Baseline Compensation Research Articles

SnapE-ResNet: A novel electronic nose classification algorithm for gas data collected by open sampling systems

Increasing the depth of the neural network and implementing the ensemble of neural networks are two main methods to improve the accuracy of gas recognition algorithms. However, the issues of optimization difficulties or excessive resource consumption may occur when training deep neural networks or integrating multiple neural networks. In this study, an algorithm of snapshot ensemble is combined with Residual network (ResNet) to form a SnapE-ResNet which could simplify the training of the network due to the residual structure of ResNet, while realizes the ensemble of multiple ResNet models without additional time consumption and helps the network escape from local minimum using cyclic cosine annealing algorithm. The effectiveness of the proposed SnapE-ResNet is verified through classification experiments on the public dataset. Furthermore, the long-term drift and short-term drift are reduced by applying a zero-offset baseline compensation algorithm and a gaussian noise that added to the baseline signal. The experimental result indicating a high gas classification accuracy of 99.8 % from SnapE-ResNet is obtained, outperforming the comparative models. In addition, the necessity for snapshot ensemble is validated by network ablation experiments. This study could offer a reference for gas classification tasks in the gas detection fields.

A novel DenseNet with warm restarts for gas recognition in complex airflow environments

The diffusion mechanisms in natural environments often result in irregular and turbulent flow patterns in electronic nose field. This leads to random responses of electronic nose when exposed to the same gas ambiance, and thus brings serious challenges in gas identification. Recent studies have shown that the introducing of skip connections can enhance the capability of neural networks to extract features from gas data. In response to this finding, a novel One-dimensional DenseNet with Warm Restarts (1D-DNR) comprising skip connections is presented in this study. The network combines shallow and deep features using DenseNet and extracts the signal relevant to the unique characteristics of gas data through a 1D convolution. Furthermore, the classification accuracy and the stability of the proposed network are enhanced via the cosine annealing with warm restarts method. Further, zero-offset baseline compensation and Discrete Wavelet Transform (DWT) were employed to correct long-term drift and short-term drift effects. The results revealed that it is superior to the other models when dealing with the data of irregular and turbulent flow patterns of gases, with a classification accuracy of 99.83%.

Combination pharmacological therapy targeting multiple mechanisms of sleep apnoea: a randomised controlled cross-over trial

RationaleAcetazolamide and atomoxetine-plus-oxybutynin (‘AtoOxy’) can improve obstructive sleep apnoea (OSA) by stabilising ventilatory control and improving dilator muscle responsiveness respectively. Given the different pathophysiological mechanisms targeted by each intervention, we...

SAR Tomography Based on Atomic Norm Minimization in Urban Areas

Synthetic aperture radar (SAR) tomography (TomoSAR) is a powerful tool for the three-dimensional (3D) reconstruction of buildings in urban areas. At present, the compressed sensing (CS) technique has been widely used in the TomoSAR inversion of urban areas because of the sparsity of the backscattering power of buildings along the elevation direction. However, this algorithm discretizes the elevation and assumes that the scatterers are located on predetermined finite grids. In fact, scatterers can lie anywhere in the elevation direction, regardless of grid point constraints. The phenomenon of scatterer positioning errors due to elevation discretization is called the off-grid effect, which will affect the height estimation accuracy of TomoSAR. To overcome this problem, we proposed a TomoSAR reconstruction algorithm based on atomic norm minimization (Tomo-ANM) in this paper. Tomo-ANM employs ANM, a continuous compressed sensing technique, to obtain scatterer positions on the continuous dictionary, thus eliminating the off-grid effect. Baseline compensation is necessary to obtain the data of virtual uniform baselines or the samples of uniform data during preprocessing. A fast realization of ANM, IVDST, is utilized to accelerate the process. Tomo-ANM was tested through simulation experiments, and the results confirmed the validity of eliminating the influence of off-grid effects and exhibited an improved location accuracy and detection rate in less time compared with the on-grid TomoSAR algorithm SL1MMER. Real data experiments based on eight staring spotlight TerraSAR-X images showed that Tomo-ANM can improve the accuracy of building height estimation by 4.83% relative to its real height.

