Detection of dynamic rhythms of electroencephalography by using wavelet packets decomposition

Wavelet packet decomposition is used to investigate. the time-varying characteristics of clinical EEG signals. On the basis of the nonstationary nature of clinical EEG rhythms, wavelet packet analysis is employed for designing filters with different frequency characteristics to detect 4 kinds of EEG rhythms. The coefficients of wavelet transformation corresponding to the rhythms are used to form the dynamic brain electrical activity mapping (DBEAM). In order to understand the dynamic rhythms of the EEG, some clinical EEG are analyzed and compared. It is indicated from the experimental results that the dynamic characteristics of clinical brain electrical activities can be provided in terms of wavelet packet decomposition.published_or_final_versio

A method for estimating the instantaneous frequency of non-stationary heart sound signals

Practical signals such as speech, biomedical measurement and communications turn out to be extremely non-stationary and nonlinear time series. Traditional FFT-based power spectral analysis fails to deal with these transient signals. To provide more efficient way for investigating non-stationary and nonlinear signals with high time-frequency resolution and extract more information regarding the transient frequency features involved in the signals, a novel method based on the instantaneous frequency distribution is developed in this paper to provide the time-frequency distribution of the practical signals. The aim of this contribution is to explore the role that both empirical mode decomposition and Hilbert transform can be used to play in such practical signals. Both simulation and experimental results were presented and analyzed to demonstrate the power and effectiveness of the proposed new time-frequency distribution.published_or_final_versio

Identification of non-Gaussian parametric model with time-varying coefficients using wavelet basis

Many time series in practice turn to be the time-varying (TV) non-Gaussian processes. In this paper, we address the problem of how to describe these non-stationary non-Gaussian time series. A non-Gaussian AR model with TV parameters is proposed to track the non-stationary non-Gaussian characteristics of the signal. Since wavelet has flexibility in capturing the signal's transient characteristics at different scales, a set of wavelet basis is employed so that the model parameters can effectively track the variations of TV signals and be used to estimate the corresponding TV bispectrum. The experiments results confirm the superior performance of the presented model over the previous method.published_or_final_versio

Identification of non-Gaussian parametric model with time-varying coefficients using wavelet basis

Many time series in practice turn to be the time-varying (TV) non-Gaussian processes. In this paper, we address the problem of how to describe these non-stationary non-Gaussian time series. A non-Gaussian AR model with TV parameters is proposed to track the non-stationary non-Gaussian characteristics of the signal. Since wavelet has flexibility in capturing the signal's transient characteristics at different scales, a set of wavelet basis is employed so that the model parameters can effectively track the variations of TV signals and be used to estimate the corresponding TV bispectrum. The experiments results confirm the superior performance of the presented model over the previous method.published_or_final_versio

Cost-effective solution to synchronised audio-visual data capture using multiple sensors

Applications such as surveillance and human behaviour analysis require high- bandwidth recording from multiple cameras, as well as from other sensors. In turn, sensor fusion has increased the required accuracy of synchronisation be- tween sensors. Using commercial off-the-shelf components may compromise quality and accuracy, because it is difficult to handle the combined data rate from multiple sensors, the offset and rate discrepancies between independent hardware clocks, the absence of trigger inputs or -outputs in the hardware, as well as the different methods for timestamping the recorded data. To achieve accurate synchronisation, we centralise the synchronisation task by recording all trigger- or timestamp signals with a multi-channel audio interface. For sensors that don’t have an external trigger signal, we let the computer that captures the sensor data periodically generate timestamp signals from its se- rial port output. These signals can also be used as a common time base to synchronise multiple asynchronous audio interfaces. Furthermore, we show that a consumer PC can currently capture 8-bit video data with 1024x1024 spatial- and 59.1Hz temporal resolution, from at least 14 cameras, together with 8 channels of 24-bit audio at 96kHz. We thus improve the quality/cost ratio of multi-sensor systems data capture systems

An analysis of logistics response times for requisitions of naval aviation repairable items

