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arXiv 2024年

作者： Jin, Qiangguo Huang, Jiapeng Sun, Changming Cui, Hui Xuan, Ping Su, Ran Wei, Leyi Wu, Yu-Jie Wu, Chia-An Duh, Henry B.L. Lu, Yueh-Hsun School of Software Northwestern Polytechnical University Shaanxi China Yangtze River Delta Research Institute of NPU Suzhou China CSIRO Data61 Sydney Australia Department of Computer Science and Information Technology La Trobe University Melbourne Australia School of Engineering Shantou University Guangdong China College of Intelligence and Computing Tianjin University Tianjin China School of Information Xiamen University Xiamen China AIDD Faculty of Applied Science Macao Polytechnic University China Department of Radiology Shuang-Ho Hospital Taipei Medical University Taipei Taiwan Master of Public Health Program National Yang Ming Chiao Tung University Taipei Taiwan School of Design The Hong Kong Polytechnic University Hong Kong Department of Radiology School of Medicine College of Medicine Taipei Medical University Taipei Taiwan

The precise diagnosis of urinary stones is crucial for devising effective treatment strategies. The diagnostic process, however, is often complicated by the low contrast between stones and surrounding tissues, as well as the variability in stone locations across different patients. To address this issue, we propose a novel location embedding based pairwise distance learning network (LEPD-Net) that leverages low-dose abdominal X-ray imaging combined with location information for the fine-grained diagnosis of urinary stones. LEPD-Net enhances the representation of stone-related features through context-aware region enhancement, incorporates critical location knowledge via stone location embedding, and achieves recognition of fine-grained objects with our innovative fine-grained pairwise distance learning. Additionally, we have established an in-house dataset on urinary tract stones to demonstrate the effectiveness of our proposed approach. Comprehensive experiments conducted on this dataset reveal that our framework significantly surpasses existing state-of-the-art methods. Copyright © 2024, The Authors. All rights reserved.

关键词： Embeddings

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Machine Learning Approach for Identifying Anatomical Biomarkers of Early Mild Cognitive Impairment

arXiv

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arXiv 2024年

作者： Ahmad, Alwani Liyana Sanchez-Bornot, Jose Sotero, Roberto C. Coyle, Damien Idris, Zamzuri Faye, Ibrahima Department of Fundamental and Applied Sciences Faculty of Science and Information Technology Universiti Teknologi PETRONAS Perak Malaysia Department of Neurosciences Hospital Universiti Sains Malaysia Kelantan Malaysia Brain and Behaviour Cluster School of Medical Sciences Universiti Sains Malaysia Kelantan Malaysia Intelligent Systems Research Centre School of Computing Engineering and Intelligent Systems Ulster University Magee campus Derry LondonderryBT48 7JL United Kingdom Department of Radiology Hotchkiss Brain Institute University of Calgary CalgaryAB Canada The Bath Institute for the Augmented Human University of Bath BathBA2 7AY United Kingdom Department of Neurosciences School of Medical Sciences Universiti Sains Malaysia Kelantan Malaysia Universiti Teknologi PETRONAS Perak Malaysia Universiti Teknologi PETRONAS Perak32610 Malaysia

Background. Alzheimer's Disease (AD) represents a significant challenge in neurodegenerative disorders, necessitating early detection for effective intervention. Among neuroimaging methods, magnetic resonance imaging (MRI) is widely used because it is easy to apply in clinical practice and cost-effective, making it crucial for studying AD. Objective. This study aims to perform a comprehensive analysis of machine learning (ML) methods used in MRI-based biomarker selection and classification analysis. The goal is to study AD-related early cognitive decline by discriminating between healthy control (HC) participants who stayed stable and those unstable (uHC) who developed mild cognitive impairment (MCI) within five years. Methods. We utilized 3-Tesla (3T) MRI data from the Alzheimer's Disease Neuroinformatic Initiative (ADNI) and the Open Access Series of Imaging Studies 3 (OASIS-3), focusing on HC and uHC. Freesurfer’s recon-all, among other tools, was used to extract MRI-based anatomical biomarkers corresponding to semi-automatic segmented subcortical and cortical brain regions. We applied various ML techniques to select features and classify the data. These included methods from preliminary analysis performed in the MATLAB Classification Learner (MCL) app and more sophisticated methods like nested cross-validation and Bayesian optimization implemented in a customized pipeline to enhance classification performance for balanced and imbalanced datasets. Our pipeline was applied to both original imbalanced and randomly balanced datasets within a Monte Carlo analysis. Moreover, we implemented data harmonization approaches based on polynomial regression that enhanced the performance of ML and statistical methods. Complementary performance metrics, such as Accuracy (Acc), area under receiver operating characteristic curve (AROC), F1 score, and Matthew’s correlation coefficient (MCC), were used to evaluate the assessed methodologies. Results. In feature selection analyses,

