much better with state dimension n than the standard Kalman filter (KF). In short, the EnKF propagates ensembles with N state realizations instead of mean values and covariance matrices and thereby avoids the computational and storage burden of working on n×n matrices. Perhaps surprising, very little attention has been devoted to the EnKF in the signal processing community. In an attempt to change this, we present the EnKF in a Kalman filtering context. Furthermore, its application to nonlinear problems is compared to sigma point Kalman filters and the particle filter, so as to reveal new insights and improvements for high-dimensional filtering algorithms in general. A simulation example shows the EnKF performance in a space debris tracking application.
Martin Skoglund, Gustaf Hendeby, Daniel Axehill, "Extended Kalman Filter Modifications Based on an Optimization View Point", 18th International Conference of Information Fusion, 2015.
The extended Kalman filter (EKF) has been animportant tool for state estimation of nonlinear systems sinceits introduction. However, the EKF does not possess the same optimality properties as the Kalman filter, and may perform poorly. By viewing the EKF as an optimization problem it is possible to, in many cases, improve its performance and robustness. The paper derives three variations of the EKF by applying different optimisation algorithms to the EKF costfunction and relate these to the iterated EKF. The derived filters are evaluated in two simulation studies which exemplify the presented filters.
Fredrik Gustafsson, Gustaf Hendeby, David Lindgren, George Mathai, Hans Habberstad, "Direction of Arrival Estimation in Sensor Arrays Using Local Series Expansion of the Received Signal", 18th International Conference of Information Fusion, 2015.
A local series expansion of a received signal is pro-posed for computing direction of arrival (DOA) in sensor arrays. The advantages compared to classical DOA estimation methods include general sensor configurations, ultra-slow sampling, smalldimension of the arrays, and that it applies for both narrowbandand wideband signals without prior knowledge of the signals. This makes the method well suited for DOA estimation in sensor networks where size and energy consumption have to be small. We generalize the common far-field assumption of the target toalso include the near-field, which enables target tracking usinga network of sensor arrays in one framework.
Clas Veibäck, Gustaf Hendeby, Fredrik Gustafsson, "Tracking of Dolphins in a Basin Using a Constrained Motion Model", Proceedings of the 18th International Conference of Information Fusion, 2015.
Visual animal tracking is a challenging problem generally requiring extended target models, group tracking and handling of clutter and missed detections. Furthermore, the dolphin tracking problem we consider includes basin constraints, shadows, limited field of view and rapidly changing light conditions. We describe the whole pipeline of a solution based on a ceiling-mounted fisheye camera that includes foreground segmentation and observation extraction in each image, followed by a target tracking framework. A novel contribution is a potential field model of the basin edges as a part of the motion model, that provides a robust prediction of the dolphin trajectories in phases with long segments of missed detections. The overall performance on real data is quite promising.
Martin Nilsson, Jouni Rantakokko, Martin A. Skoglund, Gustaf Hendeby, "Indoor Positioning Using Multi-Frequency RSS with Foot-Mounted INS", Fifth International Conference on Indoor Positioning and Indoor Navigation, 2014.
This paper presents a system which combines a zero-velocity-update-(ZUPT-)aided inertial navigation system (INS), using a foot-mounted inertial measurement unit (IMU), with opportunistic use of multi-frequency received signal strength (RSS) measurements. The system does not rely on maps or pre-collected data from surveys of the radio-frequency (RF) environment. Instead it builds its own database of collected RSS measurements during the course of the operation. New RSS measurements are continuously compared with the stored values in the database, and when the user returns to a previously visited area this can thus be detected. This enables loop-closures to be detected online and used for error drift correction. The system utilises a distributed particle simultaneous localization and mapping (DP-SLAM) algorithm which provides a flexible 2D navigation platform that can be extended with more sensors. The experimental results presented in this paper indicates that the developed RSS SLAM algorithm can, in many cases, significantly improve the positioning performance of a foot-mounted INS.
Gustaf Hendeby, Fredrik Gustafsson, Niklas Wahlström, "Teaching Sensor Fusion and Kalman Filtering using a Smartphone", Proceedings of the 19th World Congress of the International Federation of Automatic Control (IFAC), IFAC Proceedings series, 2014.
The Kalman filter has been the work horse in model based filtering for five decades, and basic knowledge and understanding of it is an important part of the curriculum in many Master of Science programs. It is therefore important to combine theoretical studies with practical experience to allow the students to deepen their understanding of the filter. We have developed a lab where the students implement a Kalman filter in a real-time Matlab framework, to which data are streamed from the smartphone over WiFi. The goal of the lab is to estimate the orientation of the smartphone, which can be nicely visualized graphically and also be compared to the built-in filters in the smartphone. The filter can accept any combination of sensor data from accelerometers, gyroscopes, and magnetometer, with different performance. Different tunings and tricks in the Kalman filter are easily evaluated on-line. The smartphone app is also a stand-alone tool to visualize the sensor data graphically. So far the lab seems tohave been successful in reaching the pedagogic goals and to engage the students.
Viktor Deleskog, Hans Habberstad, Gustaf Hendeby, David Lindgren, Niklas Wahlström, "Robust NLS Sensor Localization using MDS Initialization", 17th International Conference on Information Fusion (FUSION), 2014, 1-7, 2014.
Before a sensor network can be used for target localization, the locations of the sensors need to be determined. We approach this calibration step by moving a source to distinct positions around the network. At each position, the range to each sensor is measured,and from these range measurements the sensor locations can be estimated by solving a nonlinear least squares (NLS) problem. Here we formulate the NLS problem and describe how to robustly initialize it by the use of multidimensional scaling. The method is evaluated on both simulations and real data from an acoustic sensor network. Withas few as six source positions, a robust calibration is demonstrated that gives a position error about the same size as the range error. In the acoustic example this RMSE is less than 40 cm.
Michael Roth, Gustaf Hendeby, Fredrik Gustafsson, "EKF/UKF Maneuvering Target Tracking using Coordinated Turn Models with Polar/Cartesian Velocity", 17th International Conference on Information Fusion (FUSION), 2014, 1-8, 2014.
Nonlinear Kalman filter adaptations such as extended Kalman filters (EKF) or unscented Kalman filters (UKF) provide approximate solutions to state estimation problems in nonlinear models. The algorithms utilize mean values and covariance matrices to represent the probability densities in the otherwise intractable Bayesian filtering equations. As a consequence, their estimation performance can show significant dependence on the choice of state coordinates. The here considered problem of tracking maneuvering targets using coordinated turn (CT) models is one practically relevant example: The velocity in the target state can either be formulated in Cartesian or polar coordinates. We extend a previous study to a broader range of CT models that allow for changes in target speed and turn rate, and investigate UKF as well as EKF variants in terms of their performance and sensitivity to noise parameters. The results advocate for the use of polar CT models.
Gustaf Hendeby, Rickard Karlsson, "Gaussian Mixture PHD Filtering with Variable Probability of Detection", 17th International Conference on Information Fusion (FUSION), 2014, 1-7, 2014.
The probabilistic hypothesis density (PHD) filter has grown in popularity during the last decade as a way to address the multi-target tracking problem. Several algorithms exist; for instance under linear-Gaussian assumptions, the Gaussian mixture PHD (GM-PHD) filter. This paper extends the GM-PHD filter to the common case with variable probability of detection throughout the tracking volume. This allows for more efficient utilization, e.g., in situations with distance dependent probability of detection or occluded regions. The proposed method avoids previous algorithmic pitfalls that can result in a not well-defined PHD. The method is illustrated and compared to the standard GM-PHD in a simplified multi-target tracking example as well asin a realistic nonlinear underwater sonar simulation application, both demonstrating the effectiveness of the proposed method.
Saikat Saha, Gustaf Hendeby, "Rao-Blackwellized particle filter for Markov modulated nonlinear dynamic systems", Statistical Signal Processing (SSP), 2014 IEEE Workshop on, 272-275, 2014.
The Markov modulated (switching) state space is an important model paradigm in statistical signal processing. In this article, we specifically consider Markov modulated nonlinear state-space models and address the online Bayesian inference problem for such models. In particular, we propose a new Rao-Blackwellized particle filter for the inference task which is our main contribution here. A detailed description of the problem and an algorithm is presented.