Gender-based salary differences in academic medicine: a retrospective review of data from six public medical centers in the Western USA

ObjectivesWe assessed the effect of gender, rank and research productivity on compensation for faculty at academic medical centres.DesignA web-based retrospective review of salary for professors in 2016.SettingFaculty from six state-run,...

Drift in a popular metal oxide sensor dataset reveals limitations for gas classification benchmarks

Metal oxide (MOx) gas sensors are a popular choice for many applications, due to their tunable sensitivity, space efficiency and low cost. Publicly available sensor datasets are particularly valuable for the research community as they accelerate the development and evaluation of novel algorithms for gas sensor data analysis. A dataset published in 2013 by Vergara and colleagues contains recordings from MOx gas sensor arrays in a wind tunnel. It has since become a standard benchmark in the field. Here we report a latent property of this dataset that limits its suitability for gas classification studies. Measurement timestamps show that gases were recorded in separate, temporally clustered batches. Sensor baseline response before gas exposure were strongly correlated with the recording batch, to the extent that baseline response was largely sufficient to infer the gas used in a given trial. Zero-offset baseline compensation did not resolve the issue, since residual short-term drift still contained enough information for gas/trial identification using a machine learning classifier. A subset of the data recorded within a short period of time was minimally affected by drift and suitable for gas classification benchmarking after offset-compensation, but with much reduced classification performance compared to the full dataset. We found 18 publications where this dataset was used without precautions against the circumstances we describe, thus potentially overestimating the accuracy of gas classification algorithms. These observations highlight potential pitfalls in using previously recorded gas sensor data, which may have distorted widely reported results.

Hyperspectral Molecular Orientation Mapping in Metamaterials

The four polarisation method is adopted for measurement of molecular orientation in dielectric nanolayers of metal-insulator-metal (MIM) metamaterials composed of gold nanodisks on polyimide and gold films. Hyperspectral mapping at the chemical finger printing spectral range of 4–20 μμm was carried out for MIM patterns of 1–2.5 μμm period (sub-wavelength). Overlay images taken at 0,π4,π2,3π4 orientation angles and subsequent baseline compensation are shown to be critically important for the interpretation of chemical mapping results and reduction of spurious artefacts. Light field enhancement in the 60-nm-thick polyimide (I in MIM) was responsible for strong absorption at the characteristic polyimide bands. Strong absorbance A at narrow IR bands can be used as a thermal emitter (emittance E=1−R), where R is the reflectance and A=1−R−T, where for optically thick samples the transmittance is T=0.

Ground Moving Target Indication for the Geosynchronous-Low Earth Orbit Bistatic Multichannel SAR System

In this article, an effective clutter suppression and moving target imaging approach is proposed for the geosynchronous-low earth orbit (GEO-LEO) bistatic multichannel synthetic aperture radar (SAR) system, which is robust for the fast moving target with Doppler centroid ambiguity. For the GEO-LEO bistatic multichannel SAR system, the characteristic of baseline with azimuth invariant in Doppler Fourier transform domain is not tenable. It is difficult to implement clutter suppression by the unified baseline compensation in azimuth Doppler Fourier transform domain. Fortunately, we discover that the baseline can be approximately regarded as a constant in chirp Fourier transform domain for the GEO-LEO bistatic multichannel SAR system. Hence, the corresponding baseline compensation can be achieved in the azimuth chirp Fourier transform domain for the clutter. With an orthogonality vector of clutter, the clutter can be well suppressed and the moving target is extracted. After that, the moving target imaging approach is developed with the baseband Doppler centroid estimation and Doppler ambiguity number estimation. Finally, the theoretical investigations and the proposed approach in this article are validated by some experiments, where the experiments for clutter suppression and experiments for fast moving targets are included. Especially, an experiment with real SAR scattering scene is involved. In addition, some discussions for blind velocity targets are presented.