关键词： Neurodegenerative diseases

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Preface

SpringerBriefs in Applied Sciences and Technology

引用

SpringerBriefs in applied Sciences and technology 2023年 V页

作者： Ismail, Azman Zulkipli, Fatin Nur Long, Zalizah Awang Öchsner, Andreas Centre for Women Advancement and Leadership Malaysian Institute of Marine Engineering Technology Universiti Kuala Lumpur Perak Lumut Malaysia School of Information Science College of Computing Informatics and Media Universiti Teknologi MARA Machang Malaysia Malaysian Institute of Information Technology Universiti Kuala Lumpur Kuala Lumpur Malaysia Faculty of Mechanical Engineering Esslingen University of Applied Sciences Esslingen Germany

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Multi‑lingual character handwriting framework based on an integrated deep learning based sequence‑to‑sequence attention model

TechRxiv

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TechRxiv 2021年

作者： Rabhi, Besma Elbaati, Abdelkarim Boubaker, Houcine Hamdi, Yahia Hussain, Amir Alimi, Adel M. BP 1173 Sfax3038 Tunisia Higher Institute of Applied Sciences and Technology of Mahdia REGIM-Laboratory: Research Groups in Intelligent Machines LR11ES48 University of Monastir Mahdia5121 Tunisia School of Computing Edinburgh Napier University Edinburgh United Kingdom Department of Electrical and Electronic Engineering Science Faculty of Engineering and the Built Environment University of Johannesburg Johannesburg South Africa

Online signals are rich in dynamic features such as trajectory chronology, velocity, pressure and pen up/down movements. Their offline counterparts consist of a set of pixels. Thus, online handwriting recognition accuracy is generally better than offline. In this paper, we propose an original framework for recovering temporal order and pen velocity from offline multilingual handwriting. Our framework is based on an integrated sequence-to-sequence attention model. The proposed system involves extracting a hidden representation from an image using a convolutional neural network (CNN) and a bidirectional gated recurrent unit (BGRU), and decoding the encoded vectors to generate dynamic information using a BGRU with temporal attention. We validate our framework using an online recognition system applied to a benchmark Latin, Arabic and Indian On/Off dual-handwriting character database. The performance of the proposed multi-lingual system is demonstrated through a low error rate of point coordinates and high accuracy system rate. © 2021, CC BY.

关键词： Convolutional neural networks

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Effect of channel thickness on the particle diffusion and permeability of carbon nanotubes a membrane in reverse electrodialysis process using molecular dynamics simulation

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International Communications in Heat and Mass Transfer 2025年 166卷

作者： Shuai Sun Ali Basem Narinderjit Singh Sawaran Singh Younis Mohamed Atiah Al-zahy Salman Saeidlou Khursheed Muzammil Soheil Salahshour S. Mohammad Sajadi Hani Sahramaneshi School of Energy and Constructional Engineering Shandong Huayu University of Technology Dezhou Shandong 253034 China Faculty of Engineering DongShin University Naju-si Jeollanam-do 58245 South Korea Faculty of Engineering Warith Al-Anbiyaa University Karbala 56001 Iraq Faculty of Data Science and Information Technology INTI International University Persiaran Perdana BBN Putra Nilai Nilai 71800 Malaysia Department of Physics College of Education Misan University Maysan Iraq School of Engineering Technology and Design Canterbury Christ Church University Kent UK Department of Public Health College of Applied Medical Sciences Khamis Mushait Campus King Khalid University Abha 62561 Saudi Arabia Faculty of Engineering and Natural Sciences Istanbul Okan University Istanbul Turkey Faculty of Engineering and Natural Sciences Bahcesehir University Istanbul Turkey Research Center of Applied Mathematics Khazar University Baku Azerbaijan Department of Chemistry Payam e Noor University Saqqez Branch Saqqez Kurdistan Iran Fast Computing Center Shabihsazan Ati Pars Tehran Iran