Svante Björklund, Henrik Petersson, Gustaf Hendeby, "On distinguishing between human individuals in micro-Doppler signatures", 14th International Radar Symposium (IRS), 865-870, 2013.
Attila Reiss, Gustaf Hendeby, Didier Stricker, "Confidence-based multiclass AdaBoost for physical activity monitoring", ISWC '13: Proceedings of the 2013 International Symposium on Wearable Computers, 13-20, 2013.
Physical activity monitoring has recently become an important topic in wearable computing, motivated by e.g. healthcare applications. However, new benchmark results show that the difficulty of the complex classification problems exceeds the potential of existing classifiers. Therefore, this paper proposes the ConfAdaBoost.M1 algorithm. The proposed algorithm is a variant of the AdaBoost.M1 that incorporates well established ideas for confidence based boosting. The method is compared to the most commonly used boosting methods using benchmark datasets from the UCI machine learning repository and it is also evaluated on an activity recognition and an intensity estimation problem, including a large number of physical activities from the recently released PAMAP2 dataset. The presented results indicate that the proposed ConfAdaBoost.M1 algorithm significantly improves the classification performance on most of the evaluated datasets, especially for larger and more complex classification tasks.
David Lindgren, Mehmet B. Guldogan, Fredrik Gustafsson, Hans Habberstad, Gustaf Hendeby, "Acoustic Source Localization in a Network of Doppler Shift Sensors", 16th International Conference on Information Fusion, 2013.
It is well-known that the motion of an acoustic source can be estimated from Doppler shift observations. It ishowever not obvious how to design a sensor network to efficiently deliver the localization service. In this work a rather simplistic motion model is proposed that is aimed at sensor networks with realistic numbers of sensor nodes. It is also described how to efficiently solve the associated least squares optimization problem by Gauss-Newton variable projection techniques, and how to initiate the numerical search from simple features extracted from the observed frequency series. The methods are demonstrated onreal data by determining the distance to a passing propellerdriven aircraft and by localizing an all-terrain vehicle. It is concluded that the processing components included are fairly mature for practical implementations in sensor networks.
Attila Reiss, Gustaf Hendeby, Didier Stricker, "Towards Robust Activity Recognition for Everyday Life: Methods and Evaluation", 7th International Conference on Pervasive Computing Technologies for Healthcare (PervasiveHealth), 2013, 25-32, 2013.
The monitoring of physical activities under realistic, everyday life conditions - thus while an individual follows his regular daily routine - is usually neglected or even completely ignored. Therefore, this paper investigates the development and evaluation of robust methods for everyday life scenarios, with focus on the task of aerobic activity recognition. Two important aspects of robustness are investigated: dealing with various (unknown) other activities and subject independency. Methods to handle these issues are proposed and compared, a thorough evaluation simulates usual everyday scenarios of the usage of activity recognition applications. Moreover, a new evaluation technique is introduced (leave-one-other-activity-out) to simulate when an activity recognition system is used while performing a previously unknown activity. Through applying the proposed methods it is possible to design a robust physical activity recognition system with the desired generalization characteristic.
Attila Reiss, Gustaf Hendeby, Didier Stricker, "A Competitive Approach for Human Activity Recognition on Smartphones", ESANN 2013, 455-460, 2013.
This paper describes a competitive approach developed for an activity recognition challenge. The competition was defined on a new and publicly available dataset of human activities, recorded with smartphone sensors. This work investigates different feature sets for the activity recognition task of the competition. Moreover, the focus is also on the introduction of a new, confidence-based boosting algorithm called ConfAda- Boost.M1. Results show that the new classification method outperforms commonly used classifiers, such as decision trees or AdaBoost.M1.
Saikat Saha, Gustaf Hendeby, Fredrik Gustafsson, "Noise Adaptive Particle Filtering: A Hierarchical Perspective", ISBA Regional Meeting and International Workshop/Conference on Bayesian Theory and Applications (IWCBTA), 6-10 January 2013, Varanasi, Uttar Pradesh, India, 2013.
Optimal estimation problems for general state space models do not typically admit a closed form solution. However, modern Monte Carlo methods have paved the way to solve such complex inference problems. Particle filters (PF) are a popular class of such Monte Carlo based Bayesian algorithms, which solve the estimation problems numerically in a sequential manner.
PF in general, assume a prior knowledge of the (process and observation) noise distributions involving the state space model, whereas the properties of the noise processes are often unknown for many practical problems. Furthermore, the unknown noise distributions may be state dependent or even non-stationary, which prevent the offline noise calibrations.
In this article, the unknown noises are assumed to be slowly varying in time. The article then proposes a hierarchical noise adaptive PF where a two tier PF is run, the top tier PF estimates the latent states from the streaming observations and the bottom tier PF estimates the noise statistics conditioned on the top tier PF output together with the observations. The estimates are statistically fused together for the inference purpose. In essence, it is an implementation of approximate Rao-Blackwellized PF, where the later is achieved through local Monte Carlo integration. This approach is very generic for different noise classes and importantly, it enhances the level of parallelism in PF implementations.
Gabriele Bleser, Gustaf Hendeby, "Using egocentric vision to achieve robust inertial body tracking under magnetic disturbances", 10th IEEE International Symposium on Mixed and Augmented Reality 26-29 October 2011, Basel, Switzerland, 103-109, 2011.
In the context of a smart user assistance system for industrial manipulation tasks it is necessary to capture motions of the upper body and limbs of the worker in order to derive his or her interactions with the task space. While such capturing technology already exists, the novelty of the proposed work results from the strong requirements of the application context: The method should be flexible and use only on-body sensors, work accurately in industrial environments that suffer from severe magnetic disturbances, and enable consistent registration between the user body frame and the task space. Currently available systems cannot provide this. This paper suggests a novel egocentric solution for visual-inertial upper-body motion tracking based on recursive filtering and model-based sensor fusion. Visual detections of the wrists in the images of a chest-mounted camera are used as substitute for the commonly used magnetometer measurements. The on-body sensor network, the motion capturing system, and the required calibration procedure are described and successful operation is shown in a real industrial environment.
Markus Weber, Gabriele Bleser, Gustaf Hendeby, Attila Reiss, Didier Stricker, "Unsupervised model generation for motion monitoring", Proceedings of the IEEE International Conference on Systems, Man, and Cybernetics (SMC), IEEE International Conference on Systems, Man, and Cybernetics. Conference Proceedings, 2011.
This paper addresses two fundamental requirements of full body motion monitoring: (a) the ability to sense the input of the user and (b) the means to interpret the captured input. Appropriate technology in both areas is required for an interactive virtual reality system to provide feedback in a useful and natural way. This paper combines technologies for both areas: It develops a sensor fusion approach for capturing user input based on miniature on-body inertial and magnetic motion sensors. Furthermore, it presents work in progress to automatically generate models for motion patterns from the captured input. The technology is then used and evaluated in the context of a personalized virtual rehabilitation trainer application.
Attila Reiss, Gustaf Hendeby, Gabriele Bleser, Didier Stricker, "Activity Recognition Using Biomechanical Model Based Pose Estimation", Smart Sensing and Context, 2010, Lecture Notes in Computer Science, Vol. 6446, 42-55, 2010.
In this paper, a novel activity recognition method based on signal-oriented and model-based features is presented. The model-based features are calculated from shoulder and elbow joint angles and torso orientation, provided by upper-body pose estimation based on a biomechanical body model. The recognition performance of signal-oriented and model-based features is compared within this paper, and the potential of improving recognition accuracy by combining the two approaches is proved: the accuracy increased by 4–6% for certain activities when adding model-based features to the signal-oriented classifier. The presented activity recognition techniques are used for recognizing 9 everyday and fitness activities, and thus can be applied for e.g., fitness applications or 'in vivo' monitoring of patients.
Gabriele Bleser, Gustaf Hendeby, "Using optical flow for filling the gaps in visual-inertial tracking", European Signal Processing Conference (EUSIPCO 2010), August 23-27, 2010, Aalborg, Denmark, European Signal Processing Conference, 2010.
