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Journal of Physics: Conference Series 2021年第1期1973卷

作者： Brijeshkumar Y. Panchal Gaurang Chauhan Teaching Cum Research assistant Department of Computer Science and Engineering DEPSTAR CHARUSAT Charotar University of Science and Technology (CHARUSAT) CHARUSAT campus Changa 388421 India ITsouls Vadodara

The proposed Implementation is on the Android Application to extract using Tesseract OCR in which the following concepts will be used, which are Adaptive Thresholding, Connected Component, Fine Lines, and Recognize Word. Using this Optical Character Recognition (OCR) Technology, an Application generated text which is printed on a clean, B/W or colourful background can be converted into a computer readable form ASCII. With the help of this Android Application using Tesseract OCR, the system has two ways for Text Extraction. The first one is to capture a photo while the second one uploads an image from the gallery after that system can proceed for as per the user requirement which portion of the image they want to crop or edit. After editing the picture, it converts into the text. This Android Application is for two languages, English and Hindi.

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Effective removal of auramine O and safranin O from aqueous solutions using nickel copper ferrite magnetic nanoparticles

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Journal of Molecular Structure 2025年 1344卷

作者： Irfan Ahmad Dilshad Alhedrawie Vicky Jain Abhinav Kumar M.M Rekha Mayank Kundlas S. Sunitha Subhashree Ray Shirin Shomurotova Department of Clinical Laboratory Sciences College of Applied Medical Sciences King Khalid University Abha Saudi Arabia Department of Computer Techniques Engineering College of Technical Engineering The Islamic University Najaf Iraq Department of Computer Techniques Engineering College of Technical Engineering The Islamic University of Al Diwaniyah Al Diwaniyah Iraq Department of Computer Techniques Engineering College of Technical Engineering The Islamic University of Babylon Babylon Iraq Marwadi University Research Center Department of Chemistry Faculty of Science Marwadi University Rajkot 360003 Gujarat India Department of Nuclear and Renewable Energy Ural Federal University Named after the First President of Russia Boris Yeltsin Ekaterinburg 620002 Russia Department of Mechanical Engineering Karpagam Academy of Higher Education Coimbatore 641021 India Department of Chemistry and Biochemistry School of Sciences Jain (Deemed to be University) Bangalore Karnataka India Centre for Research Impact and Outcome Chitkara University Institute of Engineering and Technology Chitkara University Rajpura 140401 Punjab India Department of Chemistry Sathyabama Institute of Science and Technology Chennai Tamil Nadu India Department of Biochemistry IMS and SUM Hospital Siksha 'O' Anusandhan (Deemed to be University) Bhubaneswar Odisha 751003 India Department of Chemistry Teaching Methods Tashkent State Pedagogical University named after Nizami Bunyodkor street 27 Tashkent Uzbekistan

Water contamination by industrial dyes has become one of the major environmental challenges in recent decades. In this study, the adsorption of auramine O (Au-O) and safranin O (Sa-O) from aqueous solutions using nickel copper ferrite magnetic nanoparticles (NiCuFe 2 O 4 NPs) were investigated. These nanoparticles were synthesized via the sol-gel method and characterized using Fourier transform infrared spectroscopy (FTIR), vibrating sample magnetometry (VSM), X-ray diffraction (XRD), energy-dispersive X-ray spectroscopy (EDX), point of zero charge (pH pzc ), and scanning electron microscopy (SEM) techniques. Key operational parameters, including pH, ultrasonic duration, adsorbent dosage, and analyte concentration, were optimized using response surface methodology (RSM) based on the Box-Behnken design. A second-order polynomial model was selected for prediction and validated through analysis of variance (ANOVA). The optimal conditions for adsorption were determined to be pH of 7, NiCuFe 2 O 4 dosage of 0.021 g, analyte concentration of 32 mg L −1 , and an ultrasound duration of 11 min. Under these conditions, the maximum removal efficiency for Au-O and Sa-O was 98.24 % and 95.77 %, respectively. The reusability tests indicated that NiCuFe 2 O 4 NPs retained their adsorption performance over four consecutive cycles without significant efficiency loss. Moreover, the adsorbent demonstrated high efficiency in treating real water samples, with removal percentages ranging from 87.35 % to 98.06 %. Therefore, NiCuFe 2 O 4 NPs can be considered a promising, cost-effective, stable, and reusable adsorbent for the treatment of industrial effluents and contaminated water resources.

