Готові списки джерел за темами / Golay Cell

Добірка наукової літератури з теми "Golay Cell"

Автор: Grafiati
Опубліковано: 1 квітня 2023

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Статті в журналах з теми "Golay Cell"

1

Yamashita, Kaoru, Akishi Murata, and Masanori Okuyama. "Miniaturized infrared sensor using silicon diaphragm based on Golay cell." Sensors and Actuators A: Physical 66, no. 1-3 (April 1998): 29–32. http://dx.doi.org/10.1016/s0924-4247(97)01702-0.

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2

Gaudreault, Charles, Joanny Salvas, and Joël Sirois. "Savitzky–Golay smoothing and differentiation for polymerase chain reaction quantification." Biochemistry and Cell Biology 96, no. 3 (June 2018): 380–89. http://dx.doi.org/10.1139/bcb-2016-0194.

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Анотація:
In quantitative PCR (qPCR), replicates can minimize the impact of intra-assay variation; however, inter-assay variations must be minimized to obtain a robust quantification method. The method proposed in this study uses Savitzky–Golay smoothing and differentiation (SGSD) to identify a derivative-maximum-based cycle of quantification. It does not rely on curve modeling, as is the case with many existing techniques. PCR fluorescence data sets challenged for inter-assay variations (different thermocycler units, different reagents batches, different operators, different standard curves, and different labs) were used for the evaluation. The algorithm was compared with a four-parameter logistic model (4PLM) method, the Cy0 method, and the threshold method. The SGSD method compared favourably with all methods in terms of inter-assay variation. SGSD was statistically different from the 4PLM (P = 0.03), Cy0 (P = 0.05), and threshold (P = 0.004) methods on relative error comparison basis. For intra-assay variations, SGSD outperformed the threshold method (P = 0.005) and equalled the 4PLM and Cy0 methods (P > 0.05) on relative error basis. Our results demonstrate that the SGSD method could potentially be an alternative to sigmoid modeling based methods (4PLM and Cy0) when PCR data are challenged for inter-assay variations.
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3

Huang, Yue, Yuting Yang, Hang Xu, Gang Zhao, Liwen Feng, Jinqiang Xu, Senlin Huang, and Kexin Liu. "The impact of modulation parameters on the responsivity of Golay cell measuring terahertz radiation." Infrared Physics & Technology 125 (September 2022): 104290. http://dx.doi.org/10.1016/j.infrared.2022.104290.

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4

Desmaris, Vincent, Hawal Rashid, Alexey Pavolotsky, and Victor Belitsky. "Design, simulations and optimization of micromachined Golay-cell based THz sensors operating at room temperature." Procedia Chemistry 1, no. 1 (September 2009): 1175–78. http://dx.doi.org/10.1016/j.proche.2009.07.293.

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5

Pei, Jie, and Gang Chen. "Design of Terahertz-Wave Transmission Imaging System." Applied Mechanics and Materials 347-350 (August 2013): 1940–44. http://dx.doi.org/10.4028/www.scientific.net/amm.347-350.1940.

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Анотація:
An imaging system based on the transmission and reflection modes in the terahertz (THz) region is developed by using a backward-wave oscillator (BWO) as source, a Golay-Cell as detector, and an oscilloscope as data acquisition unit. The system software based on the oscilloscope is designed to control the object movement, and the capture and display of the continuous THz wave image data. The imaging of different objects is tested at the frequencies of 450 GHz and 890 GHz to show the validity of the imaging system at room temperature. The influence of objects humidity and thickness, incident wavelength, and translation step on the THz imaging is discussed in details.
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6

Barton, Sinead, Salaheddin Alakkari, Kevin O’Dwyer, Tomas Ward, and Bryan Hennelly. "Convolution Network with Custom Loss Function for the Denoising of Low SNR Raman Spectra." Sensors 21, no. 14 (July 6, 2021): 4623. http://dx.doi.org/10.3390/s21144623.

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Анотація:
Raman spectroscopy is a powerful diagnostic tool in biomedical science, whereby different disease groups can be classified based on subtle differences in the cell or tissue spectra. A key component in the classification of Raman spectra is the application of multi-variate statistical models. However, Raman scattering is a weak process, resulting in a trade-off between acquisition times and signal-to-noise ratios, which has limited its more widespread adoption as a clinical tool. Typically denoising is applied to the Raman spectrum from a biological sample to improve the signal-to-noise ratio before application of statistical modeling. A popular method for performing this is Savitsky–Golay filtering. Such an algorithm is difficult to tailor so that it can strike a balance between denoising and excessive smoothing of spectral peaks, the characteristics of which are critically important for classification purposes. In this paper, we demonstrate how Convolutional Neural Networks may be enhanced with a non-standard loss function in order to improve the overall signal-to-noise ratio of spectra while limiting corruption of the spectral peaks. Simulated Raman spectra and experimental data are used to train and evaluate the performance of the algorithm in terms of the signal to noise ratio and peak fidelity. The proposed method is demonstrated to effectively smooth noise while preserving spectral features in low intensity spectra which is advantageous when compared with Savitzky–Golay filtering. For low intensity spectra the proposed algorithm was shown to improve the signal to noise ratios by up to 100% in terms of both local and overall signal to noise ratios, indicating that this method would be most suitable for low light or high throughput applications.
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7

Wang, Yuye, Gang Nie, Changhao Hu, Kai Chen, Chao Yan, Bin Wu, Junfeng Zhu, Degang Xu, and Jianquan Yao. "High-sensitive terahertz detection by parametric up-conversion using nanosecond pulsed laser." Chinese Physics B 31, no. 2 (February 1, 2021): 024204. http://dx.doi.org/10.1088/1674-1056/ac2d20.

