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Discrete null field equation methods for solving Laplace's equation: Boundary layer computations

Numerical Methods for Partial Differential Equations 2024年第4期40卷 e23092-e23092页

作者： Zhang, Li-Ping Li, Zi-Cai Lee, Ming-Gong Huang, Hung-Tsai School of Mathematical Sciences Qufu Normal University Shandong Qufu China Department of Applied Mathematics National Sun Yat-sen University Kaohsiung Taiwan Department of Tourism and Leisure/Ph.D. Program in Engineering Science Chung Hua University Hsinchu Taiwan Department of Data Science and Analytics I-Shou University Kaohsiung Taiwan

Consider Dirichlet problems of Laplace's equation in a bounded simply-connected domain (Formula presented.), and use the null field equation (NFE) of Green's representation formulation, where the source nodes (Formula presented.) are located on a pseudo-boundary (Formula presented.) outside (Formula presented.) but not close to its boundary (Formula presented.). Simple algorithms are proposed in this article by using the central rule for the NFE, and the normal derivatives (Formula presented.) of the solutions on the boundary (Formula presented.) can be easily obtained. These algorithms are called the discrete null field equation method (DNFEM) because the collocation equations are, indeed, the direct discrete form of the NFE. The bounds of the condition number are like those by the method of fundamental solutions (MFS) yielding the exponential growth as the number of unknowns increases. One trouble of the DNFEM is the near singularity of integrations for the solutions in boundary layers in Green's representation formulation. The traditional BEM also suffers from the same trouble. To deal with the near singularity, quadrature by expansions and the sinh transformation are often used. To handle this trouble, however, we develop two kinds of new techniques: (I) the interpolation techniques by Taylor's formulas with piecewise (Formula presented.) -degree polynomials and the Fourier series, and (II) the mini-rules of integrals, such as the mini-Simpson's and the mini-Gaussian rules. Error analysis is made for technique I to achieve optimal convergence rates. Numerical experiments are carried out for disk domains to support the theoretical analysis made. The numerical performance of the DNFEM is excellent for disk domains to compete with the MFS. The errors with (Formula presented.) can be obtained by combination algorithms, which are satisfactory for most engineering problems. In summary, the new simple DNFEM is based on the NFE, which is different from the boundary elem

关键词： Fourier series

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Privacy-Preserving Dashboard for F.A.I.R Head and Neck Cancer data supporting multi-centered collaborations 14

Privacy-Preserving Dashboard for F.A.I.R Head and Neck Cance...

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14th International Conference on Semantic Web Applications and Tools for Health Care and Life sciences, SWAT4HCLS 2023

作者： Gouthamchand, Varsha Choudhury, Ananya Hoebers, Frank Wesseling, Frederik Welch, Mattea Kim, Sejin Haibe-Kains, Benjamin Kazmierska, Joanna Dekker, Andre van Soest, Johan Wee, Leonard GROW School of Oncology and Reproduction Maastricht University Medical Centre+ Maastricht Netherlands Clinical Data Science Faculty of Health Medicine and Life Sciences Maastricht University Maastricht Netherlands Radiation Medicine Program Princess Margaret Cancer Centre University Health Network TorontoON Canada Dept of Radiation Oncology Greater Poland Cancer Centre II Poznan Poland Brightlands Institute for Smart Society Faculty of Science and Engineering Maastricht University Heerlen Netherlands