Achieving high sensing in 0.5 nA for the driving pixel currents in AMOLEDs with settling time of 7 µs by a new external current sensing circuit

A new external current sensing circuit with baseline compensation for the active matrix organic light emitting diode (AMOLED) display is developed herein to achieve the sensing precision of 0.5 nA in pixel with 7 µs of settling time. Current sensing circuit incorporates a new push–pull transient current feedforward whereas the current analog to digital converter (CADC) based digital baseline current compensation incorporates an 11-bit current digital-to-analog converter, a current comparator and a digital control circuit with an 11-bit successive approximation register. The proposed integrated mixed signal IC drives a 6T1C pixel-based AMOLED panel with one horizontal time of 7.7 µs at a scan frequency of 60 Hz. The design readout chip can simultaneously sense and compensate TFT baseline current variation. The readout circuit and the baseline compensation circuit are implemented in the integrated chip with chip area of 125 μm × 46 μm and fabricated via TSMC T18 process. With the standard 3.3 V supply, experimental result shows that the overall power consumption of the chip is 988 µW watt. The minimum LSB current for the CADC is 10 nA and the maximum achievable sampling rate is 500 KS/s. The measured INL and DNL of CADC is 0.84 and 0.98 respectively. Despite of heavy data line parasitic capacitances (2.6 KΩ/20 pF) of the AMOLED display, experimental results show that the proposed circuit can sense 0.5 nA current within 7 µs of settling time. The sensing precision of 0.5 nA within 7 µs are the best among all reported literature to date whereas the current sense range (0.5–500 nA), system sampling rate (142 KS/s), INL (0.84) and DNL (0.98) of the CADC is approximately comparable among all reported.

Compensation of the baseline temperature fluctuations for autonomous CE–C4D instrument working in harsh environments

One of the main problems of the remote complex sample analysis instrumentation is that such systems are susceptible to temperature fluctuations. Temperature regulation is energetically ineffective, and it is not used in most of the field portable analytical systems. Separations performed in a changing temperature environment provide electropherograms with considerable baseline fluctuations, resulting in significant errors in detection and integration of the peaks. This paper describes electropherogram baseline compensation that is suitable for the capillary electrophoresis-contactless conductivity detection analytical method. The baseline compensation utilizes linear or polynomial data processing methods, and can be programmed in-line using simple microcontroller, or on-line and off-line in data acquisition software. This method is targeted for field portable and autonomous analytical systems that are utilized in a fluctuating environment.

Multiparameter Sensor Interface Circuit With Integrative Baseline/Offset Compensation by Switched-Capacitor Level Shifting/Balancing

The proposed sensor interface circuit provides an integrative baseline/offset compensation to give higher adaptability and effectiveness for multiparameter sensing microsystems. Capacitive/resistive and voltage type sensors are dealt with and switched-capacitor-based circuits are mostly employed to facilitate integrative baseline/offset cancellation and interface various types of sensors. For integrative signal conditioning, sensor signals are first converted to voltage signals and then given rail-to-rail baseline compensation and fine offset cancellation of 0.7 mV/bit. At the same time, each interface circuit demonstrates a large total conversion gain (C: 194 mV/fF, R: 6260 mV/k $\Omega$ , V: 230 V/V) and a coefficient of determination (R2) over 0.998, which indicates a high conversion linearity.

In-Cell Self-Capacitive-Type Mobile Touch System and Embedded Readout Circuit in Display Driver IC

A mobile display system, which includes a self- capacitive type in-cell touch screen panel and a display driver IC, in which the readout circuit is embedded, is developed for reduced cost, improved display performance, and superior touch performance. A touch electrode is implemented with a segmented common electrode of an LCD display. The display system of the in-cell touch panel is 5.7-in a-Si HD (720 × 1280), the number of touch electrodes is 576 (18 × 32), and the sensor pitch is approximately 4 mm. Compared to the display-only system, display performance degradation does not occur in the proposed system since in-cell technology is adopted. Despite using a self-capacitance sensing method in the panel, unlimited multitouch is available by using an all-point sensing scheme; this system shows a touch accuracy of less than 0.2 mm and signal-to-noise ratio is measured to be more than 48 dB in the entire panel without any digital filter. To enhance the touch performance, we proposed noise reduction techniques that are strongly related to the display operation, such as base line compensation, delta adding correlated double sampling, and the use of a high-voltage charge compensator. The power consumption including micro controller unit (MCU) is less than 30 mW.