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Анотація:
A high-sensitive terahertz detector operating at room temperature was demonstrated based on parametric up-conversion. A nanosecond 1064-nm Nd:YAG laser was used to pump the parametric up-conversion detector and the up-conversion from terahertz wave to NIR laser was realized in a lithium niobate crystal. The minimum detectable terahertz energy of 9 pJ was realized with the detection dynamic range of 54 dB, which was three orders of magnitude higher than that of commercial Golay cell. The detectable terahertz frequency range of the detection system was 0.90 Thz–1.83 THz. Besides, the effects of pump energy and effective gain length on the detection sensitivity were studied in experiment. The results showed that higher pump energy and longer effective gain length are helpful for improving the detection sensitivity of parametric up-conversion detector.
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8

Xu, Chenhua, Zhicheng Tu, Wenjie Zhang, Jian Cen, Jianbin Xiong, and Na Wang. "A Method of Optimizing Cell Voltage Based on STA-LSSVM Model." Mathematics 10, no. 24 (December 12, 2022): 4710. http://dx.doi.org/10.3390/math10244710.

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Анотація:
It is challenging to control and optimize the aluminum electrolysis process due to its non-linearity and high energy consumption. Reducing the cell voltage is crucial for energy consumption reduction. This paper presents an intelligent method of predicting and optimizing cell voltage based on the evaluation of modeling the comprehensive cell state. Firstly, the Savitzky–Golay filtering algorithm(SGFA) is adopted to denoise the sample data to improve the accuracy of the experimental model. Due to the influencing factors of the cell state, a comprehensive evaluation model of the cell state is established. Secondly, the model of the least squares supports vector machine (LSSVM) is proposed to predict the cell voltage. In order to improve the accuracy of the model, the state transition algorithm (STA) is employed to optimize the structure parameters of the model. Thirdly, the optimization and control model of the cell voltage is developed by an analysis of the technical conditions. Then, the STA is used to realize the optimization of the front model. Finally, the actual data were applied to the experiments of the above method, and the proposed STA was compared with other methods. The results of experiments show that this method is efficient and satisfactory. The optimization value of average cell voltage based on the STA-LSSVM is 3.8165v, and it can be used to guide process operation. The DC power consumption is 11,971 KW·h per tonne of aluminum, with a reduction in power consumption of 373 KW·h. This result guarantees the reduction of aluminum electrolysis energy consumption.
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9

Li, Lian, Baoyang Ding, Qi Yang, Shang Chen, Huaying Ren, Jinfeng Wang, Hengchang Zang, Fengshan Wang, and Lixuan Zang. "The relevance study of effective information between near infrared spectroscopy and chondroitin sulfate in ethanol precipitation process." Journal of Innovative Optical Health Sciences 07, no. 06 (October 21, 2014): 1450022. http://dx.doi.org/10.1142/s1793545814500229.

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Анотація:
Near infrared spectroscopy (NIRS) is based on molecular overtone and combination vibrations. It is difficult to assign specific features under complicated system. So it is necessary to find the relevance between NIRS and target compound. For this purpose, the chondroitin sulfate (CS) ethanol precipitation process was selected as the research model, and 90 samples of 5 different batches were collected and the content of CS was determined by modified carbazole method. The relevance between NIRS and CS was studied throughout optical pathlength, pretreatment methods and variables selection methods. In conclusion, the first derivative with Savitzky–Golay (SG) smoothing was selected as the best pretreatment, and the best spectral region was selected using interval partial least squares (iPLS) method under 1 mm optical cell. A multivariate calibration model was established using PLS algorithm for determining the content of CS, and the root mean square error of prediction (RMSEP) is 3.934 g⋅L-1. This method will have great potential in process analytical technology in the future.
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10

Черномырдин, Н. В., А. С. Кучерявенко, Е. Н. Римская, И. Н. Долганова, В. А. Желнов, П. А. Каралкин, А. А. Грядунова та ін. "Терагерцовый микроскоп на основе эффекта твердотельной иммерсии для визуализации биологических тканей-=SUP=-*-=/SUP=-". Журнал технической физики 126, № 5 (2019): 642. http://dx.doi.org/10.21883/os.2019.05.47665.14-19.