Research in modern healthcare requires vast volumes of data from various healthcare centers across the globe. It is not always feasible to centralize clinical data without compromising privacy. A tool addressing these issues and facilitating reuse of clinical data is the need of the hour. The Federated Learning approach, governed in a set of agreements such as the Personal Health Train (PHT) manages to tackle these concerns by distributing models to the data centers instead of the traditional approach of centralizing datasets. One of the prerequisites of PHT is using semantically interoperable datasets for the models to be able to find them. FAIR (Findable, Accessible, Interoperable, Reusable) principles help in building interoperable and reusable data by adding knowledge representation and providing descriptive metadata. However, the process of making data FAIR is not always easy and straight-forward. Our main objective is to disentangle this process by using domain and technical expertise and get data prepared for federated learning. This paper introduces applications that are easily deployable as Docker containers, which will automate parts of the aforementioned process and significantly simplify the task of creating FAIR clinical data. Our method bypasses the need for clinical researchers to have a high degree of technical skills. We demonstrate the FAIR-ification process by applying it to five Head and Neck cancer datasets (four public and one private). The PHT paradigm is explored by building a distributed visualization dashboard from the aggregated summaries of the FAIR-ified datasets. Using the PHT infrastructure for exchanging only statistical summaries or model coefficients allows researchers to explore data from multiple centers without breaching privacy. © 2023 Copyright for this paper by its authors. Use permitted under Creative Commons License Attribution 4.0 International (CC BY 4.0).

关键词： Knowledge representation

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Surgical Instrument Detection for Laparoscopic Surgery using Deep Learning 19

Surgical Instrument Detection for Laparoscopic Surgery using...

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19th International Conference on Electrical engineering/Electronics, Computer, Telecommunications and Information Technology, ECTI-CON 2022

作者： Boonkong, Apiwat Hormdee, Daranee Sonsilphong, Suphachoke Khampitak, Kovit Khon Kaen University Embedded System RandD Group Computer Engineering Khon Kaen Thailand Khon Kaen University Data Science and Health Informatics Program Academic Affairs Khon Kaen Thailand Khon Kaen University Faculty of Medicine Department of Obstetrics and Gynecology Khon Kaen Thailand

ISBN: (纸本)9781665485845

Laparoscopic surgery has transformed conventional open surgery. Robot-Assisted laparoscopic surgery which is minimally invasive is effective for operations in limited space. Nevertheless, the robotic system which is utilized in such surgery can inflict impair to the surgical instruments, organs, or tissues as a consequence of the narrow field of view and space available to operate, and insufficient tactile response. In laparoscopy, the surgeon observes what he operates via digital images which are displayed on a monitor. In addition to the surgeon's expertise, the image-guided surgery system could offer him significant support if that system is capable of understanding those images. Computer Vision has been able to proceed due to the emergence of Machine Learning, and especially Deep Learning. This paper applies Deep Learning for surgical instrument detection for laparoscopic surgery. The fastest model, based on results trained on the COCO 2017 dataset on TensorFlow Framework, for each of 4 algorithms-Faster-RCNN, SSD, CenterNet and EfficientDet-from Model Zoo, along with YOLOv4 on Darknet Framework, have been investigated in this work. The evaluation metrics used are Precision, Recall and F1-score. The results reveal that each model plays its part well;however, YOLOv4 seemed to breakthrough this statement by offering grate result for all three accuracy metrics. © 2022 IEEE.

关键词： Laparoscopy

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Computational Analysis of Mechanical Interactions between a Soft Robotic Device and a Skin-Muscle Phantom for Mechanotherapy

Computational Analysis of Mechanical Interactions between a ...

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Annual International Conference of the IEEE engineering in Medicine and Biology Society (EMBC)

作者： Victor Ticllacuri Renato Mio Biomedical Engineering Program PUCP-UPCH Lima Perú Laboratory of Biomechanics and Applied Robotics Pontificia Universidad Catolica del Peru Lima Perú Laboratory of Biomedical Engineering Universidad Peruana Cayetano Heredia Lima Perú Chair of Digital Health With a Focus on Data Science University of Bayreuth Germany

