scholarly journals Retrieving Performances of Vortex Beams with GS Algorithm after Transmitting in Different Types of Turbulences

2019 ◽  
Vol 9 (11) ◽  
pp. 2269 ◽  
Author(s):  
Maxime Irene Dedo ◽  
Zikun Wang ◽  
Kai Guo ◽  
Yongxuan Sun ◽  
Fei Shen ◽  
...  
Keyword(s):  
Random Phase ◽  
Power Density Spectrum ◽  
Structural Parameter ◽  
Phase Front ◽  
Simulation Environment ◽  
Free Space Optical ◽  
Density Spectrum ◽  
Different Types ◽  
Phase Screens ◽  
Better Than

The transmission of the orbital angular momentum (OAM) beam has attracted a lot of attention in the field of free-space optical (FSO) communication. Usually, after transmitting in atmospheric turbulences, the helical phase-front of OAM beams will be severely distorted, and there will exist the intermode crosstalk. As a result, the performance of the communication system will degrade significantly. In this paper, we have investigated the influences of the level of the turbulence strength to the transmitting OAM beams by changing the refractive-index structural parameter of C n 2 and the number of turbulence random phase screens of N in simulation environment. Then, by adopting the Gerchberg-Saxton (GS) algorithm, which can be used to compute the pre-compensation phase and correct the distorted OAM beams, the retrieving performances of transmitting single and multiplexed OAM beams under different turbulence strengths were also investigated. The simulation results show that with increasing the atmospheric-turbulence strength levels determined by the parameters C n 2 and N, the retrieving performances decrease dramatically. When the turbulence strength level is selected within an appropriate range, the OAM beams can be effectively retrieved by adopting GS algorithm and observing the power density spectrum. Notably, the retrieving performance for the transmission of a single OAM beam is better than that of the multiplexing OAM beam.

scholarly journals RECOGNIZING DIFFERENT TYPES OF STOCHASTIC PROCESSES

2006 ◽  
Vol 06 (01) ◽  
pp. L1-L6
Author(s):  
JONG U. KIM ◽  
LASZLO B. KISH
Keyword(s):  
Image Processing ◽  
Stochastic Processes ◽  
Cross Correlation ◽  
Correlation Method ◽  
Correlation Coefficients ◽  
Power Density Spectrum ◽  
Density Spectrum ◽  
Random Telegraph Signals ◽  
Different Types ◽  
Coefficient Method

We propose a new cross-correlation method that can recognize independent realizations of the same type of stochastic processes and can be used as a new kind of pattern recognition tool in biometrics, sensing, forensic, security and image processing applications. The method, which we call bispectrum correlation coefficient method, makes use of the cross-correlation of the bispectra. Three kinds of cross-correlation coefficients are introduced. To demonstrate the new method, six different random telegraph signals are tested, where four of them have the same power density spectrum. It is shown that the three coefficients can map the different stochastic processes to specific sub-volumes in a cube.

Design, Development and Comparison of Heuristic Driven Algorithms Based on the Crossed Domain Products’ Reviews for User’s Summarization

2020 ◽  
Vol 13 (5) ◽  
pp. 884-892
Author(s):  
Sartaj Ahmad ◽  
Ashutosh Gupta ◽  
Neeraj Kumar Gupta
Keyword(s):  
Decision Making ◽  
Online Shopping ◽  
Recent Time ◽  
Design Development ◽  
Different Types ◽  
Feature Based ◽  
Use Of Internet ◽  
Day By Day ◽  
Better Than

Background: In recent time, people love online shopping but before any shopping feedbacks or reviews always required. These feedbacks help customers in decision making for buying any product or availing any service. In the country like India this trend of online shopping is increasing very rapidly because awareness and the use of internet which is increasing day by day. As result numbers of customers and their feedbacks are also increasing. It is creating a problem that how to read all reviews manually. So there should be some computerized mechanism that provides customers a summary without spending time in reading feedbacks. Besides big number of reviews another problem is that reviews are not structured. Objective: In this paper, we try to design, implement and compare two algorithms with manual approach for the crossed domain Product’s reviews. Methods: Lexicon based model is used and different types of reviews are tested and analyzed to check the performance of these algorithms. Results: Algorithm based on opinions and feature based opinions are designed, implemented, applied and compared with the manual results and it is found that algorithm # 2 is performing better than algorithm # 1 and near to manual results. Conclusion: Algorithm # 2 is found better on the different product’s reviews and still to be applied on other product’s reviews to enhance its scope. Finally, it will be helpful to automate existing manual process.