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Effects of the Cattaneo–Christov flux model on thermally radiative flow of tetra hybrid nanofluid with surface tension gradient

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Case Studies in Thermal Engineering 2025年 72卷

作者： Mostafa Mohamed Okasha Munawar Abbas Faiza Benabdallah Talib K. Ibrahim Tatyana Orlova Ali Akgül Murad Khan Hassani Abdullah A. Faqihi Hakim AL. Garalleh Ahmed M. Galal Department of Mechanical Engineering College of Engineering Northern Border University Arar Saudi Arabia Department of Mathematics Saveetha School of Engineering Saveetha Institute of Medical and Technical Sciences Saveetha University Chennai 602105 Tamil Nadu India Department of Mathematics The Islamia University of Bahawalpur Bahawalpur 63100 Pakistan Department of Industrial and Systems Engineering College of Engineering Princess Nourah bint Abdulrahman University P.O. Box 84428 Riyadh 11671 Saudi Arabia Department of Petroleum Engineering College of Engineering Knowledge University Erbil 44001 Iraq Department of Petroleum Engineering Al-Kitab University Altun Kupri Iraq Department of Physics and Its Teaching Methods Tashkent State Pedagogical University Tashkent Uzbekistan Siirt University Art and Science Faculty Department of Mathematics 56100 Siirt Turkey Department of Computer Engineering Biruni University Topkapı 34010 Istanbul Turkey Near East University Mathematics Research Center Department of Mathematics Near East Boulevard PC: 99138 Mersin 10 Nicosia Turkey Applied Science Research Center Applied Science Private University Amman Jordan Ghazni University Department of Mathematics Afghanistan Department of Industrial Engineering College of Engineering and Computer Science Jazan University P. O. Box 706 Jazan 45142 Saudi Arabia Department of Mathematical Science College of Engineering University of Business and Technology Jeddah 21361 Saudi Arabia Department of Mechanical Engineering College of Engineering in Wadi Alddawasir Prince Sattam Bin Abdulaziz University Saudi Arabia Production Engineering and Mechanical Design Department Faculty of Engineering Mansoura University P.O 35516 Mansoura Egypt

The importance of thermal radiation and Stefan blowing on the boundary layer flow of tetra hybrid nanofluid flow across a disk are examined in the present work employing the Cattaneo-Christov flux model. Additionally, the Marangoni convection effect and Stefan blowing are examined. Tetra-hybrid nanofluids are employed in sophisticated thermal systems like heat exchangers, solar energy systems, and cooling technologies because of their improved thermal conductivity and heat transmission properties. Under microgravity conditions, a surface tension differential in the plasma causes the intriguing scientific phenomenon known as Marangoni convection. Important uses of the Marangoni effect include welding, convection or Bernard cells, crystal growth, electron beam melting of metals, soap film stability, and more. In order to improve heat exchangers in chemical processes, optimize thermal management in power plants, and provide effective cooling systems for intricate machinery, the model is essential. Furthermore, it is a flexible tool for contemporary engineering solutions that advance sustainable practices by improving the energy efficiency of renewable technologies. To solve the problem, the Homotopy analysis approach is applied, and graphs are used to show the analytical outcomes. The temperature and velocity fields rise as the Stefan blowing parameter rises, while the solutal profile falls.

关键词： Thermal radiation Cattaneo-Christov model Tetra hybrid nanofluid Stefan blowing Heat generation

Artificial intelligence in multimodal learning analytics: A systematic literature review

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computers and Education: Artificial Intelligence 2025年 8卷

作者： Mohammadi, Mehrnoush Tajik, Elham Martinez-Maldonado, Roberto Sadiq, Shazia Tomaszewski, Wojtek Khosravi, Hassan School of Electrical Engineering and Computer Science The University of Queensland Brisbane Australia Department of Educational Psychology and Learning Systems Florida State University Tallahassee United States Centre for Learning Analytics at Monash Faculty of Information Technology Monash University Melbourne Australia Australian Research Council Centre of Excellence for Children and Families Over the Life Course The University of Queensland Brisbane Australia Institute for Social Science Research The University of Queensland Brisbane Australia Institute for Teaching and Learning Innovation The University of Queensland Brisbane Australia

