Detection of atrial fibrillation episodes in long-term heart rhythm signals using a support vector machine

Atrial fibrillation (AF) is a serious heart arrhythmia leading to a significant increase of the risk for occurrence of ischemic stroke. Clinically, the AF episode is recognized in an electrocardiogram. However, detection of asymptomatic AF, which requires a long-term monitoring, is more efficient when based on irregularity of beat-to-beat intervals estimated by the heart rate (HR) features. Automated classification of heartbeats into AF and non-AF by means of the Lagrangian Support Vector Machine has been proposed. The classifier input vector consisted of sixteen features, including four coefficients very sensitive to beat-to-beat heart changes, taken from the fetal heart rate analysis in perinatal medicine. Effectiveness of the proposed classifier has been verified on the MIT-BIH Atrial Fibrillation Database. Designing of the LSVM classifier using very large number of feature vectors requires extreme computational efforts. Therefore, an original approach has been proposed to determine a training set of the smallest possible size that still would guarantee a high quality of AF detection. It enables to obtain satisfactory results using only 1.39% of all heartbeats as the training data. Post-processing stage based on aggregation of classified heartbeats into AF episodes has been applied to provide more reliable information on patient risk. Results obtained during the testing phase showed the sensitivity of 98.94%, positive predictive value of 98.39%, and classification accuracy of 98.86%.Web of Science203art. no. 76

Wind Variability in BZ Camelopardalis

(Shortened) Sequences of spectra of the nova-like cataclysmic variable (CV) BZ Cam were acquired on 9 nights in 2005-2006 in order to study the time development of episodes of wind activity known to occur frequently in this star. We confirm past results that the P-Cygni absorption components of the lines mostly evolve from a higher expansion velocity to lower velocity as an episode progresses. We also commonly find blueshifted emission components in the Halpha line profile, whose velocities and durations strongly suggest that they are also due to the wind. We suggest that the progression from larger to smaller expansion velocities is due the higher velocity portions of a wind concentration moving beyond the edge of the continuum light of the disk first, leaving a net redward shift of the remaining absorption profile. We also derive a new orbital ephemeris for BZ Cam, using the radial velocity of the core of the HeI 5876AA line, finding P = 0.15353(4). Using this period the wind episodes in BZ Cam are found to be concentrated near inferior conjuction of the emission line source. This result confirms that the winds in nova-like CVs are often phase dependent, in spite of the puzzling implication that such winds lack axisymmetry. We argue that the radiation-driven wind in BZ Cam receives an initial boost by acting on gas that has been lifted above the disk by the interaction of the accretion stream with the disk, thereby imposing flickering time scales onto the wind events, as well as leading to an orbital modulation of the wind due to the non-axisymmetric nature of the stream/disk interaction.Comment: The Astronomical Journal, in pres

Temporal regularity effects on pre-attentive and attentive processing of deviance

Temporal regularity allows predicting the temporal locus of future information thereby potentially facilitating cognitive processing. We applied event-related brain potentials (ERPs) to investigate how temporal regularity impacts pre-attentive and attentive processing of deviance in the auditory modality. Participants listened to sequences of sinusoidal tones differing exclusively in pitch. The inter-stimulus interval (ISI) in these sequences was manipulated to convey either isochronous or random temporal structure. In the pre-attentive session, deviance processing was unaffected by the regularity manipulation as evidenced in three event-related-potentials (ERPs): mismatch negativity (MMN), P3a, and reorienting negativity (RON). In the attentive session, the P3b was smaller for deviant tones embedded in irregular temporal structure, while the N2b component remained unaffected. These findings confirm that temporal regularity can reinforce cognitive mechanisms associated with the attentive processing of deviance. Furthermore, they provide evidence for the dynamic allocation of attention in time and dissociable pre-attentive and attention-dependent temporal processing mechanisms

The Role of Helium Stars in the Formation of Double Neutron Stars

We have calculated the evolution of 60 model binary systems consisting of helium stars in the mass range of M_He= 2.5-6Msun with a 1.4Msun neutron star companion to investigate the formation of double neutron star systems.Orbital periods ranging from 0.09 to 2 days are considered, corresponding to Roche lobe overflow starting from the helium main sequence to after the ignition of carbon burning in the core. We have also examined the evolution into a common envelope phase via secular instability, delayed dynamical instability, and the consequence of matter filling the neutron star's Roche lobe. The survival of some close He-star neutron-star binaries through the last mass transfer episode (either dynamically stable or unstable mass transfer phase) leads to the formation of extremely short-period double neutron star systems (with P<~0.1days). In addition, we find that systems throughout the entire calculated mass range can evolve into a common envelope phase, depending on the orbital period at the onset of mass transfer. The critical orbital period below which common envelope evolution occurs generally increases with M_He. In addition, a common envelope phase may occur during a short time for systems characterized by orbital periods of 0.1-0.5 days at low He-star masses (~ 2.6-3.3Msun). The existence of a short-period population of double neutron stars increases the predicted detection rate of inspiral events by ground-based gravitational-wave detectors and impacts their merger location in host galaxies and their possible role as gamma-ray burst progenitors. We use a set of population synthesis calculations and investigate the implications of the mass-transfer results for the orbital properties of DNS populations.Comment: 30 pages, Latex (AASTeX), 1 table, 8 figures. To appear in ApJ, v592 n1 July 20, 200

Diagnosis of a unit-wide disturbance caused by saturation in a manipulated variable

It is well known that faulty control valves with friction in the moving parts lead to limit cycle oscillations which can propagate to other parts of the plant. However, a control loop with healthy valve can also undergo oscillatory behavior. The root cause of a unit-wide oscillation in a distillation column was traced to a pressure control loop in a case study at Mitsui Chemicals. The diagnosis was made by means of a new technique of pattern matching of the time-resolved frequency spectrum using a wavelet analysis tool. The method identified key characteristics shared by measurements at various places in the column and quantified the similarities. Non-linearity was detected in the time trend of the pressure measurement, a result which initially suggested the root cause was a faulty actuator or sensor. Further analysis showed, however, that the source of non-linearlity was periodic saturation of the manipulated variable caused by slack tuning. The problem was remidied by changing the controller tuning settings and the unit-wide disturbance then went away

Processing count queries over event streams at multiple time granularities

Management and analysis of streaming data has become crucial with its applications in web, sensor data, network tra c data, and stock market. Data streams consist of mostly numeric data but what is more interesting is the events derived from the numerical data that need to be monitored. The events obtained from streaming data form event streams. Event streams have similar properties to data streams, i.e., they are seen only once in a fixed order as a continuous stream. Events appearing in the event stream have time stamps associated with them in a certain time granularity, such as second, minute, or hour. One type of frequently asked queries over event streams is count queries, i.e., the frequency of an event occurrence over time. Count queries can be answered over event streams easily, however, users may ask queries over di erent time granularities as well. For example, a broker may ask how many times a stock increased in the same time frame, where the time frames specified could be hour, day, or both. This is crucial especially in the case of event streams where only a window of an event stream is available at a certain time instead of the whole stream. In this paper, we propose a technique for predicting the frequencies of event occurrences in event streams at multiple time granularities. The proposed approximation method e ciently estimates the count of events with a high accuracy in an event stream at any time granularity by examining the distance distributions of event occurrences. The proposed method has been implemented and tested on di erent real data sets and the results obtained are presented to show its e ectiveness