ISBN: (数字)9798350371499

ISBN: (纸本)9798350371505

Studying the soft robot-tissue mechanical interaction in muscle stimulation devices poses a significant challenge due to the complex behavior of the materials involved. To advance this field, this paper models computationally three types of soft elastomeric actuators designed to perform deep cyclic compression stimuli on human soft tissues for muscle rehabilitation by mechanotherapy. The analysis focuses on the interaction between a phantom representing transversely isotropic muscle and homogeneous skin, with a soft robotic device comprised of a hyperelastic actuator and a rigid support. Results from deformation, stress-strain and surface pressure analysis demonstrate efficient actuation, suggesting deep and focused stimulation on the muscle, while actuators exhibit reliable safety factors and load distribution, implying longer operational life. This lightweight and compact soft robotic device is suitable for integration into a wearable suit for targeted muscle groups stimulation in the lower limbs. Furthermore, this computational approach represents a significant advance in the biomechanical study of soft robot-human tissues interaction, with potential for generalization in similar biomedical device applications. Keywords—Soft Robotics, Mechanotherapy, Transversely Isotropic Muscle, Human-Robot interaction.

关键词： Analytical models Actuators Computational modeling Biological system modeling Biological tissues Phantoms Muscles Soft robotics Skin Load modeling

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Mathematical Modeling and Characterization of a Wearable Soft Robotic Device for Muscle Mechanotherapy

Mathematical Modeling and Characterization of a Wearable Sof...

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Annual International Conference of the IEEE engineering in Medicine and Biology Society (EMBC)

作者： Victor Ticllacuri Renato Mio Biomedical Engineering Program PUCP-UPCH Lima Perú Laboratory of Biomechanics and Applied Robotics Pontificia Universidad Catolica del Peru Lima Perú Laboratory of Biomedical Engineering Universidad Peruana Cayetano Heredia Lima Perú Chair of Digital Health with a Focus on Data Science University of Bayreuth Germany

ISBN: (数字)9798350371499

ISBN: (纸本)9798350371505

Treatments of disuse-induced muscle atrophy entail unmet clinical needs due to the lack of medical devices capable of mimicking physicians manual therapies. Therefore, in this paper we develop and model a wearable soft pneumatic elastomeric actuator to perform deep cyclic compression stimuli on human soft tissues for muscle rehabilitation by mechanotherapy. Static and dynamic characterization of the prototype demonstrate a 2.5 mm active deformation at 100 kPa with 600 mm 3 /s and a 5 Hz bandwidth. We estimate the transfer function of the experimentally acquired pressure, flow and deformation signals, processed by a Gaussian kernel-based approach. Our mathematical model accurately describes the actuator behavior and enables to extract its mechanical parameters. Then, through computational simulations, we illustrate its efficacy in emulating multiple complex bio-inspired movements. Our proposed methodology aims to improve the control efficiency in wearable soft robotics for muscle atrophy treatment.

关键词： Atrophy Actuators Deformation Computational modeling Biological system modeling Transfer functions Prototypes Muscles Soft robotics Mathematical models

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Fusion of Mixture of Experts and Generative Artificial Intelligence in Mobile Edge Metaverse

arXiv

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arXiv 2024年

作者： Liu, Guangyuan Du, Hongyang Niyato, Dusit Kang, Jiawen Xiong, Zehui Jamalipour, Abbas Mao, Shiwen Kim, Dong In The College of Computing and Data Science The Energy Research Institute @ NTU Interdisciplinary Graduate Program Nanyang Technological University Singapore The College of Computing and Data Science Nanyang Technological University Singapore The School of Automation Guangdong University of Technology China The Pillar of Information Systems Technology and Design Singapore University of Technology and Design Singapore The Department of Electrical and Computer Engineering Auburn University Auburn United States The School of Electrical and Computer Engineering University of Sydney Australia The Department of Electrical and Computer Engineering Sungkyunkwan University Korea Republic of

In the digital transformation era, Metaverse offers a fusion of virtual reality (VR), augmented reality (AR), and web technologies to create immersive digital experiences. However, the evolution of the Metaverse is slowed down by the challenges of content creation, scalability, and dynamic user interaction. Our study investigates an integration of Mixture of Experts (MoE) models with Generative Artificial Intelligence (GAI) for mobile edge computing to revolutionize content creation and interaction in the Metaverse. Specifically, we harness an MoE model's ability to efficiently manage complex data and complex tasks by dynamically selecting the most relevant experts running various sub-models to enhance the capabilities of GAI. We then present a novel framework that improves video content generation quality and consistency, and demonstrate its application through case studies. Our findings underscore the efficacy of MoE and GAI integration to redefine virtual experiences by offering a scalable, efficient pathway to harvest the Metaverse's full potential. © 2024, CC BY.