Adopting innovative technology and solutions is critical for ensuring clean water. Several methods may be used to remove salts from water. They may be divided into two categories: membranes and heat. Reverse electrodialysis, which uses a membrane, is an efficient way of separating substances. Prior research investigated system-level factors, but the nanoscale mechanisms that drive ion and water penetration across membranes were poorly understood. This study closed a research gap by investigating the influence of carbon nanotube membrane thickness on particle mobility and fluid dynamics in reverse electrodialysis systems. The research is contributed to the enhancement of energy conversion efficiency and membrane performance in reverse electrodialysis systems by offering a comprehensive understanding of the influence of channel thickness on particle transport and selectivity through the carbon nanotube membrane. Molecular dynamics simulations using the LAMMPS software package are conducted to examine the effect of carbon nanotube thickness variation (1-layer vs 2-layer) on fluid flow, ionic current, hydrogen bonding, and fluid density. To the findings, increasing the thickness of a carbon nanotube from one layer to two layers decreases the fluid flow rate to 203.79 atoms/ns and the current from 5.31 e/ns to 5.15 e/ns. Additionally, the number of broken hydrogen bonds decreases from 116 to 105, indicating decreased permeability and increased stability of the hydrogen-bonding network. In addition to offering useful information for the construction of more effective and selective membranes in renewable energy applications, these results provided a molecular understanding of how carbon nanotube thickness affected reverse electrodialysis effectiveness.

关键词： Flow separation

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Terrain prickliness: theoretical grounds for high complexity viewsheds

arXiv

引用

arXiv 2021年

作者： Acharyya, Ankush Löffler, Maarten Meijer, Gert G.T. Saumell, Maria Silveira, Rodrigo I. Staals, Frank Department of Computer Science and Engineering National Institute of Technology Durgapur India Dept. of Information and Computing Sciences Utrecht University Netherlands Department of Computer Science Tulane University United States Academy of ICT and Creative Technologies NHL Stenden University of Applied Sciences Netherlands Dept. of Theoretical Computer Science Faculty of Information Technology Czech Technical University in Prague Czech Republic Dept. de Matemàtiques Universitat Politècnica de Catalunya Spain

MSC Codes 68U05An important task in terrain analysis is computing viewsheds. A viewshed is the union of all the parts of the terrain that are visible from a given viewpoint or set of viewpoints. The complexity of a viewshed can vary significantly depending on the terrain topography and the viewpoint position. In this work we study a new topographic attribute, the prickliness, that measures the number of local maxima in a terrain from all possible angles of view. We show that the prickliness effectively captures the potential of 2.5D TIN terrains to have high complexity viewsheds. We present optimal (for 1.5D terrains) and near-optimal (for 2.5D terrains) algorithms to compute it for TIN terrains, and efficient approximate algorithms for raster DEMs. We validate the usefulness of the prickliness attribute with experiments in a large set of real terrains. Copyright © 2021, The Authors. All rights reserved.

关键词： Topography

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Interaction of doxorubicin with carbon nanotubes in the capillaries surrounding cancer tumors using molecular dynamics simulation: The impact of pH on the thermal properties

引用

Results in Chemistry 2025年 16卷

作者： Ahmed Mohammed Attyah Zheoat Abeer Issa Mohammed Al Luaibi Raad Kareem Alwan Al Darraji Narinderjit Singh Sawaran Singh Soheil Salahshour S. Mohammad Sajadi M. Hekmatifar Al-Manara College for Medical Sciences Department of Pharmacy Maysan Iraq Faculty of Data Science and Information Technology INTI International University Persiaran Perdana BBN Putra Nilai Nilai 71800 Malaysia Faculty of Engineering and Natural Sciences Istanbul Okan University Istanbul Turkey Faculty of Engineering and Natural Sciences Bahcesehir University Istanbul Turkey Research Center of Applied Mathematics Khazar University Baku Azerbaijan Department of Chemistry Payam e Noor University Saqqez Branch Saqqez Kurdistan Iran. Fast Computing Center Shabihsazan Ati Pars Tehran Iran

