On-line monitoring using Multi-Process Kalman Filtering

On-line monitoring of time series becomes more and more important in different areas of application like medicine, biometry and finance. In medicine, on-line monitoring of patients after transplantation of renals (Smith83) is an easy and prominent example. In finance, fast end reliable recognition of changes in level and trend of intra-daily stock market prices is of obvious interest for ordering and purchasing. In this project, we currently consider monitoring of surgical data like heart-rate, blood pressure and oxygenation. From a statistical point of view, on-line monitoring can be considered as on-line detection of changepoints in time series. That means, changepoints have to be detected in real time as new observations come in, usually in short time intervals. Retrospective detection of changepoints, after the whole batch of observations has been recorded, is nice but useless in monitoring patients during an operation. There are various statistical approaches conceivable for on-line detection of changepoints in time series. Dynamic or state space models seem particularly well suited because ``filtering'' has historically been developed exactly for on-line estimation of the ``state'' of some system. Our approach is based on a recent extension of the so-called multi-process Kalman filter for changepoint detection (Schnatter94). It turned out, however, that some important issues for adequate and reliable application have to be considered, in particular the (appropriate) handling of outliers and, as a central point, adaptive on-line estimation of control- or hyper-parameters. In this paper, we describe a filter model that has this features and can be implemented in such a way that it is useful for real time applications with high frequency time series data. Recently, simulation based methods for estimation of non-Gaussian dynamic models have been proposed that may also be adapted and generalized for the purpose of changepoint detection. Most of them solve the smoothing problem, but very recently some proposals have been made that could be useful also for filtering and, thus, for on-line monitoring (Kitagawa96a,Kitagawa96b,Shephard96). If these approaches are a useful alternative to our development needs a careful comparison in future and is beyond the scope of this paper

Use of vane and air jet vortex generators in a thrust augmenting ejector

The beneficial application of vortex generators to control boundary layers in the sub- and supersonic flow regime has been shown in the past. In this thesis the use of vortex generators is extended beyond boundary layer control by using them within an ejector-diffuser type augmentor. During the course of the research work it was established that the vortex generators could be used as effective 'mixers' between the primary air stream and the secondary entrained air stream. A previously developed mathematical model of ejector-diffuser flow, incorporating parameters such as pressure ratio, nozzle to duct area ratio and diffuser area ratio, was extended and refined. With the help of that model the above mentioned parameters were defined and according to these parameters a test rig was designed and manufactured. The primary ejector was driven by either a peripheral slit jet or eight individual air jets or the combination of both. The major task of the project was to design a rig which was short but produced a good thrust augmentation based on the bare nozzle thrust. A good thrust augmentation ratio was obtainable by ensuring rapid mixing between the primary and secondary air streams. The test programme was split into two major parts, namely the use of vane vortex generators in conjunction with the peripheral jet and then the application of air jet vortex generators again with the peripheral jet. The vanes and also the air jets were configured either as eight co-rotating vortices or as four contra-rotating vortex pairs. A special case which was also considered involved the air jet vortex generators on their own without peripheral blowing. This test was possible because the eight air jets could be used as primary air injectors and vortex generators at the same time. It emerged that this configuration was particularly revealing because it highlighted the essential difference between co- and contra-rotating vortices. Near the design primary pressure ratio of 5.0 the bare nozzle thrust was augmented by a maximum of 30 per cent with the vanes installed. This was a considerable advance on the augmentation for the bare augmentor, i.e. the same configuration as above but without vortex generators installed, which came to 1.15 at the same pressure ratio of 5.0. The results of augmentation for the air jets were more complex due to the way in which the air was injected. Elevation and skew angle were responsible for the enlarged complexity. As a general trend it can be stated that the augmentation ratios were high for low pressure ratios, as high as 1.7 at a pressure ratio of 2.0, but fell off as the pressure was increased. Dynamic pressure contour plots in the exit plane gave good indications of the vortex movements produced by the co- and contra-rotating vortex generators. This project showed that considerable thrust augmentations could be achieved by using vortex generators

Neural basis of shame and guilt experience in women with borderline personality disorder.

Borderline personality disorder (BPD) is characterized by instability of affect, emotion dysregulation, and interpersonal dysfunction. Especially shame and guilt, so-called self-conscious emotions, are of central clinical relevance to BPD. However, only few experimental studies have focused on shame or guilt in BPD and none investigated their neurobiological underpinnings. In the present functional magnetic resonance imaging study, we took a scenario-based approach to experimentally induce feelings of shame, guilt, and disgust with neutral scenarios as control condition. We included 19 women with BPD (age 26.4 ± 5.8 years; DSM-IV diagnosed; medicated) and 22 healthy female control subjects (age 26.4 ± 4.6 years; matched for age and verbal IQ). Compared to controls, women with BPD reported more intense feelings when being confronted with affective scenarios, especially higher levels of shame, guilt, and fear. We found increased amygdala reactivity in BPD compared to controls for shame and guilt, but not for disgust scenarios (p = 0.05 FWE corrected at the cluster level; p < 0.0001 cluster defining threshold). Exploratory analyses showed that this was caused by a diminished habituation in women with BPD relative to control participants. This effect was specific to guilt and shame scenarios as both groups showed amygdala habituation to disgust scenarios. Our work suggests that heightened shame and guilt experience in BPD is not related to increased amygdala activity per se, but rather to decreased habituation to self-conscious emotions. This provides an explanation for the inconsistencies in previous imaging work on amygdala involvement in BPD as well as the typically slow progress in the psychotherapy of dysfunctional self-conscious emotions in this patient group