关键词： Augmented reality

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Predicting Microsatellite Instability from Histology Images with Dilated Neighborhood Attention Transformer in Colorectal Cancer

Predicting Microsatellite Instability from Histology Images ...

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IEEE Symposium on Bioinformatics and Bioengineering (BIBE)

作者： Yun-Chi Chen Tung Chao Wimaya Nitya Phandita Tzu-Yu Sun Huai-Zhi Wang Yi-Hsien Hsieh Le-Yin Hsu Che Lin Graduate Institute of Biomedical Electronics and Bioinformatics National Taiwan University (NTU) Taipei Taiwan College of Bioresources and Agriculture NTU Taipei Taiwan Department of Computer Science and Information Engineering National Taiwan University of Science and Technology Taipei Taiwan Graduate Institute of Communication Engineering NTU Taipei Taiwan Data Science Degree Program NTU Taipei Taiwan Department of Electrical Engineering NTU Taipei Taiwan Center for Advanced Computing and Imaging in Biomedicine NTU Taipei Taiwan Smart Medicine and Health Informatics Program NTU Taipei Taiwan

ISBN: (数字)9798331518622

ISBN: (纸本)9798331518639

Microsatellite instability (MSI) is a pivotal genetic marker influencing the efficacy of immunotherapy in colorectal cancer. Traditional MSI examination often requires additional genetic or immunohistochemical tests, whereas histology images, widely available in colorectal cancer diagnosis, offer a valuable alternative for MSI prediction. Although Transformer-based models have demonstrated promising outcomes in predicting MSI from histology images, they are hampered by traditional local attention mechanisms that struggle to capture long-range interdependencies and establish a comprehensive global receptive field. In this study, we introduce DiNAT-MSI, a novel framework for histology-based MSI prediction that incorporates the Dilated Neighborhood Attention Transformer (DiNAT). This model enhances global context recognition and substantially expands receptive fields, all without additional computational burden. Our results demonstrate that DiNAT-MSI achieves a superior patientwise AUROC compared to ResNet18 and Swin Transformer, along with commendable explainability. Our work not only illustrates a more accessible diagnostic tool for leveraging histological data but also underscores the potential of Transformerbased models with sophisticated attention designs in advancing precision medicine for colorectal cancer patients.

关键词： Attention mechanisms Histopathology Computational modeling Precision medicine Small satellites Immunotherapy Colorectal cancer Predictive models Transformers Genetics

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Quantum Fourier Transform of Atrial Fibrillation

Quantum Fourier Transform of Atrial Fibrillation

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Quantum Computing and engineering (QCE), IEEE International Conference on

作者： Yu-Ching Chen Chih-Yu Chen Tsung-Wei Huang Chia-Ho Ou Master Program in Intelligent Computing and Big Data Chung Yuan Christian University Taoyuan Taiwan Quantum Information Center Chung Yuan Christian University Taoyuan Taiwan Department of Computer Science and Information Engineering National Pingtung University Pingtung Taiwan

ISBN: (数字)9798331541378

ISBN: (纸本)9798331541385

Electrocardiograms (ECGs) are crucial for detecting cardiac diseases like atrial fibrillation (AF). Traditional analysis methods like fast Fourier transform (FFT) face challenges with increasing data complexity. This study uses Taipei Veterans General Hospital data to explore quantum Fourier transform (QFT) for ECG analysis. Results show that QFT effectively analyzes ECG signals, matching FFT performance while benefiting from quantum computing's efficiency.

