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Open Journal of Gastroenterology 2021年第5期11卷 75-80页

作者： k. Doumbia H. Sow M. Y. Dick. S. D. Sanogo M. S. Tounk.ra k. péliaba M. k.umaré G. Soumaré A. k.naté M. T. Diarra M. Y. Maiga Hepatogastroenterology Teaching Hospital Gabriel Touré Bamako Mali

Digestive hemorrhage by rupture of esophageal Varices is common and has a pejorative prognosis in our context. purpose: The main purpose of this work.was to study the digestive bleeding by esophageal varices and prognosis value of blood transfusion in the Hospital of Gabriel Touré. Methodology: It was a prospective study that took.place in the service of Hepato-gastroenterology of Gabriel Touré Hospital from June 2016 to May 2017 and from November 2017 to August 2018. Results: At the end of the study, 77 patients met the inclusion criteria out of 1396 patients hospitalized during the same period. Varices bleeding represented a prevalence of 5.5% among hospitalized patients during the same period. The average age of our patients was 46.58 ± 15.09 years. The male sex was more reported in our study with a prevalence of 67.5%. At admission, 63.2% had clinical anemia, 58.4% low arterial pressure and 50.6% hemoglobin rate less than 7 g/dL. Blood transfusion was indicated in 47 patients (61%). The mortality rate was 23.4% and was comparable in both groups (p = 0.0990). Early rebleeding was significantly observed in the case of transfusion (p = 0.0452). Hepatic encephalopathy was the leading cause of death of our patients with 72.2%. Conclusion: Digestive bleeding by esophageal varices is a worsen complication in cirrhosis in hospital setting. Transfusion has not significantly improved the prognosis of our patients.

关键词： Esophageal Varices Bleeding Blood Transfusion prognosis Gabriel Touré Hospital

Compression of Battery X-Ray Tomography Data with Machine Learning

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Chinese physics Letters 2024年第9期41卷 153-158页

作者： Zipei Yan Qiyu Wang Xiqian Yu Jizhou Li Michael k.-p.Ng Department of Electronic Engineering The Chinese University of Hong KongHong KongChina Beijing National Laboratory for Condensed Matter physics and Institute of PhysicsChinese Academy of SciencesBeijing 100190China Huairou Division Institute of PhysicsChinese Academy of SciencesBeijing 101400China Center of Materials Science and Optoelectronics Engineering University of Chinese Academy of SciencesBeijing 100049China CUHk.Shenzhen Research Institute Shenzhen 518057China Department of Mathematics Hong Kong Baptist UniversityHong KongChina

With the increasing demand for high-resolution x-ray tomography in battery characterization,the challenges of storing,transmitting,and analyzing substantial imaging data necessitate more efficient *** data compression methods struggle to balance reduction ratio and image quality,often failing to preserve critical details for accurate *** study proposes a machine learning-assisted compression method tailored for battery x-ray imaging *** physics-informed representation learning,our approach significantly reduces file sizes without sacrificing meaningful *** validate the method on typical battery materials and different x-ray imaging techniques,demonstrating its effectiveness in preserving structural and chemical *** results show an up-to-95 compression ratio while maintaining high fidelity in the projection and reconstructed *** proposed framework.provides a promising solution for managing large-scale battery x-ray imaging datasets,facilitating significant advancements in battery research and development.

关键词： battery Battery details

A Hybrid Machine Learning Approach for Improvised QoE in Video Services over 5G Wireless Network.

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Computers, Materials & Continua 2024年第3期78卷 3195-3213页

作者： k.B.Ajeyprasaath p.Vetrivelan School of Electronics Engineering Vellore Institute of TechnologyChennaiTamil Nadu600127India

Video streaming applications have grown considerably in recent *** a result,this becomes one of the most significant contributors to global internet *** to recent studies,the telecommunications industry loses millions of dollars due to poor video Quality of Experience(QoE)for *** the standard proposals for standardizing the quality of video streaming over internet service providers(ISps)is the Mean Opinion Score(MOS).However,the accurate finding of QoE by MOS is subjective and laborious,and it varies depending on the user.A fully automated data analytics framework.is required to reduce the inter-operator variability characteristic in QoE *** work.addresses this concern by suggesting a novel hybrid XGBStack.oE analytical model using a two-level layering *** one combines multiple Machine Learning(ML)models via a layer one Hybrid *** ML models at level one are trained using the entire training data *** level two Hybrid XGBStack.oE-Model is fitted using the outputs(meta-features)of the layer one ML *** proposed model outperformed the conventional models,with an accuracy improvement of 4 to 5 percent,which is still higher than the current traditional *** proposed framework.could significantly improve video QoE accuracy.