The proliferation of educational technologies has generated unprecedented volumes of diverse, multimodal learner data, offering rich insights into learning processes and outcomes. However, leveraging this complex, multimodal data requires advanced analytical methods. While Multimodal Learning Analytics (MMLA) offers promise for exploring this data, the potential of Artificial Intelligence (AI) to enhance MMLA remains largely unexplored. This paper bridges these two evolving domains by conducting the first systematic literature review at the intersection of AI and MMLA, analyzing 43 peer-reviewed papers from 11 reputable databases published between 2019 and 2024. The findings indicate a growing trend in AI-enhanced MMLA studies published predominantly in high-quality venues, led by education researchers with a predominant focus on tertiary education targeting diverse stakeholders. Guided by a novel conceptual framework, our analysis highlights the transformative role of AI across the MMLA process, particularly in model learning and feature engineering. However, it also uncovers significant gaps, including limited AI implementation in components requiring deep integration with learning theories, insufficient application of advanced AI techniques, and lack of large-scale studies in authentic learning environments. The review identifies key benefits, such as enhanced personalization and real-time feedback, while also addressing challenges related to ethical considerations, data integration, and scalability. Our study contributes by offering comprehensive recommendations for future research, emphasizing international collaboration, multi-level studies, and ethical AI implementation. These findings advance the theoretical understanding of AI's role in education, providing a foundation for developing sophisticated, interpretable, and scalable AI-enhanced MMLA approaches, potentially revolutionizing personalized learning across diverse educational settings. © 2025

关键词： Educational robots

An approach for realistically simulating the performance of scientific applications on high performance computing systems

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arXiv 2019年

作者： Mohammed, Ali Eleliemy, Ahmed Ciorba, Florina M. Kasielke, Franziska Banicescu, Ioana Department of Mathematics and Computer Science University of Basel Switzerland Institute of Software Methods for Product Virtualization German Aerospace Center Germany Department of Computer Science and Engineering Mississippi State University United States

Scientific applications often contain large, computationally-intensive, and irregular parallel loops or tasks that exhibit stochastic characteristics. Applications may suffer from load imbalance during their execution on high-performance computing (HPC) systems due to such characteristics. Dynamic loop self-scheduling (DLS) techniques are instrumental in improving the performance of scientific applications on HPC systems via load balancing. Selecting a DLS technique that results in the best performance for different problems and system sizes requires a large number of exploratory experiments. A theoretical model that can be used to predict the scheduling technique that yields the best performance for a given problem and system has not yet been identified. Therefore, simulation is the most appropriate approach for conducting such exploratory experiments with reasonable costs. This work devises an approach to realistically simulate computationally-intensive scientific applications that employ DLS and execute on HPC systems. Several approaches to represent the application tasks (or loop iterations) are compared to establish their influence on the simulative application performance. A novel simulation strategy is introduced, which transforms a native application code into a simulative code. The native and simulative performance of two computationally-intensive scientific applications are compared to evaluate the realism of the proposed simulation approach. The comparison of the performance characteristics extracted from the native and simulative performance shows that the proposed simulation approach fully captured most of the performance characteristics of interest. This work shows and establishes the importance of simulations that realistically predict the performance of DLS techniques for different applications and system configurations. Copyright © 2019, The Authors. All rights reserved.

关键词： Benchmarking

Realistic Kilonova Up Close

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arXiv 2022年

作者： Stewart, Alexandra Ruth Lo, Li-Ta Korobkin, Oleg Sagert, Irina Loiseau, Julien Lim, Hyun Kaltenborn, Mark Alexander Mauney, Christopher Michael Miller, Jonah Maxwell CCS-2 Computational Physics and Methods Los Alamos National Laboratories Los AlamosNM87545 United States CCS-3 Information Sciences Los Alamos National Laboratories Los AlamosNM87545 United States CCS-7 Applied Computer Science Los Alamos National Laboratories Los AlamosNM87545 United States HPC Environments Los Alamos National Laboratories Los AlamosNM87545 United States Department of Physics Massachusetts Institute of Technology CambridgeMA02139 United States Department of Physics The George Washington University WashingtonDC20052 United States

Neutron star mergers are cosmic catastrophes that produce some of the most energetic observed phenomena: short gamma-ray bursts, gravitational wave signals, and kilonovae. The latter are optical transients, powered by radioactive nuclides which are synthesized when the neutron-rich ejecta of a disrupted neutron star undergoes decompression. We model this decompression phase using data from simulations of post-merger accretion disk winds. We use smoothed particle hydrodynamics with realistic nuclear heating to model the expansion over multiple scales, from initially several thousand km to billions of km. We then render a realistic image of a kilonova ejecta as it would appear for a nearby observer. This is the first time such a visualization is performed using input from state-of-the-art accretion disk simulations, nuclear physics and atomic physics. The volume rendering in our model computes an opacity transfer function on the basis of the physical opacity, varying significantly with the inhomogeneity of the neutron richness in the ejecta. Other physical quantities such as temperature or electron fraction can be visualized using an independent color transfer function. We discuss several difficulties with the ParaView application that we encountered during the visualization process, and give descriptions of our solutions and workarounds which could be used for future improvements. © 2022, CC BY.