Egomotion tracking is since the last decades an often addressed problem and hybrid approaches evidentially have potential to provide accurate, efficient and robust results. Simultaneous localisation and mapping (SLAM) - in contrast to a model-based approach - is used to enable tracking in unknown environments. However, it also suffers from high computational complexity. Moreover, in many applications, the map itself is not needed and the target environment is partiall known, e.g. in a few 3D anchor points. In this paper, rather than using SLAM, optical flow measurements are introduced into a model-based system. With these measurements, a modified visual-inertial tracking method is derived, which in Monte Carlo simulations reduces the need for 3D points and thus allows tracking during extended gaps of 3D point registrations.
Gustaf Hendeby, Gabriele Bleser, Illias Lamprinos, Didier Stricker, "Healthy aging using physical activity monitoring", ALLIANCE Conference, February 28 - March 3, 2010, San Antonio, USA, 2010.
Gabriele Bleser, Gustaf Hendeby, "Using optical flow as lightweight SLAM alternative", Mixed and Augmented Reality, 2009, 175-176, 2009.
Visual simultaneous localisation and mapping (SLAM) is since the last decades an often addressed problem. Online mapping enables tracking in unknown environments. However, it also suffers from high computational complexity and potential drift. Moreover, in augmented reality applications the map itself is often not needed and the target environment is partially known, e.g. in a few 3D anchor or marker points. In this paper, rather than using SLAM, measurements based on optical flow are introduced. With these measurements, a modified visual-inertial tracking method is derived, which in Monte Carlo simulations reduces the need for 3D points and allows tracking for extended periods of time without any 3D point registrations.
Gustaf Hendeby, Fredrik Gustafsson, "On Nonlinear Transformations of Stochastic Variables and its Application to Nonlinear Filtering", Proceedings of the '08 IEEE International Conference on Acoustics, Speech and Signal Processing, 3617-3620, 2008.
A class of nonlinear transformation-based filters (NLTF) for state estimation is proposed. The nonlinear transformations that can be used include first (TT1) and second (TT2) order Taylor expansions, the unscented transformation (UT), and the Monte Carlo transformation (MCT) approximation. The unscented Kalman filter (UKF) is by construction a special case, but also nonstandard implementations of the Kalman filter (KF) and the extended Kalman filter (EKF) are included, where there are no explicit Riccati equations. The theoretical properties of these mappings are important for the performance of the NLTF. TT 2 does by definition take care of the bias and covariance of the second order term that is neglected in the TT 1 based EKF. The UT computes this bias term accurately, but the covariance is correct only for scalar state vectors. This result is demonstrated with a simple example and a general theorem, which explicitly shows the difference between TT 1, TT 2, UT, and MCT.
Gustaf Hendeby, Rickard Karlsson, Fredrik Gustafsson, "A New Formulation of the Rao-Blackwellized Particle Filter", Proceedings of the 14th IEEE/SP Statistical Signal Processing Workshop, 84-88, 2007.
For performance gain and efficiency it is important to utilize model structure in particle filtering. Applying Bayes- rule, present linear Gaussian substructure can be efficiently handled by a bank of Kalman filters. This is the standard formulation of the Rao-Blackwellized particle filter (RBPF), by some authors denoted the marginalized particle filter (MPF), and usually presented in a way that makes it hard to implement in an object oriented fashion. This paper discusses how the solution can be rewritten in order to increase the understanding as well as simplify the implementation and reuse of standard filtering components, such as Kalman filter banks and particle filters. Calculations show that the new algorithm is equivalent to the classical formulation, and the new algorithm is exemplified in a target tracking simulation study.
Gustaf Hendeby, Jeroen Hol, Rickard Karlsson, Fredrik Gustafsson, "A Graphics Processing Unit Implementation of the Particle Filter", Proceedings of the 15th European Statistical Signal Processing Conference, European Signal Processing Conference, 1639-1643, 2007.
Modern graphics cards for computers, and especially their graphics processing units (GPUs), are designed for fast rendering of graphics. In order to achieve this GPUs are equipped with a parallel architecture which can be exploited for general-purpose computing on GPU (GPGPU) as a complement to the central processing unit (CPU). In this paper GPGPU techniques are used to make a parallel GPU implementation of state-of-the-art recursive Bayesian estimation using particle filters (PF). The modifications made to obtain a parallel particle filter, especially for the resampling step, are discussed and the performance of the resulting GPU implementation is compared to one achieved with a traditional CPU implementation. The resulting GPU filter is faster with the same accuracy as the CPU filter for many particles, and it shows how the particle filter can be parallelized.
Gustaf Hendeby, Rickard Karlsson, "Target Tracking Performance Evaluation - A General Software Environment for Filtering", Proceedings of the 2007 IEEE Aerospace Conference, 1-13, 2007.
In this paper, several recursive Bayesian filtering methods for target tracking are discussed. Performance for target tracking problems is usually measured using the second-order moment. For nonlinear or non-Gaussian applications, this measure is not always sufficient. The Kullback divergence is proposed as an alternative to mean square error analysis, and it is extensively used to compare estimated posterior distributions for various applications. The important issue of efficient software development, for nonlinear and non-Gaussian estimation, is also addressed. A new framework in C++ is detailed. Utilizing modern design techniques an object oriented filtering and simulation framework is provided to allow for easy and efficient comparisons of different estimators. The software environment is extensively used in several applications and examples.
Gustaf Hendeby, Fredrik Gustafsson, "Fundamental Filtering Limitations in Linear Non-Gaussian Systems", Proceedings of Reglermöte 2006, 2006.
The Kalman filter is known to be the optimal linear filter for linear non-Gaussian systems. However, nonlinear filters such as Kalman filter banks and more recent numerical methods such as the particle filter are sometimes superior in performance. Here a procedure to a priori decide how much can be gained using nonlinear filters, without having to resort to Monte Carlo simulations, is outlined. The procedure is derived in terms of the posterior Cramer-Rao lower bound. Results are shown for a class of standard distributions and models in practice.
Gustaf Hendeby, Fredrik Gustafsson, "Detection Limits for Linear Non-Gaussian State-Space Models", Proceedings of the 6th IFAC Symposium on Fault Detection, Supervision and Safty of Technical Processes, 282-287, 2006.
The performance of nonlinear fault detection schemes is hard to decide objectively, so Monte Carlo simulations are often used to get a subjective measure and relative performance for comparing different algorithms. There is a strong need for a constructive way of computing an analytical performance bound, similar to the Cramér-Rao lower bound for estimation. This paper provides such a result for linear non-Gaussian systems. It is first shown how a batch of data from a linear state-space model with additive faults and non-Gaussian noise can be transformed to a residual described by a general linear non-Gaussian model. This also involves a parametric description of incipient faults. The generalized likelihood ratio test is then used as the asymptotic performance bound. The test statistic itself may be impossible to compute without resorting to numerical algorithms, but the detection performance scales analytically with a constant that depends only on the distribution of the noise. It is described how to compute this constant, and a simulation study illustrates the results.
Gustaf Hendeby, Rickard Karlsson, Fredrik Gustafsson, Neil Gordon, "Performance Issues in Non-Gaussian Filtering Problems", Proceedings of the 2006 IEEE Nonlinear Statistical Signal Workshop, 65-68, 2006.
Performance for many filtering problems is usually measured using the second order moment. For non-Gaussian application this measure is not always sufficient. In the paper the Kullback divergence is extensively used to compare distributions. Several estimation techniques are compared, and methods such as the particle filter are shown to give superior performance over some classical second-order estimators.
Gustaf Hendeby, Rickard Karlsson, Fredrik Gustafsson, Neil Gordon, "Recursive Triangulation Using Bearings-Only Sensors", Proceedings of the 2006 IEE Seminar on Target Tracking: Algorithms and Applications, 3-10, 2006.
Recursive triangulation, using a bearings-only sensor, is investigated for a fly-by scenario. In a simulation study, several estimators are compared, fundamental estimation limits are calculated for different measurement noise assumptions. The quality of the estimated state distributions is evaluated.
Gustaf Hendeby, Fredrik Gustafsson, "Fundamental Fault Detection Limitations in Linear Non-Gaussian Systems", Proceedings of the 44th IEEE Conference on Decision and Control and European Control Conference, 338-343, 2005.
Sophisticated fault detection (FD) algorithms often include nonlinear mappings of observed data to fault decisions, and simulation studies are used to support the methods. Objective statistically supported performance analysis of FDalgorithms is only possible for some special cases, including linear Gaussian models. The goal here is to derive general statistical performance bounds for any FD algorithm, given a nonlinear non-Gaussian model of the system. Recent advances in numerical algorithms for nonlinear filtering indicate that such bounds in many practical cases are attainable. This paper focuses on linear non-Gaussian models. A couple of different fault detection setups based on parity space and Kalman filter approaches are considered, where the fault enters a computable residual linearly. For this class of systems, fault detection can be based on the best linear unbiased estimate (BLUE) of the fault vector. Alternatively, a nonlinear filter can potentially compute the maximum likelihood (ML) state estimate, whose performance is bounded by the Cramér-Rao lower bound (CRLB). The contribution in this paper is general expressions for the CRLB for this class of systems, interpreted in terms offault detectability. The analysis is exemplified for a case with measurements affected by outliers.