关键词： Hybrid XGBStack.oE-model machine learning MOS performance metrics QoE 5G video services

MDCN:Modified Dense Convolution Network.Based Disease Classification in Mango Leaves

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Computers, Materials & Continua 2024年第2期78卷 2511-2533页

作者： Chirag Chandrashek.r k.p.Vijayak.mar k.pradeep A.Balasundaram School of Computer Science and Engineering Vellore Institute of Technology(VIT)ChennaiIndia Center for Cyber physical Systems School of Computer Science and EngineeringVellore Institute of Technology(VIT)ChennaiIndia

The most widely farmed fruit in the world is *** the production and quality of the mangoes are hampered by many *** diseases need to be effectively controlled and ***,a quick.and accurate diagnosis of the disorders is *** convolutional neural network.,renowned for their independence in feature extraction,have established their value in numerous detection and classification ***,it requires large training datasets and several parameters that need careful *** proposed Modified Dense Convolutional Network.MDCN)provides a successful classification scheme for plant diseases affecting mango *** model employs the strength of pre-trained network. and modifies them for the particular context of mango leaf diseases by incorporating transfer learning *** data loader also builds mini-batches for training the models to reduce training ***,optimization approaches help increase the overall model’s efficiency and lower computing *** employed on the MangoLeafBD Dataset consists of a total of 4,000 *** the experimental results,the proposed system is compared with existing techniques and it is clear that the proposed algorithm surpasses the existing algorithms by achieving high performance and overall throughput.

关键词： Leaf disease detection deep convolutional neural network. transfer learning optimization MangoLeafBD Dataset

Emission colour tuning in k.nF_(4):Yb^(3+),Er^(3+)/Ho^(3+)phosphor

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Journal of Rare Earths 2024年第1期42卷 57-65,I0002页

作者： Janani k.Gayathri E Vijayatha V Ramasubramanian S Thiyagarajan p Department of Science and Humanities Nehru Institute of TechnologyKaliapuramThirumalayampalayamCoimbatoreIndia Department of Sciences Amrita School of Physical SciencesAmrita Vishwa VidyapeethamCoimbatoreIndia Department of physics Anna UniversityChennaiIndia

k.nF_(4):Yb^(3+),Er^(3+)/Ho^(3+)(Ln=Y,Yb,Gd)phosphors were prepared by solid-state reaction *** each of the Yb^(3+)/Er^(3+)and Yb^(3+)/Ho^(3+)co-doped phosphors independently,phase confirmation and morphological examination were accomplished using the X-ray diffraction technique and scanning electron microscope analysis.X-ray photoelectron spectroscopy analysis shows the charge state and existence of lanthanides and *** luminescence emissions of green and red colour were detected for the synthesized *** changes in the upconverted emission intensities and colour output pertaining to the change of the lanthanide host matrix along with dopants were investigated for the prepared *** the upconversion luminescence,erbium-doped samples exhibit a predominance of red emission while holmium-doped samples display a prevalence of green *** rare-earth Er/Ho doped k.bF4shows strong red emission compared to other ***_(4):Yb,Er/Ho exhibits relatively significant green upconve rsion emissions,while Yb,Er-doped k.dF_(4)host displays a 10-fold increase in green/red emission ratio with an increase in the input power of 20-780 *** photoluminescence studies and decay curve analysis were carried out using UV light excitation for the developed phosphors.A higher lifetime of 2.2 ms was measured for the downshifting red emission in the Ho doped k.bF_(4)*** study suggests a potential for colour tunability in the upconversion and downshifting emissions through host modifications to the fluoride phosphor.

关键词： Rare earths Energy transfer upconversion Downshifting Colour coordinates

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LiDAR-based estimation of bounding box coordinates using Gaussian process regression and particle swarm optimization

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Biomimetic Intelligence & Robotics 2024年第1期4卷 24-35页

作者： Vinodha k. E.S.Gopi Tushar Agnibhoj Department of Electronics and Communication Engineering National Institute of Technology TiruchirappalliTamil Nadu620015India

Camera-based object track.ng systems in a given closed environment lack.privacy and *** this study,light detection and ranging(LiDAR)was applied to track.objects similar to the camera track.ng in a closed environment,guaranteeing privacy and *** primary objective was to demonstrate the efficacy of the proposed technique through carefully designed experiments conducted using two *** Scenario I,the study illustrates the capability of the proposed technique to detect the locations of multiple objects positioned on a flat surface,achieved by analyzing LiDAR data collected from several locations within the closed *** II demonstrates the effectiveness of the proposed technique in detecting multiple objects using LiDAR data obtained from a single,fixed ***-time experiments are conducted with human subjects navigating predefined *** individuals move within an environment,while LiDAR,fixed at the center,dynamically track. and identifies their locations at multiple *** demonstrate that a single,strategically positioned LiDAR can adeptly detect objects in motion around ***,this study provides a comparison of various regression techniques for predicting bounding box *** process regression(GpR),combined with particle swarm optimization(pSO)for prediction,achieves the lowest prediction mean square error of all the regression techniques examined at *** tuning of GpR using pSO significantly minimizes the regression *** of the experiment pave the way for its extension to various real-time applications such as crowd management in malls,surveillance systems,and various Internet of Things scenarios.