关键词： Merging

CXR-Net: An Encoder-Decoder-Encoder Multitask Deep Neural Network for Explainable and Accurate Diagnosis of COVID-19 pneumonia with Chest X-ray Images

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arXiv 2021年

作者： Zhang, Xin Han, Liangxiu Sobeih, Tam Han, Lianghao Dempsey, Nina Lechareas, Symeon Tridente, Ascanio Chen, Haoming White, Stephen The Department of Computing and Mathematics Manchester Metropolitan University ManchesterM15GD United Kingdom The Department of Computer Science Brunel University UxbridgeUB8 3PH United Kingdom The Department of Life Sciences Manchester Metropolitan University ManchesterM15GD United Kingdom The Radiology Whiston Hospital St Helens and Knowsley Teaching Hospitals NHS Trust Warrington Road PrescotL355DR United Kingdom The Intensive Care Unit Whiston Hospital St Helens and Knowsley Teaching Hospitals NHS Trust Warrington Road PrescotL355DR United Kingdom The Computer Science and Artificial Intelligence University of Sheffield SheffieldS14DP United Kingdom The Cardiovascular Pathology Manchester Metropolitan University ManchesterM15GD United Kingdom

Accurate and rapid detection of COVID-19 pneumonia is crucial for optimal patient treatment. Chest X-Ray (CXR) is the first line imaging test for COVID-19 pneumonia diagnosis as it is fast, cheap and easily accessible. Inspired by the success of deep learning (DL) in computer vision, many DL-models have been proposed to detect COVID-19 pneumonia using CXR images. Unfortunately, these deep classifiers lack the transparency in interpreting findings, which may limit their applications in clinical practice. The existing commonly used visual explanation methods are either too noisy or imprecise, with low resolution, and hence are unsuitable for diagnostic purposes. In this work, we propose a novel explainable deep learning framework (CXRNet) for accurate COVID-19 pneumonia detection with an enhanced pixel-level visual explanation from CXR images. The proposed framework is based on a new Encoder-Decoder-Encoder multitask architecture, allowing for both disease classification and visual explanation. The method has been evaluated on real world CXR datasets from both public and private data sources, including: healthy, bacterial pneumonia, viral pneumonia and COVID-19 pneumonia cases The experimental results demonstrate that the proposed method can achieve a satisfactory level of accuracy and provide fine-resolution classification activation maps for visual explanation in lung disease detection. The Average Accuracy, the Precision, Recall and F1-score of COVID-19 pneumonia reached 0.879, 0.985, 0.992 and 0.989, respectively. We have also found that using lung segmented (CXR) images can help improve the performance of the model. The proposed method can provide more detailed high resolution visual explanation for the classification decision, compared to current state-of-the-art visual explanation methods and has a great potential to be used in clinical practice for COVID-19 pneumonia diagnosis. © 2021, CC BY.

关键词： Patient treatment

Reweighting of binaural localization cues induced by lateralization training

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arXiv 2020年

作者： Klingel, Maike Kopčo, Norbert Laback, Bernhard Acoustics Research Institute Austrian Academy of Sciences Vienna1040 Austria Department of Cognition Emotion and Methods in Psychology Faculty of Psychology University of Vienna Vienna1010 Austria Institute of Computer Science Faculty of Science P. J. Šafárik University in Košice Košice04180 Slovakia

Normal-hearing listeners adapt to alterations in sound localization cues. This adaptation can result from the establishment of a new spatial map of the altered cues or from a stronger relative weighting of unaltered compared to altered cues. Such reweighting has been shown for monaural vs. binaural cues. However, studies attempting to reweight the two binaural cues, interaural differences in time and level, yielded inconclusive results. In this study we investigated whether binaural cue reweighting can be induced by a lateralization training in a virtual audio-visual environment. 20 normal-hearing participants, divided into two groups, completed the experiment consisting of a seven-day lateralization training in a virtual audio-visual environment, preceded and followed by a test measuring the binaural cue weights. During testing, the participants’ task was to lateralize 500-ms bandpass-filtered (2-4 kHz) noise bursts containing various combinations of spatially consistent and inconsistent ITDs and ILDs. During training, the task was extended by visual cues reinforcing ITDs in one group and ILDs in the other group as well as manipulating the azimuthal ranges of the two cues. In both groups, the weight given to the reinforced cue increased significantly from pre- to posttest, suggesting that participants reweighted the binaural cues in the expected direction. This reweighting occurred predominantly within the first training session. The present results are relevant as binaural cue reweighting is, for example, likely to occur when normal-hearing listeners adapt to new acoustic environments. Similarly, binaural cue reweighting might be a factor underlying the low contribution of ITDs to sound localization of cochlear-implant listeners as they typically do not experience reliable ITD cues with their clinical devices. Copyright © 2020, The Authors. All rights reserved.