BER performance analysis of FSO using hybrid-SIM technique with APD receiver over weak and strong turbulence channels

2021 ◽  
Vol 0 (0) ◽  
Author(s):  
Rajat Kumar Giri
Keyword(s):  
Performance Improvement ◽  
System Performance ◽  
Avalanche Photodiode ◽  
Free Space Optical ◽  
Error Performance ◽  
Strong Turbulence ◽  
Meijer G Function ◽  
Hermite Approximation ◽  
Ber Performance ◽  
Better Than

Abstract In this paper, a hybrid-subcarrier-intensity-modulation (hybrid-SIM) technique for the performance improvement of free-space-optical (FSO) communication system has been proposed. Subsequently, for further error performance improvement, avalanche photodiode (APD) based receiver is used in the proposed system. The system performance is analyzed at various atmospheric turbulence levels over weak and strong turbulence channels. The bit error rate (BER) is theoretically derived using Gauss–Hermite approximation and Meijer-G function and it is simulated in the MATLAB environment. The simulation result shows that the BER performance of hybrid-SIM is better than BPSK-SIM technique irrespective of the channel types and also the significant BER performance improvement is observed by APD receiver.

scholarly journals Properties of Faint X-ray Activity of XTE J1908+094 in 2019

Galaxies ◽  
2021 ◽  
Vol 9 (2) ◽  
pp. 25
Author(s):  
Debjit Chatterjee ◽  
Arghajit Jana ◽  
Kaushik Chatterjee ◽  
Riya Bhowmick ◽  
Sujoy Kumar Nath ◽  
...  
Keyword(s):  
Black Hole ◽  
Temporal Analysis ◽  
Power Density Spectrum ◽  
Periodic Oscillations ◽  
Telescope Array ◽  
Density Spectrum ◽  
X Ray ◽  
Black Hole Candidate ◽  
Short Period ◽  
Spectral State

We study the properties of the faint X-ray activity of Galactic transient black hole candidate XTE J1908+094 during its 2019 outburst. Here, we report the results of detailed spectral and temporal analysis during this outburst using observations from Nuclear Spectroscopic Telescope Array (NuSTAR). We have not observed any quasi-periodic-oscillations (QPOs) in the power density spectrum (PDS). The spectral study suggests that the source remained in the softer (more precisely, in the soft–intermediate) spectral state during this short period of X-ray activity. We notice a faint but broad Fe Kα emission line at around 6.5 keV. We also estimate the probable mass of the black hole to be 6.5−0.7+0.5M⊙, with 90% confidence.

scholarly journals Fighting Together against the Pandemic: Learning Multiple Models on Tomography Images for COVID-19 Diagnosis

AI ◽  
2021 ◽  
Vol 2 (2) ◽  
pp. 261-273
Author(s):  
Mario Manzo ◽  
Simone Pellino
Keyword(s):  
Network Architecture ◽  
State Of The Art ◽  
Ensemble Classification ◽  
Effective Vaccine ◽  
Rt Pcr ◽  
Neural Network Architecture ◽  
Experimental Phase ◽  
Different Types ◽  
Polymerase Chain ◽  
Better Than