关键词： Heart Quantum computing Fast Fourier transforms Hospitals High performance computing Atrial fibrillation Machine learning Electrocardiography Real-time systems Signal analysis

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A Position Control System for a Single-port Laparoscopic Manipulating Robot

A Position Control System for a Single-port Laparoscopic Man...

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2022 International Electrical engineering Congress, iEECON 2022

作者： Sonsilphong, Amornthep Sonsilphong, Suphachoke Soemphol, Chaiyong Hormdee, Daranee Khampitak, Kovit Rajamangala University of Technology Isan Department of Electrical Engineering Khon Kean Thailand Khon Kaen University Data Science Health Informatics Program Faculty of Medicine Khon Kaen Thailand Mahasarakham University Faculty of Engineering Department of Electrical Engineering Mahasarakham Thailand Khon Kaen University Embedded System RD Group Computer Engineering Faculty of Engineering Khon Kaen Thailand Khon Kean University Faculty of Medicine Department of Obstetrics and Gynecology Khon Kean Thailand

ISBN: (纸本)9781665402064

The research herein proposes a position control system, designed for a single-port surgical robot, based on the lockup table method. The programmable logic controller (PLC) was implemented to move the single- port surgical robot and handle laparoscope and surgical instruments with feedback control. The output responses of the desired angle were investigated under several conditions. The rotating angle allows movement of the laparoscope in the range of -10o to +10o. The error of the desired position of the designed system was less than approximately ± 0.1o. Moreover, the output data from several experiments may be employed to improve the open-loop control systems. This system is also capable of providing computer vision task implementation, enabling semi- automatic or automatic surgery in the future. © 2022 IEEE.

关键词： Laparoscopy

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Advancements in Quantum Radar Technology An Overview of Experimental Methods and Quantum Electrodynamics Considerations

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IEEE Nanotechnology Magazine 2024年第3期18卷 4-14页

作者： Lin, Yu-Cheng Huang, Tsung-Wei Tsai, Pin-Ju Chen, Yen-Hung Zhong, Yuan-Liang Chang, Ching-Ray National Taiwan University Department of Physics Taipei106319 Taiwan Chung-Yuan Christian University Quantum Information Center Taoyuan City320 Taiwan Chung-Yuan Christian University Undergraduate Program in Intelligent Computing and Big Data Taoyuan City320 Taiwan National Central University Department of Optics and Photonics Taoyuan City320 Taiwan National Central University Quantum Technology Center College of Science Taoyuan City320 Taiwan National Central University Center for Astronautical Physics and Engineering Taoyuan City320 Taiwan Chung-Yuan Christian University Department of Physics Taoyuan City320 Taiwan

This paper provides a brief introduction of the current state of quantum radar (QR) technology development, focusing on the experimental methods used for modifying QR in a laboratory setting. We delve into the foundational principles of quantum electrodynamics and consider interferometric aspects. Quantum radar systems, empowered by quantum measurements, extend their capabilities beyond conventional target detection and recognition, encompassing the detection and identification of RF stealth platforms and advanced weapons systems. Quantum technology is gaining paramount significance in various research domains, with the emergence of the concept of quantum radar, which leverages the quantum states of photons to extract information from distant targets. The mechanism involves dispatching photons, or photon clusters, toward the target, whereupon they are absorbed and subsequently re-emitted. The crucial measurement process can be executed in two distinct manners. One approach entails an interferometric measurement, often referred to as phase measurement, conducted on the photons, while the alternative method involves the straightforward quantification of returning photons. These methods are respectively known as Interferometric QR and Quantum Illumination (QI). In both approaches, one can opt to employ stationary quantum states of photons or harness entangled states. Extensive research has demonstrated that the use of entangled states yields the most significant resolution enhancement, achieving optimal results under ideal conditions. Quantum states offer a substantial advantage by virtue of their inherent correlations, referred to as quantum correlations, which augment both resolution and signal-to-noise ratio (SNR) in the radar system. This paper explores the intricacies of these advancements in quantum radar technology, shedding light on the underlying principles and experimental methodologies. © 2007-2011 IEEE.

关键词： Photons

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