Development of a DAQ system for a plasma display panel-based X-ray detector (PXD)

Recently, a novel plasma display panel (PDP)-based X-ray detector (PXD) was developed. The goal of this study is to develop a data acquisition system for use with the PXD as an imaging detector. Since the prototype detector does not have any barrier ribs or a switching device in a detector pixel, a novel pixelation scheme—the line-scan method—is developed for this new detector. To implement line scanning, a multichannel high-voltage switching circuit and a multichannel charge-acquisition circuit are developed. These two circuits are controlled by an FPGA-based digital signal processing board, from which the information about the charge and position of each pixel can be sent to a PC. FPGA-based baseline compensation and switching noise rejection algorithms are used to improve the signal-to-noise ratio (SNR). The characteristic curve of the entire PXD system is acquired, and the correlation coefficients between the X-ray dose, and the signal intensity and the SNR were determined to be approximately 0.99 and 52.9, respectively.

Analysis of noisy multi-angle dynamic light scattering data.

In multi-angle dynamic light scattering measurements, due to the inevitable presence of baseline measurement noise, the normalized intensity autocorrelation function (ACF) data deviates from the true value. This leads to incorrect angular weighting estimates, which affect the accuracy of inversion results and determination of particle size distributions (PSDs). We outline a method to calculate better angular weighting coefficients from the noisy intensity ACF data. The method involves first compensating for the baseline error in the ACF data and then determining the weighting coefficients. We demonstrate the method using simulated ACF data containing baseline error for unimodal and bimodal PSDs and also for experimental data for unimodal and bimodal samples. For the unimodal PSDs ACF data were simulated for 100-900nm and 100-650nm particle size ranges, and for bimodal PSDs 360-900nm and 100-900nm particle size ranges were used. The performance of our method was shown by comparing the results of weighting coefficient and PSD determination with and without baseline compensation to the known coefficient values and PSDs. With baseline compensation the relative error of the weighting coefficients decreased significantly. Furthermore, with baseline compensation, the PSD results for the four groups of simulated data were improved. The deviations between the known and recovered PSDs were decreased, the relative error of peak position obviously decreased, and the occurrence of false peaks was reduced. The PSD results from the experimental data further validates the conclusion that the method proposed apparently reduces the relative error of peak position, effectively eliminates the false peak, and improves the accuracy of the recovered PSD.

SiPM optical crosstalk amplification due to scintillator crystal: effects on timing performance

For a given photon detection efficiency (PDE), the primary, Poisson distributed, dark count rate of the detector (DCR0) is one of the most limiting factors affecting the timing resolution of a silicon photomultiplier (SiPM) in the scintillation light readout. If the effects of DCR0 are removed through a suitable baseline compensation algorithm or by cooling, it is possible to clearly observe another phenomenon that limits the PDE, and thus the timing resolution of the detector. It is caused by the optical crosstalk of the SiPM, which is significantly increased by the presence of the scintillator. In this paper, we describe this phenomenon, which is also easily observed from the reverse I–V curve of the device, and we relate it to the measured coincidence resolving time in 511 keV γ-ray measurements. We discuss its consequences on the SiPM design and, in particular, we observe that there is an optimal cell size, dependent on both SiPM and crystal parameters, that maximizes the PDE in presence of optical crosstalk. Finally, we report on a crosstalk simulator developed to study the phenomenon and we compare the simulation results obtained for different SiPM technologies, featuring different approaches to the reduction of the crosstalk.

Analog Circuit for Timing Measurements With Large Area SiPMs Coupled to LYSO Crystals

The most common method for time pick-off from signals coming from SiPMs coupled to scintillator crystals in PET applications is the Leading Edge Triggering. In this work we propose a new filtering scheme to be applied before the discriminator. It implements a type of baseline compensation aimed at the reduction of the time jitter due to the dark counts of the detector and is based on a simple analog filter, which is well suited for an ASIC implementation. We describe a circuit, built with discrete components, that implements the filter. Finally we report on the Coincidence Resolving Time measurements performed coupling the circuit to the real detector, composed of a SiPM built at FBK and a LYSO crystal, for the detection of 511 keV photons. The results obtained are promising, showing that the method is quite effective in reducing the impact of the detector noise on the timing performance of the system.