IoTSan: Fortifying the Safety of IoT Systems

Today's IoT systems include event-driven smart applications (apps) that interact with sensors and actuators. A problem specific to IoT systems is that buggy apps, unforeseen bad app interactions, or device/communication failures, can cause unsafe and dangerous physical states. Detecting flaws that lead to such states, requires a holistic view of installed apps, component devices, their configurations, and more importantly, how they interact. In this paper, we design IoTSan, a novel practical system that uses model checking as a building block to reveal "interaction-level" flaws by identifying events that can lead the system to unsafe states. In building IoTSan, we design novel techniques tailored to IoT systems, to alleviate the state explosion associated with model checking. IoTSan also automatically translates IoT apps into a format amenable to model checking. Finally, to understand the root cause of a detected vulnerability, we design an attribution mechanism to identify problematic and potentially malicious apps. We evaluate IoTSan on the Samsung SmartThings platform. From 76 manually configured systems, IoTSan detects 147 vulnerabilities. We also evaluate IoTSan with malicious SmartThings apps from a previous effort. IoTSan detects the potential safety violations and also effectively attributes these apps as malicious.Comment: Proc. of the 14th ACM CoNEXT, 201

Results of the MTLRS-1 upgrade

In this report, the results of the upgrade of the German Modular Transportable Laser Ranging System MTLRS-1 are summarized. A short description of the new components and their influence on the system accuracy is given. It is shown, that the single shot accuracy of the MTLRS-1 has been improved from 5 cm to 1 cm

On the ultimate convergence rates for isotropic algorithms and the best choices among various forms of isotropy

In this paper, we show universal lower bounds for isotropic algorithms, that hold for any algorithm such that each new point is the sum of one already visited p oint plus one random isotropic direction multiplied by any step size (whenever the step size is chosen by an oracle with arbitrarily high computational power). The bound is 1 − O(1/d) for the constant in the linear convergence (i.e. the constant C such that the distance to the optimum after n steps is upp er b ounded by C n ), as already seen for some families of evolution strategies in [19, 12], in contrast with 1 − O(1) for the reverse case of a random step size and a direction chosen by an oracle with arbitrary high computational power. We then recall that isotropy does not uniquely determine the distribution of a sample on the sphere and show that the convergence rate in isotropic algorithms is improved by using stratified or antithetic isotropy instead of naive isotropy. We show at the end of the pap er that b eyond the mathematical proof, the result holds on exp eriments. We conclude that one should use antithetic-isotropy or stratified-isotropy, and never standard-isotropy

Relationship between regional white matter hyperintensities and alpha oscillations in older adults

Aging is associated with increased white matter hyperintensities (WMHs) and with alterations of alpha oscillations (7–13 Hz). However, a crucial question remains, whether changes in alpha oscillations relate to aging per se or whether this relationship is mediated by age-related neuropathology like WMHs. Using a large cohort of cognitively healthy older adults (N=907, 60-80 years), we assessed relative alpha power, alpha peak frequency, and long-range temporal correlations (LRTC) from resting-state EEG. We further associated these parameters with voxel-wise WMHs from 3T MRI. We found that a higher prevalence of WMHs in the superior and posterior corona radiata as well as in the thalamic radiation was related to elevated alpha power, with the strongest association in the bilateral occipital cortex. In contrast, we observed no significant relation of the WMHs probability with alpha peak frequency and LRTC. Finally, higher age was associated with elevated alpha power via total WMH volume. We suggest that an elevated alpha power is a consequence of WMH affecting a spatial organization of alpha sources

eBay users form stable groups of common interest

Market segmentation of an online auction site is studied by analyzing the users' bidding behavior. The distribution of user activity is investigated and a network of bidders connected by common interest in individual articles is constructed. The network's cluster structure corresponds to the main user groups according to common interest, exhibiting hierarchy and overlap. Key feature of the analysis is its independence of any similarity measure between the articles offered on eBay, as such a measure would only introduce bias in the analysis. Results are compared to null models based on random networks and clusters are validated and interpreted using the taxonomic classifications of eBay categories. We find clear-cut and coherent interest profiles for the bidders in each cluster. The interest profiles of bidder groups are compared to the classification of articles actually bought by these users during the time span 6-9 months after the initial grouping. The interest profiles discovered remain stable, indicating typical interest profiles in society. Our results show how network theory can be applied successfully to problems of market segmentation and sociological milieu studies with sparse, high dimensional data.Comment: Major revision of the manuscript. Methodological improvements and inclusion of analysis of temporal development of user interests. 19 pages, 12 figures, 5 table