Large Amount Of Spectrum Research Articles

Application of semi-supervised convolutional neural network regression model based on data augmentation and process spectral labeling in Raman predictive modeling of cell culture processes

Raman spectroscopy coupled to chemometric model-based technology have a great potential for real-time monitoring of critical process parameters in animal cell culture. The measurement of off-line reference values required for calibration of monitoring procedures is complex, time- and resource-intensive, whereas the acquisition of spectra is a seconds- or minutes-based process. Usually, less than 5% spectra is labeled with off-line data during calibration steps, thus a large amount of spectra is wasted. In this study, we proposed a Semi-Supervised Convolutional Neural Network Regression (SSCNNR) model framework for Raman model establishment based on data augmentation and process spectra labeling. Compared with the original CNNR model, the size of the calibration dataset was expanded from 132 samples to nearly 8500, and the constructed SSCNNR models obtained a significantly improved accuracy in predicting glucose, glutamine, asparagine, and ammonium, with RMSEP values decreased by 29.1%, 37.3%, 38.3% and 7%, respectively. Compared with traditional modeling approach of PLSR and SVR, the SSCNNR models were proved to accurately predict the trend of substance concentration during frequent feeding process. Based on this framework, potential efforts included improving model prediction accuracy by hyperparameters optimization and accommodating scenarios of culture change by transfer learning.

Bilişsel radyo ağlar için servis kalitesini esas alan fiyat politikası

Recently, a large amount of spectrum and bandwidth are demanded by mobile network operators (MNOs) in order to obtain the high data rates quality of service (QoS). For optimal spectrum utilization for better efficiency, MNO should handle unused spectrums through a convenient spectrum management. Significantly, MNOs should trade-off among the proposed QoS, service pricing and secondary users’ (SUs) satisfaction. In this study, adaptive spectrum management based on the requesting SUs’ (RSUs) QoS requirement is proposed in cognitive radio network (CRN). QoS-driven pricing policy is developed so that MNO charges RSUs fairly while improving spectrum utilization and network revenue (NR) efficiency in the long term. Simulation results illustrate the RSUs charging strategy based on dynamic switch system in off-peak and peak hours.

On opportunistic spectrum access in radar bands: Lessons learned from measurement of weather radar signals

The need for extra spectrum and the fact that a large amount of spectrum below 6 GHz is allocated to radar systems has motivated regulatory bodies and researchers to investigate the feasibility of dynamic spectrum access in radar bands. To design efficient wireless communication schemes that coexist with radar systems, it is essential that the wireless community thoroughly understand the operations of these systems in different bands. This article studies incumbent operations and usage patterns in the 5 GHz band, where weather radar systems dominate, dynamic frequency selection is employed as a sharing mechanism, and recent works have explored the possibility to temporally share the spectrum with such radar systems. We present a measurement-based study of spectrum usage by a weather radar in Finland. Our measurement results show that the weather radar's scan patterns are quasi-periodic, and that use of sensing may not reliably detect radar signals due to its quasi-periodic scanning patterns and different vertical scanning angles. Finally, we present a framework for a database-assisted temporal sharing coexistence mechanism that takes into account the real occupancy behavior of the radar.

Identifying Carbon stars from the LAMOST pilot survey with the efficient manifold ranking algorithm

Carbon stars are excellent kinematic tracers of galaxies and can serve as a viable standard candle, so it is worthwhile to automatically search for them in a large amount of spectra. In this paper, we apply the efficient manifold ranking algorithm to search for carbon stars from the Large Sky Area Multi-Object Fiber Spectroscopic Telescope (LAMOST) pilot survey, whose performance and robustness are verified comprehensively with four test experiments. Using this algorithm, we find a total of 183 carbon stars, and 158 of them are new findings. According to different spectral features, our carbon stars are classified as 58 C-H stars, 11 C-H star candidates, 56 C-R stars, ten C-R star candidates, 30 C-N stars, three C-N star candidates, and four C-J stars. There are also ten objects which have no spectral type because of low spectral quality, and a composite spectrum consisting of a white dwarf and a carbon star. Applying the support vector machine algorithm, we obtain the linear optimum classification plane in the J – H versus H – Ks color diagram which can be used to distinguish C-H from C-N stars with their J – H and H – Ks colors. In addition, we identify 18 dwarf carbon stars with their relatively high proper motions, and find three carbon stars with FUV detections likely have optical invisible companions by cross matching with data from the Galaxy Evolution Explorer. In the end, we detect four variable carbon stars with the Northern Sky Variability Survey, the Catalina Sky Survey and the LINEAR variability databases. According to their periods and amplitudes derived by fitting light curves with a sinusoidal function, three of them are likely semiregular variable stars and one is likely a Mira variable star.

Error-free phase correction of interferograms using digital all-pass filters

We present a novel method for the phase correction of FT-IR interferograms that can produce spectra free of photometric errors. It is based on the design and application of an all-pass digital filter whose phase response is the opposite to that of the interferogram. After filtering, the interferogram becomes nearly (or completely, depending on the computational effort) phase-error-free and subsequent Fourier transforming yields accurate spectra. To virtually eliminate any photometric error, this method can be followed up by the Mertz method, which given that the filtered interferogram is nearly symmetric, will generate no errors. Without the filtering, Mertz method was shown to introduce photometric error in FT-IR spectra. When stored filter coefficients are used, this method is orders of magnitude faster than the Mertz method, while still keeping the photometric error within acceptable levels. This advantage of the method could be used, for example, in hyper-spectral imaging applications where a large amount of spectra from infrared focal plane arrays needs to be collected and processed in (near) real time. The method can be easily implemented in DSP circuits. Examples of phase correction of double-sided interferograms using both the Mertz and the all-pass filter method were given and photometric accuracy compared.

Calibration of the Faber-Jackson relation for M31 globular clusters using Hipparcos data

In this paper we present a data analysis regarding globular clusters as possible extragalactic distance indicators. For this purpose, we collected all velocity dispersion measurements published for galactic and M31 globular clusters. The slope and the zero-point of the Faber-Jackson relation were calibrated using Hipparcos distance measurements, and the relation was applied to extragalactic globular clusters in M31. A distance modulus of 24.12 \pm 0.45 mag was found. This is coherent with what is found by fitting the red giant branches of globular clusters (24.47 \pm 0.07, Holland 98), and is found from the peak of globular clusters luminosity function (24.03 \pm 0.23, Ostriker an d Gnedin 97), but shorter than the 24.7 \pm 0.2 mag (Lanoix et al. 98) and 24.77 \pm 0.11 mag (Feast and Catchpole 97), obtained by using Hipparcos data to calibrate the Cepheid period-luminosity. This calibrated Faber-Jackson relation can now be directly use for other Sc galaxies with resolved globular clusters, as soon as large amounts of spectra will become available, e.g., through the VLT.