COVID-19 has been a great challenge for humanity since the year 2020. The whole world has made a huge effort to find an effective vaccine in order to save those not yet infected. The alternative solution is early diagnosis, carried out through real-time polymerase chain reaction (RT-PCR) tests or thorax Computer Tomography (CT) scan images. Deep learning algorithms, specifically convolutional neural networks, represent a methodology for image analysis. They optimize the classification design task, which is essential for an automatic approach with different types of images, including medical. In this paper, we adopt a pretrained deep convolutional neural network architecture in order to diagnose COVID-19 disease from CT images. Our idea is inspired by what the whole of humanity is achieving, as the set of multiple contributions is better than any single one for the fight against the pandemic. First, we adapt, and subsequently retrain for our assumption, some neural architectures that have been adopted in other application domains. Secondly, we combine the knowledge extracted from images by the neural architectures in an ensemble classification context. Our experimental phase is performed on a CT image dataset, and the results obtained show the effectiveness of the proposed approach with respect to the state-of-the-art competitors.

scholarly journals Deep Learning Methods for Classification of Certain Abnormalities in Echocardiography

Electronics ◽  
2021 ◽  
Vol 10 (4) ◽  
pp. 495
Author(s):  
Imayanmosha Wahlang ◽  
Arnab Kumar Maji ◽  
Goutam Saha ◽  
Prasun Chakrabarti ◽  
Michal Jasinski ◽  
...  
Keyword(s):  
Deep Learning ◽  
Short Term Memory ◽  
Support Vector ◽  
Variational Autoencoder ◽  
Different Types ◽  
Static Images ◽  
Long Short Term Memory ◽  
2D And 3D ◽  
Better Than

This article experiments with deep learning methodologies in echocardiogram (echo), a promising and vigorously researched technique in the preponderance field. This paper involves two different kinds of classification in the echo. Firstly, classification into normal (absence of abnormalities) or abnormal (presence of abnormalities) has been done, using 2D echo images, 3D Doppler images, and videographic images. Secondly, based on different types of regurgitation, namely, Mitral Regurgitation (MR), Aortic Regurgitation (AR), Tricuspid Regurgitation (TR), and a combination of the three types of regurgitation are classified using videographic echo images. Two deep-learning methodologies are used for these purposes, a Recurrent Neural Network (RNN) based methodology (Long Short Term Memory (LSTM)) and an Autoencoder based methodology (Variational AutoEncoder (VAE)). The use of videographic images distinguished this work from the existing work using SVM (Support Vector Machine) and also application of deep-learning methodologies is the first of many in this particular field. It was found that deep-learning methodologies perform better than SVM methodology in normal or abnormal classification. Overall, VAE performs better in 2D and 3D Doppler images (static images) while LSTM performs better in the case of videographic images.

System of retinal visual acuity determination based on random phase screens for diagnostics of initial shapes of cataracts

2003 ◽  
Author(s):  
Alexander V. Novokhreshenov ◽  
Valery V. Bakutkin ◽  
Valery V. Tuchin ◽  
Vladimir P. Ryabukho ◽  
Irina L. Maksimova ◽  
...  
Keyword(s):  
Visual Acuity ◽  
Random Phase ◽  
Phase Screens

Etude par spectrométrie infrarouge de l'action de solvants aprotiques sur l'association ester–eau et ester–Ba2+. Discussion du rôle catalytique du solvant et de l'ion Ba2+ dans l'hydrolyse alcaline du propionate de methyle

1979 ◽  
Vol 57 (4) ◽  
pp. 400-403 ◽  
Author(s):  
Anne Le Narvor ◽  
Pierre Saumagne
Keyword(s):  
Ir Spectra ◽  
Charge Density ◽  
Carbonyl Group ◽  
Alkaline Hydrolysis ◽  
Experimental Results ◽  
Methyl Propionate ◽  
Orbital Control ◽  
Different Types ◽  
Kinetics Of ◽  
Better Than

The ir spectra of mixtures of methyl propionate/water and methyl propionate/Ba2+ in dimethylsulfoxide and in acetonitrile have been recorded in the region of the νCO mode of the ester. Evidence is presented to indicate the presence of different types of complexes; their concentration was determined as a function of the composition of the medium. The spectroscopic results are compared to those from the kinetics of the alkaline hydrolysis in the same conditions. It is demonstrated that the orbital control explains the experimental results better than does the charge density on the carbon of the carbonyl group. [Journal translation]

scholarly journals The relevance of non-stationarities and non-Gaussianities in vibration fatigue