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Анотація:
A novel method of terahertz (THz) microscopy was proposed for imaging of biological tissues with sub-wavelength spatial resolution. It allows for overcoming the Abbe diffraction limit and provides a sub-wavelength resolution thanks to the solid immersion effect – i.e. to the reduction in the dimensions of electromagnetic beam caustic, when the beam is focused in free space, at a small distance (smaller than the wavelength) behind the medium featuring high refractive index. An experimental setup realizing the proposed method was developed. It uses a backward wave oscillator, as a THz-wave emitter, and a Golay cell, as a THz-wave detector. In this setup, the radiation is focused behind the silicon hemisphere in order to realize the solid immersion effect. The spatial resolution of 0.15λ was demonstrated for the developed microscope, while the measurements were carried out at the wavelength of λ=500 μm, with the metal-air interface as a test object. Such a high spatial resolution represents a significant advantage over that of the previously reported arrangements of solid immersion microscopes. The solid immersion microscopy does not imply using any diaphragms or other near-field probes for achieving the sub-wavelength spatial resolution; thus, it eliminates the energy losses associated with such elements. The proposed methods were applied for imaging of biological tissues, and the observed results highlight its potential in biology and medicine.
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Дисертації з теми "Golay Cell"

1

Golat, Brian [Verfasser], Wolfram-H. [Akademischer Betreuer] Zimmermann, Rüdiger [Gutachter] Behr, Lutz [Gutachter] Walter, Ralf [Gutachter] Dressel, Stefan [Gutachter] Luther, and Steven [Gutachter] Johnsen. "Development of a Rhesus macaque engineered heart muscle model from pluripotent stem cells / Brian Golat ; Gutachter: Rüdiger Behr, Lutz Walter, Ralf Dressel, Stefan Luther, Steven Johnsen ; Betreuer: Wolfram-H. Zimmermann." Göttingen : Niedersächsische Staats- und Universitätsbibliothek Göttingen, 2017. http://d-nb.info/1135487715/34.

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Частини книг з теми "Golay Cell"

1

Khanna, Vinod Kumar. "Bolometers, Golay cells and pyroelectric detectors." In Practical Terahertz Electronics: Devices and Applications, Volume 2. IOP Publishing, 2021. http://dx.doi.org/10.1088/978-0-7503-4886-7ch1.

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Тези доповідей конференцій з теми "Golay Cell"

1

Fernandes, L. O. T., P. Kaufmann, R. Marcon, A. S. Kudaka, A. Marun, R. Godoy, E. C. Bortolucci, M. Beny Zakia, and J. A. Diniz. "Photometry of THz radiation using Golay cell detector." In 2011 XXXth URSI General Assembly and Scientific Symposium. IEEE, 2011. http://dx.doi.org/10.1109/ursigass.2011.6051287.

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2

Ledwosinska, Elizabeth, Thomas Szkopek, Abdeladim Guermoune, and Mohamed Siaj. "Application of graphene membrane in micro-Golay cell array." In SPIE OPTO, edited by Laurence P. Sadwick and Créidhe M. O'Sullivan. SPIE, 2012. http://dx.doi.org/10.1117/12.914054.

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3

Denison, Douglas R., Michael E. Knotts, Harley T. Hayden, Seth L. Young, and Vladimir V. Tsukruk. "Influence of micro-Golay cell cavity diameter on millimeter-wave detection sensitivity." In 2011 36th International Conference on Infrared, Millimeter, and Terahertz Waves (IRMMW-THz 2011). IEEE, 2011. http://dx.doi.org/10.1109/irmmw-thz.2011.6104982.

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4

Rashid, Hawal, Vincent Desmaris, and Victor Belitsky. "Design and simulations of a micromachined Golay-cell based THz sensors for room temperature imaging applications." In 2010 35th International Conference on Infrared, Millimeter, and Terahertz Waves (IRMMW-THz 2010). IEEE, 2010. http://dx.doi.org/10.1109/icimw.2010.5612978.

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5

Stefanova, Polina S., Jonathan M. Hammler, Andreas K. Klein, Andrew J. Gallant, and Claudio Balocco. "Polymer-based micro-golay cells for THz detection." In 2016 41st International Conference on Infrared, Millimeter, and Terahertz waves (IRMMW-THz). IEEE, 2016. http://dx.doi.org/10.1109/irmmw-thz.2016.7758964.

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6

Ledwosinska, Elizabeth, Abdeladim Guermoune, Mohamed Siaj, and Thomas Szkopek. "Fabrication and characterization of suspended graphene membranes for miniature Golay cells." In SPIE OPTO, edited by Laurence P. Sadwick and Créidhe M. O'Sullivan. SPIE, 2013. http://dx.doi.org/10.1117/12.2008974.

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7

Denison, Douglas R., Michael E. Knotts, Michael E. McConney, and Vladimir V. Tsukruk. "Experimental characterization of mm-wave detection by a micro-array of Golay cells." In SPIE Defense, Security, and Sensing, edited by Roger Appleby and David A. Wikner. SPIE, 2009. http://dx.doi.org/10.1117/12.818387.

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