Environmental factors, including pH, can affect the efficacy of doxorubicin, a chemotherapeutic drug that is frequently used. This study employs molecular dynamics modeling to investigate the correlation between doxorubicin and carbon nanotubes in the capillaries surrounding malignant tumors. After a period of 10 ns, the system reaches to equilibrium when the kinetic and potential energies are stabilized at 0.93 kcal/mol and 5.68 kcal/mol, respectively. The maximum density increases from 0.0033 to 0.0036 atm/Å 3 as the pH increased from 3 to 11. Conversely, the shear tension decreases from 3.25 to 3.11 Pa, and the maximum temperature decreases from 391.91 to 368.77 K. The enhancement in drug stability and minimal degradation under physiological conditions was demonstrated by the decrease in temperature and shear stress that occurred with an increase in pH. The root mean square deviation and mean squared displacement also suggested that structural stability was improved at higher pH levels. This work facilitated the development of pH-responsive drug delivery devices, which improved drug stability and facilitated the controlled release of pharmaceuticals at physiological pH. These results may have a direct impact on the development of more effective cancer medications, particularly in the form of pH-sensitive drug delivery systems. This study facilitated the development of personalized therapies that could improve the stability and controlled release of chemotherapeutic medications throughout the body by regulating the interactions between doxorubicin and carbon nanotubes, thereby paving the way for future clinical research. This method had the potential to enhance the precision of drug administration, mitigate adverse effects, and enhance therapeutic outcomes in the treatment of cancer.

关键词： Molecular dynamics simulation Drug doxorubicin Carbon nanotubes pH level Atomic behavior Physical behavior DOX Doxorubicin CNT Carbon nanotube MD Molecular Dynamics MSD Mean square displacement RMSD Root mean square displacement RDF Radial distribution function EAM Embedded Atom Method NPs Nanoparticles LJ Lennard-Jones LAMMPS large-scale atomic/molecular massively parallel simulation.

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Indigenous Big Data Implications in New Zealand

Indigenous Big Data Implications in New Zealand

引用

Australasian Telecommunication Networks and Applications Conference, ATNAC

作者： Marianne Cherrington David Airehrour Joan Lu Qiang Xu Steven Wade Ihaka Dunn School of Computing and Engineering University of Huddersfield Huddersfield United Kingdom School of Applied Business Unitec Institute of Technology Auckland New Zealand University of Huddersfield Huddersfield United Kingdom Faculty of Medicine University of Auckland Auckland New Zealand

ISBN: (数字)9781728188270

ISBN: (纸本)9781728188287

Our world is dynamic and digital. It is irrefutable; big data are reshaping commerce, healthcare and governmental decisions. Individuals forgo awareness or even desire to uncover or appreciate how big data are affecting our society. This raises distinct data issues of huge effect, especially for indigenous communities. The novel proposition of this research, is that by considering advances in big data optimisation and issues from an indigenous perspective, a broad appreciation of decision-making significances will result. The microcosm in Aotearoa, New Zealand is relatively simple. It permits both a clear and leading view, especially of complex indigenous effects, due to its foundations in Maoridom. As big data advancements impact the quality of life for us all, there is an enormous responsibility, opportunity and incentive to focus research and awareness into nascent data design fields. Through an indigenous lens, unique perspectives and insights are shaped and presented in this paper, implicating feature selection in high-dimensional data.