Gustaf Hendeby, Fredrik Gustafsson, "Fundamental Filtering Limitations in Linear Non-Gaussian Systems", Proceedings of the 16th IFAC World Congress, 45-45, 2005.
The Kalman filter is known to be the optimal linear filter for linear non-Gaussian systems. However, nonlinear filters such as Kalman filter banks and more recent numerical methods such as the particle filter are sometimes superior in performance. Here a procedure to a priori decide how much can be gained using nonlinear filters, without having to resort to Monte Carlo simulations, is outlined. The procedure is derived in terms of the posterior Cramér-Rao lower bound. Results are shown for a class of standard distributions and models in practice.
Gustaf Hendeby, Fredrik Gustafsson, "On Performance Measures for Approximative Parameter Estimation", Proceedings of Reglermöte 2004, 2004.
The Kalman filter computes the minimum variance state estimate as a linear function of measurements in the case of a linear model with Gaussian noise processes. There are plenty of examples of non-linear estimators that outperform the Kalman filter when the noise processes deviate from Gaussianity, for instance in target tracking with occasionally maneuvering targets. Here we present, in a preliminary study, a detailed analysis of the well-known parameter estimation problem. This time with Gaussian mixture measurement noise. We compute the discrepancy of the best linear unbiased estimator BLUE and the Cramer-Rao lower bound, and based on this conclude when computationally intensive Kalman filter banks or particle filters may be used to improve performance.
Gustaf Hendeby, "Performance and Implementation Aspects of Nonlinear Filtering", Linköping Studies in Science and Technology. Dissertations, No. 1161, 2008.
* Hur utvärderar man hur bra ett filter eller en detektor fungerar?
* Vad skiljer olika metoder åt och vad betyder det för deras egenskaper?
* Hur programmerar man de datorer som används för att utvinna informationen?
Det mått som oftast används för att tala om hur effektivt ett filter fungerar är RMSE (root mean square error), som i princip är ett mått på hur långt ifrån det korrekta tillståndet man i medel kan förvänta sig att den skattning man får är. En fördel med att använda RMSE som mått är att det begränsas av Cramér-Raos undre gräns (CRLB). Avhandlingen presenterar metoder för att bestämma vilken betydelse olika brusfördelningar har för CRLB. Brus är de störningar och fel som alltid förekommer när man mäter eller försöker beskriva ett beteende, och en brusfördelning är en statistisk beskrivning av hur bruset beter sig. Studien av CRLB leder fram till en analys av intrinsic accuracy (IA), den inneboende noggrannheten i brus. För lineära system får man rättframma resultat som kan användas för att bestämma om de mål som satts upp kan uppnås eller inte. Samma metod kan också användas för att indikera om olineära metoder som partikelfiltret kan förväntas ge bättre resultat än lineära metoder som kalmanfiltret. Motsvarande metoder som är baserade på IA kan även användas för att utvärdera detektionsalgoritmer. Sådana algoritmer används för att upptäcka fel eller förändringar i ett system.
producerar skilja sig väldigt mycket åt beroende på vilket brus det studerade systemet utsätts för. Dessa skillnader kan vara betydelsefulla i vissa fall. Som ett alternativ till RMSE används därför här kullbackdivergensen som tydligt visar på bristerna med att bara förlita sig på RMSE-analyser. Kullbackdivergensen är ett statistiskt mått på hur mycket två fördelningar skiljer sig åt.
Två filtreringsalgoritmer har analyserats mer i detalj: det rao-blackwelliserade partikelfiltret (RBPF) och den metod som kallas unscented Kalman filter (UKF). Analysen av RBPF leder fram till ett nytt sätt att presentera algoritmen som gör den lättare att använda i ett datorprogram. Dessutom kan den nya presentationen ge bättre förståelse för hur algoritmen fungerar. I undersökningen av UKF ligger fokus på den underliggande så kallade unscented transformation som används för att beskriva vad som händer med en brusfördelning när man transformerar den, till exempel genom en mätning. Resultatet består av ett antal simuleringsstudier som visar på de olika metodernas beteenden. Ett annat resultat är en jämförelse mellan UT och Gauss approximationsformel av första och andra ordningen.
Den här avhandlingen beskriver även en parallell implementation av ett partikelfilter samt ett objektorienterat ramverk för filtrering i programmeringsspråket C ++. Partikelfiltret har implementerats på ett grafikkort. Ett grafikkort är ett exempel på billig hårdvara som sitter i de flesta moderna datorer och mest används för datorspel. Det används därför sällan till sin fulla potential. Ett parallellt partikelfilter, det vill säga ett program som kör flera delar av partikelfiltret samtidigt, öppnar upp för nya tillämpningar där snabbhet och bra prestanda är viktigt. Det objektorienterade ramverket för filtrering uppnår den flexibilitet och prestanda som behövs för storskaliga Monte-Carlo-simuleringar med hjälp av modern mjukvarudesign. Ramverket kan också göra det enklare att gå från en prototyp av ett signalbehandlingssystem till en slutgiltig produkt.
Gustaf Hendeby, "Fundamental Estimation and Detection Limits in Linear Non-Gaussian Systems", Linköping Studies in Science and Technology. Thesis, No. 1199, 2005.
A lower bound for the covariance of the estimation error for any unbiased estimator s given by the Cramér-Rao lower bound (CRLB). At the same time, the Kalman filter is the best linear unbiased estimator (BLUE) for linear systems. It is in this thesis shown that the CRLB and the BLUE performance are given by the same expression, which is parameterized in the intrinsic accuracy of the noise. How the performance depends on the noise is then used to indicate when nonlinear filters, e.g., a particle filter, should be used instead of a Kalman filter. The CRLB results are shown, in simulations, to be a useful indication of when to use more powerful estimation methods. The simulations also show that other techniques should be used as a complement to the CRLB analysis to get conclusive performance results.
Gustaf Hendeby, Rickard Karlsson, "Target Tracking Performance Evaluation - A General Software Environment for Filtering", LiTH-ISY-R, No. 2767, 2007.
Gustaf Hendeby, Rickard Karlsson, Fredrik Gustafsson, "A New Formulation of the Rao-Blackwellized Particle Filter", LiTH-ISY-R, No. 2813, 2007.
Gustaf Hendeby, Jeroen Hol, Rickard Karlsson, Fredrik Gustafsson, "A Graphics Processing Unit Implementation of the Particle Filter", LiTH-ISY-R, No. 2812, 2007.
Gustaf Hendeby, Fredrik Gustafsson, "On Nonlinear Transformations of Stochastic Variables and its Application to Nonlinear Filtering", LiTH-ISY-R, No. 2828, 2007.
Gustaf Hendeby, Rickard Karlsson, Fredrik Gustafsson, Neil Gordon, "Recursive Triangulation Using Bearings-Only Sensors", LiTH-ISY-R, No. 2729, 2006.
Gustaf Hendeby, Rickard Karlsson, Fredrik Gustafsson, Neil Gordon, "Performance Issues in Non-Gaussian Filtering Problems", LiTH-ISY-R, No. 2737, 2006.
Gustaf Hendeby, Jeroen Hol, Rickard Karlsson, Fredrik Gustafsson, "Graphics Processing Unit Implementation of the Particle Filter", LiTH-ISY-R, No. 2749, 2006.
Gustaf Hendeby, Fredrik Gustafsson, "Detection Limits for Linear Non-Gaussian State-Space Models", LiTH-ISY-R, No. 2760, 2006.
Gustaf Hendeby, Fredrik Gustafsson, "Fundamental Filtering Limitations in Linear Non-Gaussian Systems", LiTH-ISY-R, No. 2681, 2005.
Gustaf Hendeby, Fredrik Gustafsson, "Fundamental Fault Detection Limitations in Linear Non-Gaussian Systems", LiTH-ISY-R, No. 2709, 2005.
Gustaf Hendeby, Fredrik Gustafsson, "On Performance Measures for Approximative Parameter Estimation", LiTH-ISY-R, No. 2608, 2004.
Gustaf Hendeby, Fredrik Gustafsson, "Fundamental Filtering Limitations in Linear Non-Gaussian Systems", LiTH-ISY-R, No. 2640, 2004.
Gustaf Hendeby, "Development and Evaluation of an Active Radio Frequency Seeker Model for a Missile with Data-Link Capability", Student thesis, LiTH-ISY-Ex No. 3309, 2002.
To develop and maintain a modern combat aircraft it is important to have simple, yet accurate, threat models to support early stages of functional development. Therefore this thesis develops and evaluates a model of an active radio frequency (RF) seeker for a missile with data-link capability. The highly parametrized MATLAB-model consists of a pulse level radar model, a tracker using either interacting multiple models (IMM) or particle filters, and a guidance law.
Monte Carlo simulations with the missile model indicate that, under the given conditions, the missile performs well (hit rate>99%) with both filter types, and the model is relatively insensitive to lost data-link transmissions. It is therefore under normal conditions not worthwhile to use the more computer intense particle filter today, however when the data-link degrades the particle filter performs considerably better than the IMM filter. Analysis also indicate that the measurements generated by the radar model are neither independent, white nor Gaussian. This contradicts the assumptions made in this, and many other radar applications. However, the performance of the model suggests that the assumptions are acceptable approximations of actual conditions, but further studies within this are recommended to verify this.
Torkel Glad, Gustaf Hendeby (editors), Forever Ljung in System Identification, Studentlitteratur, Lund 2006.