2018 ◽  
Vol 165 ◽  
pp. 10011 ◽  
Author(s):  
Martin Česnik ◽  
Janko Slavič ◽  
Lorenzo Capponi ◽  
Massimiliano Palmieri ◽  
Filippo Cianetti ◽  
...  
Keyword(s):  
Frequency Domain ◽  
Dynamic Loading ◽  
Amplitude Modulation ◽  
Time History ◽  
Power Density Spectrum ◽  
Time To Failure ◽  
Density Spectrum ◽  
Frequency Domain Methods ◽  
Vibration Fatigue ◽  
Non Gaussian

In classical fatigue of materials, the frequency contents of dynamic loading are well below the natural frequencies of the observed structure or test specimen. However, when dealing with vibration fatigue the frequency contents of dynamic loading and structure's dynamic response overlap, resulting in amplified stress loads of the structure. For such cases, frequency counting methods are especially convenient. Gaussianity and stationarity assumptions are applied in frequency-domain methods for obtaining dynamic structure's response and frequency-domain methods for calculating damage accumulation rate. Since it is common in real environments for the structure to be excited with non-Gaussian and non-stationary loads, this study addresses the effects of such dynamic excitation to experimental time-to-failure of a structure. Initially, the influence of non-Gaussian stationary excitation is experimentally studied via excitation signals with equal power density spectrum and different values of kurtosis. Since no relevant changes of structure's time-to-failure were observed, the study focused on non-stationary excitation signals that are also inherently non-Gaussian. The non-stationarity of excitation was achieved by amplitude modulation and significantly shorter times-to-failure were observed when compared to experiments with stationary non-Gaussian excitation. Additionally, the structure's time-to-failure varied with the rate of the amplitude modulation. To oversee this phenomenon the presented study proposes a non-stationarity index which can be obtained from the excitation time history. The non-stationarity index was experimentally confirmed as a reliable estimator for severity of non-stationary excitation. The non-stationarity index is used to determine if the frequencydomain methods can safely be applied for time-to-failure calculation.

The structures of benzimidazole derivatives and their potential as tuberculostatics

2018 ◽  
Vol 74 (12) ◽  
pp. 1684-1691
Author(s):  
Marek L. Główka ◽  
Sylwia Kałużyńska ◽  
Malwina Krause ◽  
Katarzyna Gobis ◽  
Henryk Foks ◽  
...  
Keyword(s):  
Multidrug Resistant ◽  
Benzimidazole Derivatives ◽  
X Ray Diffraction ◽  
Intermolecular Hydrogen Bonds ◽  
X Ray ◽  
Resistant Varieties ◽  
Different Types ◽  
Mdr Tb ◽  
Aromatic Systems ◽  
Better Than

Tuberculosis still remains a very important problem, especially its multidrug resistant varieties (MDR-TB). Among the potential tuberculostatics, there are two benzimidazole derivatives, namely 5,6-dimethyl-2-phenylethylbenzo[d]imidazole (1) and (E)-5,6-dimethyl-2-styryl-1H-benzo[d]imidazole (2) which showed significant tuberculostatic activities, better than those of Pyrazinamide and Isoniazyd. Also, the cytotoxicity of 1 appeared promising. The compounds were studied (with the use of X-ray diffraction) in the form of the hemihydrate of 1, C17H18N2·0.5H2O (1a), the methanol hemisolvate of 2, C17H16N2·0.5CH3OH (2a), and the acid oxalate salt of 2, namely (E)-5,6-dimethyl-2-styryl-1H-benzo[d]imidazolium hydrogen oxalate, C17H17N2 +·C2HO4 − (2b). All three structures reveal a similar extended conformation, despite the flexible linker between the two aromatic systems and the different types of strong intermolecular hydrogen bonds. The molecules of 2a are practically planar due to the double bond in the linker, which enables conjugation along the whole molecule, while the molecules of 1a exhibit the possibility of parallel orientations of their aromatic systems, despite the aliphatic (ethyl) linker.

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