关键词： LiDAR Data acquisition Bounding box Gaussian process regression particle swarm optimization(pSO)

A new route to weak.force sensing beyond SQL: Squeezed magnons in cavity magnomechanics

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Science China(physics,Mechanics & Astronomy) 2024年第10期Mechanics & Astronomy) .卷 170-171页

作者： ?.k.?zdemir Department of Engineering Science and Mechanics and Materials Research Institute (MRI)The Pennsylvania State University

Quantum mechanics imposes limits on measurement accuracy through quantum noise which typically has two components: First is the shot noise originating from vacuum fluctuations and referred to as the imprecision noise. Second is the quantum back.ction originating from the “action” of the measurement back.on the object being measured.

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Modal Frequency prediction of Chladni patterns Using Machine Learning

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Open Journal of Acoustics 2024年第1期12卷 1-16页

作者： Atul k.mar k. p. Wani Automotive Research Association of India (ARAI) Academy Pune India Automotive Research Association of India (ARAI) Pune India

The introduction of machine learning (ML) in the research domain is a new era technique. The machine learning algorithm is developed for frequency predication of patterns that are formed on the Chladni plate and focused on the application of machine learning algorithms in image processing. In the Chladni plate, nodes and antinodes are demonstrated at various excited frequencies. Sand on the plate creates specific patterns when it is excited by vibrations from a mechanical oscillator. In the experimental setup, a rectangular aluminum plate of 16 cm x 16 cm and 0.61 mm thick.ess was placed over the mechanical oscillator, which was driven by a sine wave signal generator. 14 Chladni patterns are obtained on a Chladni plate and validation is done with modal analysis in Ansys. For machine learning, a large number of data sets are required, as captured around 200 photos of each modal frequency and around 3000 photos with a camera of all 14 Chladni patterns for supervised learning. The current model is written in python language and model has one convolution layer. The main modules used in this are Tensor Flow k.ras, Numpy, CV2 and Maxpooling. The fed reference data is tak.n for 14 frequencies between 330 Hz to 3910 Hz. In the model, all the images are converted to grayscale and canny edge detected. All patterns of frequencies have an almost 80% - 99% correlation with test sample experimental data. This approach is to form a directory of Chladni patterns for future reference purpose in real-life application. A machine learning algorithm can predict the resonant frequency based on the patterns formed on the Chladni plate.

关键词： Chaldni pattern Modal Analysis Machine Learning Resonant Frequency Image processing

Dynamical system analysis of Dirac-Born-Infeld scalar field cosmology in coincident f(Q) gravity

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Chinese physics C 2024年第9期48卷 203-213页

作者： Sayantan Ghosh Raja Solank. p.k.Sahoo Department of Mathematics Birla Institute of Technology and Science-PilaniHyderabad Campus

In this article,we present a dynamical system analysis of a Dirac-Born-Infeld scalar field in a modified f(Q) gravity *** considered a polynomial form of modified gravity,used two different types of scalar potential,polynomial and exponential,and found a closed autonomous dynamical system of *** analyzed the fixed points of such a system and evaluated the conditions under which deceleration to late-time acceleration occurs in this *** note the similarity of the two models and show that our result is consistent with a previous study on Einstein s *** also investigated the phenomenological implications of our models by plotting EoS(ω),energy density(Ω),and deceleration parameter(q) *** e-fold time and comparing to the present *** conclude the paper by observing how the dynamical system analysis differs in the modified f(Q) gravity,and present the future scope of our research.

关键词： dark.energy Dirac-Born-Infeld field dynamical system analysis f(Q) gravity

Sparse identification-assisted exploration of the atomic-scale deformation mechanism in multiphase CoCrFeNi high-entropy alloys

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Science China(Technological Sciences) 2024年第4期67卷 1124-1132页

作者： XIAO Lu GUO XiaoXiang SUN YuTong WANG Gang LONG WeiMin LIAW peter k. REN JingLi School of Mathematics and Statistics Zhengzhou UniversityZhengzhou 450001China Academy of Mathematics and Systems Science Chinese Academy of SciencesBeijing 100190China Institute of Materials Shanghai UniversityShanghai 200444China Sk. of Advanced Brazing Metals&Technology Zhengzhou Research Institute of Mechanical EngineeringZhengzhou 450001China Department of Materials Science and Engineering The University of TennesseeKnoxvilleTN 37996USA

This study investigated the atomic-scale deformation mechanism of multiphase CoCrFeNi high-entropy alloys(HEAs)at liquid helium,liquid nitrogen,and room temperatures.A million-atom multiphase HEA was prepared using molecular dynamics simulation involving melt and quench *** HEA exhibited high-density dislocations and some twins,consistent with experimental *** analysis revealed an inconsistent evolution of the microstructure under tensile *** particular,the elastic and initial plastic stages exhibited an increase in the disordered structure at the expense of the face-centered cubic and hexagonal close-pack.d structures,followed by a subsequent transformation involving multiple structural ***,through sparse identification,a model depicting microstructural evolution during tension was extracted for the CoCrFeNi HEA at three typical temperatures and three tensile *** model highlighted the importance of the body-centered cubic structure in the evolutionary process.

关键词： high-entropy alloy data-driven method microstructure evolution multiphase structure molecular dynamics simulation

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