text:
Q: How to temporarily hide toolbar menu I have host activity which can have different fragments, it is some sort of SingleFragmentActivity, so user navigating between different fragments inside this activity, but inside my menu I have button that brings user to the another fragment, so I need to hide menu when fragment is replaced and restore it when user goes back to the previous fragment.
I have tried to clear menu, it works, but how can I restore menu than on previous fragment ?
In code this looks like
   public void onAttach(Activity activity) {
        super.onAttach(activity);
        try {
            mToolbarProvider = (ToolbarProvider) activity;
          //  mToolbarProvider.saveCurrentMenu();
            mToolbarProvider.getToolbar().getMenu().clear();

        }
        catch (ClassCastException ex) {
            Log.e(getString(R.string.error_tag), "Activty has to implement " + ToolbarProvider.class.getSimpleName() + " interface");
        }
    }

This work, but when I am back again to the fragment that needs menu, how can I restore menu, I have tried to save menu object, but doesn't work for me.
   @Override
    public void onAttach(Activity activity) {
        super.onAttach(activity);
        try {
            mActivityController = (ActivityController) activity;
            mToolbarProvider = (ToolbarProvider) activity;
           /* Menu lastMenu = mToolbarProvider.restoreLastMenu();
            if(lastMenu!=null) {
                activity.onCreateOptionsMenu(lastMenu);
            }*/
            Menu toolBarMenu = mToolbarProvider.restoreLastMenu();
            if(toolBarMenu!=null) {
                mToolbarProvider.getToolbar().inflateMenu(R.menu.menu_main);
            }