关键词： Big Data Artificial intelligence Business Market research Feature extraction Cultural differences Government

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Gain enhancement of rectangular dielectric resonator antenna using air gap

引用

AIP Conference Proceedings 2023年第1期2579卷

作者： Shanmuka Rooban Gunasekaran Thennarasan Sabapathy Muzammil Jusoh R. Badlishah Ahmad Mohamed Nasrun Osman Saidatul Norlyana Azemi Nur Farhan Kahar Wan Zuki Azman Wan Muhamad Saravanan Nathan Lurudusamy Advanced Communication Engineering (ACE) Centre of Excellence Universiti Malaysia Perlis (UniMAP) Perlis Malaysia Faculty of Electronic Engineering Technology Universiti Malaysia Perlis (UniMAP) Perlis Malaysia Centre of Excellence Advanced Computing (AdvComp) Universiti Malaysia Perlis Malaysia Faculty of Applied and Human Science Universiti Malaysia Perlis Arau 02600 Perlis Malaysia Universiti Malaya Lembah Pantai Kuala Lumpur Malaysia

This paper presents a gain enhanced rectangular dielectric resonator antenna (DRA) using air gap. The air gap placed under the dielectric resonator antenna and above the ground plane. A gain of 6.605 dBi obtained from the DRA with air gap while gain of 5.956 dBi is achieved by DRA without air gap. The size of the antenna is approximately 50 mm by 40 mm, thus it can be considered a compact design. This antenna designed using Rogers RO4003 substrate and the DRA material is Eccostock HIK. All the design and simulation results are conducted using CST Studio Suite 2019 software. Based on the result, it shows that the antenna operates with reflection coefficient of less than -10 dB at the desired operating frequency range, centered at 3.5 GHz. The inclusion of air gap proved that it can enhance the gain value of the DRA.

关键词：

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Impacts of oxytactic microorganisms and viscous dissipation in Carreau nanoliquid featuring ferromagnetic nanoparticles

引用

Partial Differential Equations in applied Mathematics 2025年 13卷

作者： Tabrez, Muhammad Hussain, I. Khan, W.A. Khan, S.U. Waqas, M. Rashid, Rzgar Farooq Anwar, M.I. Ammar, Mohamed Ben Zamri, Nurnadiah Abiyev, Ruzimurod Garalleh, Hakim AL Department of Mathematics Mohi-ud-Din Islamic University Nerian Sharif Azad Jammu and Kashmir 12010 Pakistan Department of Mathematics Namal University Mianwali 42250 Pakistan NUTECH School of Applied Sciences and Humanities National University of Technology Islamabad 44000 Pakistan Department of Computer Science and Mathematics Lebanese American University Beirut Lebanon Faculty of Informatics and Computing Universiti Sultan Zainal Abidin Besut Campus Terengganu Besut 22200 Malaysia Department of Medical Laboratory Science College of Science Knowledge University Erbil 44001 Iraq Department of Medical Laboratory Technique College of Medical Technology AL-Kitab University Kirkuk Iraq Department of Mathematics School of Sciences and Humanities Nazarbayev University Astana Kazakhstan Center for Scientific Research and Entrepreneurship Northern Border University Arar 73213 Saudi Arabia Department of Mathematics and its Teaching Methods in Primary Education Tashkent State Pedagogical University Tashkent Uzbekistan Department of Mathematical Science College of Engineering University of Business and Technology Jeddah 21361 Saudi Arabia

Owing to rapid progress in field of nanotechnology, various mathematical model has been proposed regarding the flow of nanofluids. Based on boosted thermal properties, multidisciplinary applications of such materials has been claimed in various engineering and industrial processes. In current work, a theoretical analysis is performed for bioconvective flow of Carreau fluid with applications of magnetic dipole. The significance of magnetic dipole are presented with interaction of ferrofluid. The applications of viscous dissipation have also been entertained. The flow is subject to applications of stretched surface. Similarity variables are used for making transformation to obtain set of nonlinear ODEs from set of PDEs. The numerical computation is also made by using of well-known numerical method termed as bvp4c. Influences of various non dimensional fluid parameters like Brownian motion, viscous dissipation, Curie temperature, Weissenberg number, motile difference parameter and bioconvection Paclet number are examined and expressed graphically. It is perceived that ferrofluid's concentration declines when Brownian diffusive variable is augmented while opposite characteristics are reported for Schmidt number. Current results conveying applications in the biofuels, better heat transport medium, fertilizers, catalysts, electronics, paints, semiconductors, speakers, drug delivery, fertilizers etc. © 2024 The Author(s)

关键词： Bioconvection Carreau fluid Ferromagnetic flow Magnetic dipole Viscous dissipation

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