Analysis of noisy dynamic light scattering data using constrained regularization techniques

Dynamic light scattering (DLS) from colloidal particles often contains noise, which makes inversion of the correlation function to obtain the particle size distribution (PSD) unreliable. In this work, poor-quality correlation function data with baseline error were analyzed using constrained regularization techniques. The effect of baseline error was investigated, and two strategies were proposed to compensate for baseline error. One strategy is based on edge proportion detection of spurious peaks at large size in the PSD, and the other is based on the solution norm. Results from simulated and experimental data demonstrate the effectiveness of our proposed strategies. The L-curve rules for standard Tikhonov and for constrained regularization, the generalized cross-validation (GCV) rule, and the robust GCV rule were investigated for determination of the regularization parameter. A comparison of these rules was done using both simulated and experimental data. It is shown that correction of baseline error with baseline compensation as well as a reasonable regularization parameter choice improves the accuracy of PSD recovery in poor-quality DLS data analysis.

Pre-treatment compensation use is a stronger correlate of measures of activity limitations than cognitive impairment

Objectives: This study examined the relationship between baseline compensation use, activity limitations and cognitive impairment in persons who sustained moderate-to-severe acquired brain injury.Design: Randomized controlled clinical trial.Methods: A total of 22 individuals with medically documented brain injury and their family members completed a baseline assessment including measures of cognitive functioning (Repeatable Battery of Neuropsychological Assessment; RBANS), activity limitations (Neurobehavioural Functioning Inventory; NFI) and compensatory strategies use (Compensation Techniques Questionnaire; CTQ). There were no gender differences on measures of cognitive impairment, activity limitations or compensation use.Results: As predicted, cognitive impairment was not significantly associated with frequency of baseline compensation strategy use. Weaker word-list learning on RBANS was associated with greater family-reported memory problems on the NFI. Lower frequency of compensatory strategy use was correlated with greater patient-reported activity limitations on NFI, while it was not related to family ratings of activity limitations. After adjusting for history of depression and anxiety, baseline compensation use uniquely accounted for 16% of variance in predicting greater patient ratings of mood difficulties.Conclusions: Results indicate that, after acquired brain injury, baseline compensation use is more strongly associated with measures of activity limitations than is cognitive impairment.

Binding of benzodiazepine drugs to bovine serum albumin: A second derivative spectrophotometric study

The binding constants ( K values) of three benzodiazepine drugs to bovine serum albumin were determined by a second derivative spectrophotometric method. Despite the sample and reference samples were prepared in the same way to maintain the same albumin content in each sample and reference pair, the absorption spectra show that the baseline compensation was incomplete because of the strong background signals caused by bovine serum albumin. Accordingly, further quantitative spectral information could not be obtained from these absorption spectra. On the other hand, the calculated second derivative spectra clearly show isosbestic points indicating the complete removal of the residual background signal effects. Using the derivative intensity differences (Δ D values) of the studied benzodiazepine drugs before and after the addition of albumin, the binding constants were calculated and obtained with R.S.D. of less than 8%. The interactions of drugs with bovine serum albumin were investigated using Scatchard's plot. In addition, the consistency between the fractions of bound benzodiazepine calculated from the obtained K values and the experimental values were established. The results indicate that the second derivative method can be advantageously applicable to the determination of binding constants of drugs to serum albumin without prior separation. Moreover, the validity of the proposed method was confirmed.

Chemical Shifts and Lifetimes for Nuclear Magnetic Resonance (NMR) Analysis of Biofuels

Determination of the molecular composition of biofuels is critical to process development. Because biofuels, such as pyrolysis oil, contain hundreds of compounds, quantitative determination of the mixtures is a formidable task and is often not necessary for routine development work. 13C and 1H nuclear magnetic resonance (NMR) offer a reasonable trade-off between functional group identification and analytical measurement effort. However, accuracy depends upon selection of chemical-shift regions, baseline compensation, and correction for incomplete longitudinal relaxation effects. We propose chemical-shift assignments and T1 correction factors based on 13C and 1H NMR measurements of over 50 compounds that have been previously identified in pyrolysis oils and several plant natural products, especially terpenes. The results are intended to allow for a semiquantitative assessment of molecular composition of bio-oils on a time scale of 1−8 h to provide feedback for process development.