关键词： Audition

An Analysis by Synthesis Approach for Automatic Vertebral Shape Identification in Clinical QCT 40th

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An Analysis by Synthesis Approach for Automatic Vertebral Sh...

40th German Conference on Pattern Recognition, GCPR 2018

作者： Reinhold, Stefan Damm, Timo Huber, Lukas Andresen, Reimer Barkmann, Reinhard Glüer, Claus-C. Koch, Reinhard Department of Computer Science Kiel University Kiel Germany Kiel University Kiel Germany Institute of Diagnostic and Interventional Radiology/Neuroradiology Westküstenklinikum Heide Academic Teaching Hospital of the Universities of Kiel Lübeck and Hamburg Heide Germany

ISBN: (纸本)9783030129385

Quantitative computed tomography (QCT) is a widely used tool for osteoporosis diagnosis and monitoring. The assessment of cortical markers like cortical bone mineral density (BMD) and thickness is a demanding task, mainly because of the limited spatial resolution of QCT. We propose a direct model based method to automatically identify the surface through the center of the cortex of human vertebra. We develop a statistical bone model and analyze its probability distribution after the imaging process. Using an as-rigid-as-possible deformation we find the cortical surface that maximizes the likelihood of our model given the input volume. Using the European Spine Phantom (ESP) and a high resolution µCT scan of a cadaveric vertebra, we show that the proposed method is able to accurately identify the real center of cortex ex-vivo. To demonstrate the in-vivo applicability of our method we use manually obtained surfaces for comparison. © 2019, Springer Nature Switzerland AG.

关键词： Probability distributions

Crucial inflammatory mediators and efficacy of drug interventions in pneumonia inflated COVID-19: An invivo mathematical modelling study

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arXiv 2020年

作者： Chhetri, Bishal Vamsi, D.K.K. Bhagat, Vijay M. Ananth, V.S. Prakash, Bhanu Mandale, Roshan Muthusamy, Swapna Department of Mathematics and Computer Science Sri Sathya Sai Institute of Higher Learning - SSSIHL India Central Leprosy Teaching and Research Institute - CLTRI Chennai India Sri Sathya Sai Higher Secondary School - SSSHSS Puttaparthi India

The virus SARS-COV-2 caused disease COVID-19 has been declared a pandemic by WHO. Currently, over 210 countries and territories have been affected. Careful, well-designed drugs and vaccine for the total elimination of this virus seem to be the need of the hour. In this context, the invivo mathematical modelling studies can be extremely helpful in understanding the efficacy of the drug interventions. These studies can also help understand the role of the crucial inflammatory mediators and the behaviour of immune response towards this novel coronavirus. Motivated by these facts, in this paper, we study the invivo dynamics of Covid-19. We initially model and study the natural history, the course of the infection and its dynamics. We then validate the model by generating two-parameter heat plots that represent the characteristics of Covid-19. We also do the sensitivity analysis to identify the sensitive parameters of the system. Lastly, we study the efficacy of drug interventions for Covid-19 by formulating an Optimal Control Problem. The outcomes of these studies are multi-fold. The system admits two steady states: the disease-free equilibrium and the infected equilibrium. The dynamics of the system show that the disease takes its course to one of these steady states based on the reproduction number R0. The system undergoes a transcritical bifurcation at R0 = 1. From the sensitivity analysis, it is seen that the burst rate of the virus particles and the natural death rate of the virus are the sensitive parameters of the system. Results from the optimal control studies suggest that the antiviral drugs that target viral replication and the drugs that enhance the immune system response both reduce the infected cells and viral load when taken individually. However, it is observed that these drugs yield the best possible results when administered together. Hence, it is concluded that the optimal control strategy would be to use the combination of both these drugs which not

关键词： Optimal control systems