        } catch (ClassCastException ex) {
            Log.e(getString(R.string.error_tag), "Activty has to implement " + ActivityController.class.getSimpleName() + " interface");
        }
    }

It would be better just to hide it and show when I need this.
Please help to implement this.
EDIT
As suggested below, I have tried to do this and first time it didn't work , but I have moved logic into onCreateView , I have really forgotten that I am doing everything in onAttach, that is called only once. Really stupid mistake.
So now everything works like a charm.
Here is code.
In onCreateView() in my fragment where I need to hide menu.
  Menu menu = mToolbarProvider.getToolbar().getMenu();
        MenuItem menuItem = menu.findItem(R.id.action_settings);
        if(menuItem!=null) {
            menuItem.setVisible(false);
            mToolbarProvider.addHiddenItem(menuItem);
        }

And in main fragment where all menu items are visible.
List<MenuItem> hiddenItemsList = mToolbarProvider.getAllHiddenItems();
    if(hiddenItemsList!=null && hiddenItemsList.size()>0) {
        int size = hiddenItemsList.size();
        for(int i=0;i<size;i++) {
            hiddenItemsList.get(i).setVisible(true);
        }
    }

Or you create method like setAllItemsVisible()

A: you can try hide menu item by using menuItem.setVisible(false); and to show them again menuItem.setVisible(true);

redpajama_set_name: RedPajamaStackExchange


Funkmaster V's Uptown Cabs of Renown: Governor Funk!
Entertainer Funkmaster V is running for TN State Governor... but why?
First, he wants to provide an option for Tennessee voters who want representation that will advance the agendas of peace, liberty, common sense, smaller government, and freedom.
Secondly, its to bring awareness to a ballot access nightmare in the state of Tennessee. Public servants that want to run as a Democrat, Independent, or Republican, need only 25 signatures to be recognized by their party affiliation, all other parties this year need more than 33,000. This simply isn't fair, and it needs to change.
Vinnie Vineyard will be on the ballot as an independent. But, he is not an independent, he is a Libertarian. Get on the Funk train!


text:
When Dogs Heal: Post-Traumatic Stress Disorder
June 30, 2015 By Christina Garofalo Uncategorized No Comments
We know that dogs are able to help people overcome anxiety and depression, and that they're able to help people feel more connected to their communities. Yet there has been little research done to show how dogs might be able to bring that same therapeutic value to soldiers coming back from war, who might be dealing with similar challenges as a result of Post-Traumatic Stress Disorder (PTSD).
Now, thanks to Paws for Purple Hearts — launched in 2008 by a social worker named Rick Yount — people are starting to pay attention.
Paws for Purple Hearts arranges for a veteran to spend six weeks with a dog, training it to be a mobility-assistance animal for a physically disabled veteran. The reason why it's been so successful is that the training not only benefits the person receiving the dog; it also benefits the trainer.
Smithsonian Magazine recently highlighted the program and its effect on Robert Soliz, a former army specialist who, after coming home from Baghdad, struggled to show affection to his children — a common hurdles for people dealing with PTSD. After spending six weeks training a golden retriever through Paws for Purple Hearts, Soliz says he began to feel more comfortable with his family and found that his life had started to go back to the way it was before leaving for war.
In teaching vets to train service dogs, the program has been shown to improve a patient's ability to communicate by being assertive but not aggressive. The animals also fight the tendency for isolation, and having to praise the dogs has helped traumatized veterans overcome emotional numbness.
Yount and his team have played in integral role in getting canine caretaking recognized by congress. A study is now underway in Florida to assess the effectiveness of the therapy used by Paws for Purple Hearts in treating those with PTSD. Yount hopes that the results will provide the scientific evidence needed to get bring this therapy to more people.
Fred Says gives $50,000 to organizations working with HIV+ youth around the U.S December 11, 2016
Camille & Co.: Grateful for the Little Things April 15, 2016
Sharing Warmth and Teaching Patience April 8, 2016
Who Rescued Whom? Melissa & Stan March 25, 2016
The One Who Caught My Heart: Charles & Samson March 11, 2016
The Nurse At My Right Side: Hannia & Danna February 26, 2016
My Survivor: Thomas & Daisy February 12, 2016
A Special Knack for Healing: Seven & Rosey January 22, 2016
The Dog That Give Me Back the Night: Alison & Sebastian January 8, 2016
The Dog Who Saved 1,000 Lives August 3, 2015
How Canines Can Help the Classroom August 3, 2015
A Hotel Doorman, with the Help of a Dog, Changes the Life of a Sick Guest June 30, 2015
A Dog with Three Paws Gives a Little Girl Hope June 30, 2015
Dogs in Prison: How this LA Non-Profit is Transforming Lives June 30, 2015
Therapy Dogs Can Now Help Your Child Learn to Read June 30, 2015
© WHEN DOGS HEAL, 2020. Copyright 2015 - When Dogs Heal Project

