Support Vector machine and duration-aware conditional random field for identification of spatio-temporal activity patterns by combined indoor positioning and heart rate sensors

Tracking the spatio-temporal activity is highly relevant for domains like security, health, and quality management. Since animal welfare became a topic in politics and legislation locomotion patterns of livestock have received increasing interest. In contrast to the monitoring of pedestrians cattle activity tracking poses special challenges to both sensors and data analysis. Interesting states are not directly observable by a single sensor. In addition, sensors must be accepted by cattle and need to be robust enough to cope with a rough environment. In this article, we introduce the novel combination of heart rate and positioning sensors. Attached to neck and chest they are less interfering than accelerometers at the ankles. Exploiting the potential of such combined sensor system that records locomotion and non-spatial information from the heart rate sensor however is challenging. We introduce a novel two level method for the activity tracking focused on the duration and sequence of activity states. We combine Support Vector Machine (SVM) with Conditional Random Field (CRF) and extend Conditional Random fields by an explicit representation of duration. The SVM characterizes local activity states, whereas the CRF addresses sequences of local states to sequences incorporating spatial and non-spatial contextual knowledge. This combination provides a reliable and comprehensive identification of defined activity patterns, as well as their chronology and durations, suitable for the integration in an activity data base. This data base is used to extract physiological parameters and promises insights into internal states such as fitness, well-being and stress. Interestingly we were able to demonstrate a significant correlation between resting pulse rate and the day of pregnancy.     

Mesh-free canonical tensor products for six-dimensional density matrix: computation of kinetic energy

The computation of a six-dimensional density matrix is the crucial step for the evaluation of kinetic energy in electronic structure calculations. For molecules with heavy nuclei, one has to consider a very refined mesh in order to deal with the nuclear cusps. This leads to high computational time and needs huge memory for the computation of the density matrix. To reduce the computational complexity and avoid discretization errors in the approximation, we use mesh-free canonical tensor products in electronic structure calculations. In this paper, we approximate the six-dimensional density matrix in an efficient way and then compute the kinetic energy. Accuracy is examined by comparing our computed kinetic energy with the exact computation of the kinetic energy.     

Gesture-based interaction via finger tracking for mobile augmented reality

The goal of this research is to explore new interaction metaphors for augmented reality on mobile phones, i.e. applications where users look at the live image of the device’s video camera and 3D virtual objects enrich the scene that they see. Common interaction concepts for such applications are often limited to pure 2D pointing and clicking on the device’s touch screen. Such an interaction with virtual objects is not only restrictive but also difficult, for example, due to the small form factor. In this article, we investigate the potential of finger tracking for gesture-based interaction. We present two experiments evaluating canonical operations such as translation, rotation, and scaling of virtual objects with respect to performance (time and accuracy) and engagement (subjective user feedback). Our results indicate a high entertainment value, but low accuracy if objects are manipulated in midair, suggesting great possibilities for leisure applications but limited usage for serious tasks.     

CPU demand for web serving: Measurement analysis and dynamic estimation

Managing the resources in a large Web serving system requires knowledge of the resource needs for service requests of various types. In order to investigate the properties of Web traffic and its demand, we collected measurements of throughput and CPU utilization and performed some data analyses. First, we present our findings in relation to the time-varying nature of the traffic, the skewness of traffic intensity among the various types of requests, the correlation among traffic streams, and other system-related phenomena. Then, given such nature of web traffic, we devise and implement an on-line method for the dynamic estimation of CPU demand.

Assessing resource needs is commonly performed using techniques such as off-line profiling, application instrumentation, and kernel-based instrumentation. Little attention has been given to the dynamic estimation of dynamic resource needs, relying only on external and high-level measurements such as overall resource utilization and request rates. We consider the problem of dynamically estimating dynamic CPU demands of multiple kinds of requests using CPU utilization and throughput measurements. We formulate the problem as a multivariate linear regression problem and obtain its basic solution. However, as our measurement data analysis indicates, one is faced with issues such as insignificant flows, collinear flows, space and temporal variations, and background noise. In order to deal with such issues, we present several mechanisms such as data aging, flow rejection, flow combining, noise reduction, and smoothing. We implemented these techniques in a Work Profiler component that we delivered as part of a broader system management product. We present experimental results from using this component in scenarios inspired by real-world usage of that product.     