Minimized safety level investment, while achieving high service levels and low customer wait time, is critical to the performance of the United States Navy supply system. The Naval Inventory Control Point (NAVICP) uses the Uniform Inventory Control Program to compute safety levels for each of the stock items they maintain. To assist in computing these levels, NAVICP aggregates repairable items based on demand and cost. The performance metrics used to measure the effectiveness of the model, Supply Material Availability and Average Days Delay, are affected by this aggregation. The purpose of the thesis is to describe an alternative methodology of aggregation that will allow NAVICP to allocate its item management skills more efficiently. The proposed methodology, based on item cost, demand, and Logistics Response Times for requisitions, can improve inventory performance without increasing the workload of item managers. Using analysis of variance, an analytical approach is adopted to ascertain whether an item has an average Logistics Response Time that exceeds the Navy's goal. It is shown that the proposed aggregation can improve Supply Material Availability and safety level investments while better managing items based on Logistics Response Time.http://archive.org/details/annalysisoflogis109455961LCDR, SC, USNApproved for public release; distribution is unlimited

Strong correlations and orbital texture in single-layer 1T-TaSe2

Strong electron correlation can induce Mott insulating behaviour and produce intriguing states of matter such as unconventional superconductivity and quantum spin liquids. Recent advances in van der Waals material synthesis enable the exploration of Mott systems in the two-dimensional limit. Here we report characterization of the local electronic properties of single- and few-layer 1T-TaSe2 via spatial- and momentum-resolved spectroscopy involving scanning tunnelling microscopy and angle-resolved photoemission. Our results indicate that electron correlation induces a robust Mott insulator state in single-layer 1T-TaSe2 that is accompanied by unusual orbital texture. Interlayer coupling weakens the insulating phase, as shown by reduction of the energy gap and quenching of the correlation-driven orbital texture in bilayer and trilayer 1T-TaSe2. This establishes single-layer 1T-TaSe2 as a useful platform for investigating strong correlation physics in two dimensions

Analysis of time-varying synchronization of multi-channel EEG signals using wavelet coherence

This paper proposes a novel method based on the time-frequency coherent representation for quantifying synchronization of multi-channel signals with high resolution. The presented wavelet-coherent technique provides the information regarding both the degree of coherence and the relation of phase difference. The wavelet coherence enables to provide the synchronization and the direction of information flow between two-channel signals. In addition, real EEG recordings are collected based on the cognitive targets during sentences identification and the wavelet coherence is employed for the analysis of the multi-channel EEG signals. It is observed from both the magnitude spectra and phase of the wavelet coherence that there are obvious differences between two kinds of cognitive activities. Finally, some results are illustrated with both simulation and real EEG lime series to show the effectiveness of the method.published_or_final_versio

Transitional cell carcinoma of the ovary: A rare case and review of literature

<p>Abstract</p> <p>Introduction</p> <p>Transitional cell carcinoma (TCC) of the ovary is a rare, recently recognized, subtype of ovarian surface epithelial cancer.</p> <p>Case presentation</p> <p>A 69-year-old postmenopausal woman presented with a 2-year history of progressive enlargement of an abdominal mass. Abdominal computed tomography showed a pelvic mass. CA-125 was normal. A staging operation with total abdominal hysterectomy, bilateral salpingo-oophorectomy, infracolic omentectomy and pelvic lymph node dissection was performed. After surgery, the pathologic report of the right ovarian tumour was TCC, grade 3, stage IC. The patient underwent 3 cycles of chemotherapy: carboplatin and paclitaxel. She is regularly followed up and has been disease free for 10 months</p> <p>Conclusion</p> <p>Transitional cell carcinoma (TCC) of the ovary is a rare subtype of epithelial ovarian cancer. Surgical resection is the primary therapeutic approach, and patient outcomes after chemotherapy are better than for other types of ovarian cancers.</p

Evidence for solar cycles in a late Holocene speleothem record from Dongge Cave, China

The association between solar activity and Asian monsoon (AM) remains unclear. Here we evaluate the possible connection between them based on a precisely-dated, high-resolution speleothem oxygen isotope record from Dongge Cave, southwest China during the past 4.2 thousand years (ka). Without being adjusted chronologically to the solar signal, our record shows a distinct peak-to-peak correlation with cosmogenic nuclide 14C, total solar irradiance (TSI) and sunspot number (SN) at multi-decadal to centennial timescales. Further cross-wavelet analyses between our calcite δ18O and atmospheric 14C show statistically strong coherence at three typical periodicities of ~80, 200 and 340 years, suggesting important roles of solar activities in modulating AM changes at those timescales. Our result has further indicated a better correlation between our calcite δ18O record and atmospheric 14C than between our record and TSI. This better correlation may imply that the Sun–monsoon connection is dominated most likely by cosmic rays and oceanic circulation (both associated to atmospheric 14C), instead of the direct solar heating (TSI)