redpajama_set_name: RedPajamaCommonCrawl


text:
Kamala Harris Reappears and Immediately Makes a Mess of Things
In recent weeks, we haven't seen Vice-President Kamala Harris as much.
Although it's not necessarily bad considering her penchant for making cringeworthy word salads and embarrassing the United States on a global stage, it doesn't mean she's completely out of the ordinary.
In November, Harris spent some time on Twitter, posting photos and videos of her family and trips to other countries. It was a tweet about vaccines she posted Monday that attracted a lot of attention, especially after Health and Human Secretary Xavier Becerra posted a similar one the next day that seemed to contradict Harris.
Harris tweeted, "One shot once a year–that's it for most people to remain protected from COVID year long," with a link to vaccines.gov.
One shot, once a year—that's all most people will need to stay protected from COVID year-long. Make a plan to get your shot at https://t.co/ddwWZdNCgg.
— Vice President Kamala Harris (@VP) November 28, 2022
Becerra, on the contrary, suggested that people who haven't had a shot for more than two months should get one immediately to help them avoid the worst effects of COVID. This message was targeted at those over 50, who according to the CDC are most susceptible to dying from severe coronavirus cases.
An updated COVID vaccine can help protect you from the worst outcomes of COVID. If it's been over 2 months since your last dose, make a plan to get one now.
Find updated vaccines at https://t.co/b0lnuggpPW. pic.twitter.com/MQUdE921Du
— Secretary Xavier Becerra (@SecBecerra) November 29, 2022
Which one is the best? Do you want one every two months or once a year? Mixed messaging caused confusion and some wondered what the science behind the different claims was.
Yesterday the Vice President @VP told us that a covid booster is good for a year. Today the health secretary is telling us it's only good for two months. Nobody will tell us its actual benefits or risks.
How can we be expected to believe a word from this administration? https://t.co/391AjtcCZ0
— Sarah Beth Burwick (@sarahbeth345) November 29, 2022
Others pointed out that the vaccine does not prevent you from getting it again. However, the CDC states it can help you avoid having to deal with a severe case. Many who replied to Becerra's message wondered when exactly the every-two-month thing began.
Instead of listening, I decided to go directly to the CDC website. There was more information and I was directed to different links, much like how you are transferred from one person to another during a call to your insurance provider or cell phone provider.
One page gives you information on how to stay up-to-date with vaccines and boosters. It also directs to another page for people who are "moderately to severely immunocompromised". Below that, you will find drop-down dosage recommendations. None of these recommend more than four doses, including the two that were promoted heavily in 2021.
It is confusing, but it is best to remember one thing. Instead of listening to politicians or other public health officials giving mixed messages about what you should do, especially those who weakened the vaccine at the time it was politically convenient, then changed their tune after 2020, talk to your doctor if you have any questions or concerns.
It's as easy as that.
Although this should not be taken as medical advice, I know of people over 50 who received the first two Pfizer shots along with the 1st booster. However, they were advised to skip the fourth dose due to insufficient evidence. One case involved a doctor telling the patient that they had sufficient protection by getting the first two shots and surviving COVID.
Every case is unique, so it is important to speak to a trusted medical professional. They should be able to point you in the right direction, and not officials from the government.
Previous articleCommon Assistance for Housing
Next articleBiden Descends Into Fantasyland on the Supply Chain and Football


I just got back a few hours ago from the most wonderful author event put on by Books Inc.'s, Not Your Mother's Book Club, and picked up some awesome sounding YA books. As an added cherry on top of the event, the wonderful woman who organized the event suggested a few books for my four year old. They were all ones that I had my eye one except for Stuck by Oliver Jeffers. So I flipped through all her picks and finally went through Stuck and knew I just had to buy it. I put it on top of my things so I would remember to pay for it on my way out. At different times the other 3 children's/YA book specialists from the various Books Inc. stores saw the book and raved about it so I was feeling good about my choice.
It is the cutest story that starts off with a little boy, Lloyd, getting his kite stuck in a tree. He starts off throwing his favorite shoe to try and get it down, then proceeds on with more and more outlandish things like his cat, his neighbor's house, a whale, etc. The illustrations are adorable and I love how in addition to the story telling, the characters in the illustrations have little blurbs that my daughter enjoyed going through. For most of the book both my daughter and I were giggling especially when Lloyd pulls out things like a ladder and instead of using it to climb the tree he instead throws it into the tree and of course… it gets stuck.
As soon as we finished my daughter was lifting the flap of the back cover hoping for more and when she realized there wasn't any more she begged to read it again. I will admit despite it being past her bedtime and having read the set number of books I usually limit her to at bedtime I gave in and read it again because I enjoyed the book that much as well.
As we said our goodnights I teased my daughter about all the things in her bed she could throw up to help get everything out of the tree and I am sure we will be reading this one again (multiple times) tomorrow. Now I have to brainstorm about fun activities I can put together to go along with this book. Any suggestions?
So I think my problem was that it says to use the Betty Crocker Sugar Cookie mix which I didn't have. So I went hunting for sugar cookie recipes. I ended up using this Wilton cookie recipe and didn't notice until I got to almost the last step where it says the dough will be very stiff. So of course that doesn't lend itself to rolling it out and then swirling it. I really had to squish the dough together and then it didn't bake evenly so I ended up flattening them out. So next time I plan on trying a different sugar cookie recipe. Suggestions are welcome!
The other problem was getting the dough the proper color without overworking the dough. I used the neon colored food coloring like the recipe called for but getting it to blend nicely was hard. A friend did just suggest that if you have a stand mixer it would be easier but I was mashing it in by hand.
Anyhow, they didn't turn out how they were supposed to look but my daughter thought they were tasty. I had planned to send her to school with these tomorrow to celebrate Dr. Seuss's birthday but guess I will end up keeping them at home for the kids and try again next year.


text:
Bjørn Skogmo (born 12 December 1940) is a Norwegian diplomat.

He was born in Namsos, and is a cand.polit. by education. He started working for the Norwegian Ministry of Foreign Affairs in 1969. He served as the Norwegian ambassador to the United Nations in Geneva from 1994 to 2002, assisting permanent under-secretary of state in the Ministry of Foreign Affairs from 2002 to 2005 and Norwegian ambassador to France from 2005 to 2009.

References

1940 births
Living people
Norwegian civil servants
Ambassadors of Norway to France
People from Namsos
Permanent Representatives of Norway to the United Nations

redpajama_set_name: RedPajamaWikipedia


text:
Lundbæk er en gammel hovedgård, som nævnes første gang i 1450. Gården ligger i Bislev Sogn, Hornum Herred, Aalborg Kommune. Hovedbygningen er opført i 1804. Lundbæk har siden 1948 været landbrugsskole.

Lundbæk Gods er på 28 hektar. Lundbæk Avlsgård er på 129 hektar.

Ejere af Lundbæk
(1450-1540) Vitskøl Kloster
(1540-1552) Mikkel Nielsen Tornekrans
(1552-1603) Christopher Mikkelsen Tornekrans
(1603-1604) Dorthe Axel Juul gift Tornekrans
(1604-1627) Iver Axelsen Juul
(1627-1679) Ove Iversen Juul
(1679-1690) Christian Ovesen baron Juel-Rysensteen
(1690-1694) Jeanne Henriksdatter Rüse gift (1) Rantzau (2) Juul-Rysensteen (3) Daa
(1694-1712) Gregers Valdemarsen Daa
(1712-1735) Ove Henriksen baron Juul-Rysensteen
(1735-1769) Otto Henrik Ovesen baron Juul-Rysensteen
(1769-1782) Christian Frederik Ovesen baron Juul-Rysensteen
(1782-1789) Christiane Dorothea Mohrsen gift (1) Juul-Rysensteen (2) von Adeler
(1789-1842) Christian Frederik Christiansen baron Juul-Rysensteen
(1842-1889) Niels Christiansen baron Juul-Rysensteen
(1889-1907) Christian Frederik Adrian Nielsen baron Juul-Rysensteen
(1907-1917) Vibeke baronesse Juul-Rysensteen gift baronesse Gyldencrone
(1917) Niels Kaas
(1917-1922) Erik Heiberg
(1922-1932) Kay Iver Andersen
(1932-1939) Olaf Kirketerp-Møller
(1939) Slægten Kirketerp-Møller
(1939) Statens Jordlovsudvalg
(1939-1947) Laurenz Westerby (hovedbygningen)
(1939-1940) Laurenz Westerby (avlsgården)
(1940-1949) H. Thorndahl (avlsgården)
(1949-1965) P. Pedersen (avlsgården)
(1965-) Vagn Christensen (avlsgården)
(1947-1948) Aalborg Amts Landboforening (hovedbygningen)
(1948-) Lundbæk Landbrugsskole (hovedbygningen)

Tordenkalven
Vagabonden Tordenkalven, der bl.a. er beskrevet i Johannes V. Jensens Himmerlandshistorier, var ansat på Lundbæk, da han blev krøbling efter at være kastet af en ustyrlig hest.