Magnebike: A magnetic wheeled robot with high mobility for inspecting complex‐shaped structures

This paper describes the Magnebike robot, a compact robot with two magnetic wheels in a motorbike arrangement, which is intended for inspecting the inner casing of ferromagnetic pipes with complex‐shaped structures. The locomotion concept is based on an adapted magnetic wheel unit integrating two lateral lever arms. These arms allow for slight lifting off the wheel in order to locally decrease the magnetic attraction force when passing concave edges, as well as laterally stabilizing the wheel unit. The robot has the main advantage of being compact (180 × 130 × 220 mm) and mechanically simple: it features only five active degrees of freedom (two driven wheels each equipped with an active lifter stabilizer and one steering unit). The paper presents in detail design and implementation issues that are specific to magnetic wheeled robots. Low‐level control functionalities are addressed because they are necessary to control the active system. The paper also focuses on characterizing and analyzing the implemented robot. The high mobility is shown through experimental results: the robot not only can climb vertical walls and follow circumferential paths inside pipe structures but it is also able to pass complex combinations of 90‐deg convex and concave ferromagnetic obstacles with almost any inclination regarding gravity. It requires only limited space to maneuver because turning on the spot around the rear wheel is possible. This high mobility enables the robot to access any location in the specified environment. Finally the paper analyzes the maximum payload for different types of environment complexities because this is a key feature for climbing robots and provides a security factor about the risk of falling and slipping. © 2009 Wiley Periodicals, Inc.     

The hierarchical Tobit model: A case study in Bayesian computing

In this paper we discuss the potentials of a new Bayesian inference tool, called the Gibbs sampler, for the analysis of the censored regression or Tobit model. Tobit models have a wide range of applications in empirical sciences, like econometrics and biometrics. The estimation results of the simple Tobit model will be compared to a hierarchical Tobit model, and the Gibbs sampling approach to the related classical algorithm of expectation-maximisation (EM). The underlying botanical example of this paper is concerned with the censoring mechanism in plant reproduction and proposes the Bayesian Tobit model for the growth relationship between the reproductive part and the rest of the plant.     

Analysis of dithiocarbamate fungicides. Second-derivative UV-spectroscopic determination of CS2, COS, and thiram (TMTD)

The application of second-derivative UV-spectroscopy offers a highly sensitive and selective method for the determination of CS₂ and COS, as acid hydrolysis products of dithiocarbamate und thiuram disulphide fungicides, using a methanolic amine absorption reagent (ethylenediamine, piperidine). With standard concentrations of 0.08–1.1 g CS₂/ml and 0.3 to 2.0 g COS/ml, respectively, calibration curves with good correlation coefficients (r>0.999) were obtained. In comparison to the official method of the Deutsche Forschungsgemeinschaft (DFG method S15) the proposed alternative is at least 100 times more sensitive to CS₂. Using the second derivative method it is possible not only to clearly differentiate between CS₂ and COS but also to quantify both gases without resorting to tedious background corrections as compared to the direct photometric methods. Additionally, second derivative spectroscopy allows the direct determination of thiram in the concentration range 1–10 g/ml after its extraction with chloroform. For example, thiram in water (10 g/l) and in thiram/talc standards (10 mg/g) were determined with good precision (±2.0%).

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Analytik der Dithiocarbamat-Fungicide. Bestimmung von CS₂, COS sowie Thiram (TMTD) mittels Derivativ-UV-Spektroskopie

Zusammenfassung Die Anwendung der Derivativ-UV-Spektroskopie (2. Ableitung) erlaubt eine sehr empfindliche Bestimmung von CS₂ und COS als Hydrolyseprodukte der Dithiocarbamat- und Thiuramdisulfid-Fungicide nach Absorption in einem methanolischem Amin-Reagens (Ethylendiamin, Piperidin). Mit Standard-Konzentrationen von 0,08–1,1 g CS₂/ml bzw. 0,3–2,0 g COS/ml zeigten die Eichgeraden gute Korrelationskoeffizienten (r<0,999). Im Vergleich zur DFG-Methode S15 zeichnet sich die vorgeschlagene Alternative durch eine um zwei Zehnerpotenzen höhere Empfindlichkeit bei der CS₂-Bestimmung aus. In der 2. Ableitung wird nicht nur die Unterscheidung von COS und CS₂ eindeutig, sondern auch deren Quantifizierung ohne rechnerische Untergrundkorrekturen ermöglicht. Mit Hilfe der Derivativspektroskopie konnte außerdem Thiram (TMTD) in Konzentrationen von 1–10 g/ml direkt erfaßt werden. So ließen sich nach Extraktion mit Chloroform 10 g/L Thiram in Wasser mit einer Präzision von ±2,0% direkt bestimmen oder Thiram/Talkum-Standards (10 mg/g) überprüfen.