Lundbæk trinbræt
Lundbæk fik billetsalgssted på Aars-Nibe-Svenstrup Jernbane (1899-1969), som i 1910 blev forlænget fra Aars til Hvalpsund. Der blev solgt billetter fra baneformandshuset, men der var ringe trafik, og billetsalget ophørte i 1921, hvor Lundbæk blev nedsat til trinbræt. Stationsbygningen blev solgt nogle år før banens lukning Den er bevaret på Algade 5, men har fået tilføjet en tilbygning, et par kviste og en vinterhave, der forbinder hovedbygning og retirade. Naturstien Nibe-Hvalpsund, som Naturstyrelsen har anlagt på det nedlagte banetracé, passerer lige forbi.

Noter

Eksterne kilder/henvisninger
 J.P. Trap: Danmark 5.udgave, Kraks Landbrug
 Lundbæk Landbrugsskole

Fredede slotte og herregårde i Danmark
Herregårde i Aalborg Kommune
Herregårde i Aalborg Amt
Landbrugsskoler i Danmark


With over 20 years of experience in the field of advertising, england provides solutions for every sort of business, from major city banking corporations, to dog food producers, we've covered a lifetimes-worth of work, while breaking quite a fair few boundaries in the process.
Digital communication is at the centre of our daily lives and it's at the centre of england too. Not a bolt on extra, digital is integral to the way we think and behave.
Having a website without optimisation is like opening a shop on a backstreet and not telling anyone. On a Bank Holiday. With our in-house experts we'll have you found in no time.
At england, we believe that PR communications have the power to transform a client's business. Our goal is to help lead clients through the ever-changing landscape – one that is influenced by technology, culture and the economy.
There are over 70 million mobile handsets in the UK alone – that's more than one for every person! So why aren't you using mobile marketing?
It's our job to carefully select the best channels to reach your customers when they're most receptive to your message. Then we get you a great deal.
Outdoors, indoors, 100 people or 100,000, it's all about being organised. Remember your wedding? Took ages to arrange didn't it? Whatever the event we'll make it happen, with imagination.
Good design is about making things useable, unobtrusive, aesthetic and easier to understand. Good design just works better whether it's a website, a brochure or a vacuum cleaner.
What's a brand? It's shorthand for what you sell and why people should buy it. We're here to create you a shorthand, that more people will understand, first time.
Communications without strategy is like a rudderless ship. With no compass. Or a captain. It's an expensive way to go nowhere in particular. Let us plan your voyage instead.
View some of the stuff that's been making us tick.


Student takes a practice exam in his PSAT practice booklet. Ohio law requires that schools administer ACT or SAT to all grade 11 students and pays for the administration but does not require or support the PSAT.
Sophomores and juniors will take the Preliminary Scholastic Aptitude Test Oct. 10, while freshmen and seniors stay home.
The PSATs are a practice test for the SATs and a qualifying test for the National Merit Scholarship. Students who score in the top 1 percent of PSAT results compete nationally for nearly $6.5 million in scholarships offered by participating universities, corporations and the National Merit organization. The tests are created by the College Board, a not for profit American organization that develops and administers the SAT and PSAT.
Students will also be given a lunch break, and the testing schedule has intermittent bathroom breaks built in.
Freshman Jack Whitaker said that he takes his education very seriously and that he agrees with having the day off because students taking the test deserve a one-hundred percent silent, focused testing environment. He said he would expect the same if he were taking the test himself.
Ohio law requires that schools administer ACT or SAT to all grade 11 students and pays for the administration but does not require or support the PSAT. The district has chosen to administer it.
All grades will be given the opportunity to retake the EOC exams in December.
I think this story is the best story ever on Shakerite!!!


text:
Authors' Rights in Scholarly Publishing
Authors' Rights in Scholarly Publishing: Home
A guide to copyright in scholarly publishing, including negotiating with publishers, journal options, and self-archiving.
Publisher Policies on Self-Archiving
Negotiating with Publishers
Creative Commons Licenses
Authors' Rights: A Video Overview
Scholarly Communications-Related Guides
Scholarly Communications at Mount Sinai
Copyright and Fair Use: The Basics
Journal Selection and Identification
NIH Public Access Policy: Steps to Compliance
Open Researcher and Contributor ID (ORCID)
Personal Impact Factor and H-Index Calculations
Plum Analytics at Mount Sinai
Preprints: The Basics
Controlling Your Copyright
What are authors' rights?
These are rights that are often considered synonymous with copyright. Copyright applies to nearly all intellectual and creative works, including—but not limited to—books, journal articles, sound recordings, photographs, paintings, sculptures, films, and websites. The rights that are granted to copyright holders encompass reproduction, distribution, performances, public displays, or the creation of a derivative (based on the original) work.
In general, the author or creator of a work initially owns its copyright.
There are exceptions to this rule. If a work is created by an employee in the course of his or her employment, the employer usually owns the copyright. Similarly, "work for hire" done by contractors is usually owned by the commissioning person or organization.
Copyright holders may voluntarily release some or all of their rights.
For example, some academic, scholarly or not-for-profit organizations make content freely available under a range of Creative Commons licenses. Open access journals, in particular, often use Creative Commons licenses.
Copyright holders often sell or transfer some or all of their rights to a distributor or a publisher.
It is common for publishers to ask you to transfer to your copyrights to them as a condition of publication.
Read the publisher's copyright agreement carefully. You may wish to modify it before signing it so that you retain some rights.
For example, you may want to retain the right to incorporate some or all of your article in your thesis or dissertation--without seeking the permission of (or paying royalties to) the publisher.
Sources: U.S. Copyright Office. (n.d). Definitions.; Crews, K. D. (2015). Copyright quick guide. Columbia University Libraries.; Stanford University Libraries. (2016). Copyright ownership: Who owns what?.
Image by Clker-Free-Vector-Images from Pixabay.
Keep Your Copyrights (Columbia University)
Next: Know Your Rights >>
Last Updated: Jan 4, 2021 11:59 AM
URL: https://libguides.mssm.edu/authorsrights