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arXiv 2023年

作者： Tang, Haoning Lou, Beicheng Du, Fan Gao, Guangqi Zhang, Mingjie Ni, Xueqi Hu, Evelyn Yacoby, Amir Cao, Yuan Fan, Shanhui Mazur, Eric School of Engineering and Applied Sciences Harvard University CambridgeMA02138 United States Department of Applied Physics Ginzton Laboratory Stanford University StanfordCA94305 United States Department of Physics Faculty of Art and Sciences Harvard University CambridgeMA02138 United States Department of Electrical Engineering and Computer Science University of California at Berkeley BerkeleyCA94720 United States

Reconfigurable optics, optical systems that have a dynamically tunable configuration, are emerging as a new frontier in photonics research. Recently, twisted moiré photonic crystal has become a competitive candidate for implementing reconfigurable optics because of its high degree of tunability. However, despite its great potential as versatile optics components, simultaneous and dynamic modulation of multiple degrees of freedom in twisted moiré photonic crystal has remained out of reach, severely limiting its area of application. In this paper, we present a MEMS-integrated twisted moiré photonic crystal sensor that offers precise control over the interlayer gap and twist angle between two photonic crystal layers, and demonstrate an active twisted moiré photonic crystal-based optical sensor that can simultaneously resolve wavelength and polarization. Leveraging twist- and gap-tuned resonance modes, we achieve high-accuracy spectropolarimetric reconstruction of light using an adaptive sensing algorithm, over a broad operational bandwidth in the telecom range and full Poincaré sphere. Our research showcases the remarkable capabilities of multidimensional control over emergent degrees of freedom in reconfigurable nanophotonics platforms and establishes a scalable pathway towards creating comprehensive flat-optics devices suitable for versatile light manipulation and information processing tasks. Extracting phase, polarization, and wavelength information from an optical signal typically necessitates the use of separate optical components, such as interferometers, polarizers, and narrow-band filters or spectrometers, that cannot easily be integrated1 and are limited in resolution and speed. Recently, however, computational sensing has made it possible to reconstruct target parameters from the optical signal obtained with a single © 2023, CC BY.

关键词： Photonic crystals

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Self-CephaloNet: A Two-stage Novel Framework using Operational Neural Network for Cephalometric Analysis

arXiv

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arXiv 2025年

作者： Sumon, Md. Shaheenur Islam Islam, Khandaker Reajul Rafique, Tanzila Hassan, Gazi Shamim Hossain, Md. Sakib Abrar Podder, Kanchon Kanti Barhom, Noha Tamimi, Faleh Alqahtani, Abdulrahman Chowdhury, Muhammad E.H. Department of Electrical Engineering Qatar University Doha2713 Qatar Shahbag Dhaka1000 Bangladesh Department of Biochemistry University of Regina Saskatchewan Canada Department of Electrical and Computer Engineering Kennesaw State University MariettaGA30060 United States College of Dental Medicine QU Health Qatar University Doha2713 Qatar Department of Biomedical Technology College of Applied Medical Sciences in Al-Kharj Prince Sattam Bin Abdulaziz University Al-Kharj11942 Saudi Arabia Department of Medical Equipment Technology College of Applied Medical Science Majmaah University Majmaah City11952 Saudi Arabia

Cephalometric analysis is essential for the diagnosis and treatment planning of orthodontics. In lateral cephalograms, however, the manual detection of anatomical landmarks is a time-consuming procedure. Deep learning solutions hold the potential to address the time constraints associated with certain tasks;however, concerns regarding their performance have been observed. To address this critical issue, we proposed an end-to-end cascaded deep learning framework (Self-CepahloNet) for the task, which demonstrated benchmark performance over the ISBI 2015 dataset in predicting 19 dental landmarks. Due to their adaptive nodal capabilities, Self-ONN (self-operational neural networks) demonstrate superior learning performance for complex feature spaces over conventional convolutional neural networks. To leverage this attribute, we introduced a novel self-bottleneck in the HRNetV2 (High Resolution Network) backbone, which has exhibited benchmark performance on the ISBI 2015 dataset for the dental landmark detection task. Our first-stage results surpassed previous studies, showcasing the efficacy of our singular end-to-end deep learning model, which achieved a remarkable 70.95% success rate in detecting cephalometric landmarks within a 2mm range for the Test1 and Test2 datasets. Moreover, the second stage significantly improved overall performance, yielding an impressive 82.25% average success rate for the datasets above within the same 2mm distance. Furthermore, external validation was conducted using the PKU cephalogram dataset. Our model demonstrated a commendable success rate of 75.95% within the 2mm range. Copyright © 2025, The Authors. All rights reserved.

关键词： Dentistry

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Regularized Ising Formulation for Near-Optimal MIMO Detection using Quantum Inspired Solvers

Regularized Ising Formulation for Near-Optimal MIMO Detectio...

引用

GLOBECOM 2022 - 2022 IEEE Global Communications Conference

作者： Abhishek Kumar Singh Kyle Jamieson Peter L. McMahon Davide Venturelli Department of Computer Science Princeton University USRA Research Institute for Advanced Computer Science Quantum AI Laboratory (QuAIL) NASA Ames Research Center School of Applied and Engineering Physics Cornell University

ISBN: (纸本)9781665435413

Optimal MIMO detection is one of the most computationally challenging tasks in wireless systems. We show that the quantum-inspired computing approach based on Coherent Ising Machines (CIMs) is a promising candidate for performing near-optimal MIMO detection. We propose a novel regularized Ising formulation for MIMO detection that mitigates a common error floor issue in the direct approach adopted in the existing literature on MIMO detection using Quantum Annealing. We evaluate our methods using a simplified, quantum-inspired model and show that our methods can achieve a near-optimal performance for several Large MIMO systems, like $16\times 16,20\times 20$ , and $24\times 24$ MIMO with BPSK modulation.

关键词： Wireless communication Maximum likelihood detection Bit error rate Modulation Detectors Quantum annealing Global communication

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LIMIT DISTRIBUTION THEORY FOR SMOOTH p-WASSERSTEIN DISTANCES

arXiv

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arXiv 2022年

作者： Goldfeld, Ziv Kato, Kengo Nietert, Sloan Rioux, Gabriel School of Electrical and Computer Engineering Cornell University United States Department of Statistics and Data Science Cornell University United States Department of Computer Science Cornell Universty United States Center for Applied Mathematics Cornell University United States

The Wasserstein distance is a metric on a space of probability measures that has seen a surge of applications in statistics, machine learning, and applied mathematics. However, statistical aspects of Wasserstein distances are bottlenecked by the curse of dimensionality, whereby the number of data points needed to accurately estimate them grows exponentially with dimension. Gaussian smoothing was recently introduced as a means to alleviate the curse of dimensionality, giving rise to a parametric convergence rate in any dimension, while preserving the Wasserstein metric and topological structure. To facilitate valid statistical inference, in this work, we develop a comprehensive limit distribution theory for the empirical smooth Wasserstein distance. The limit distribution results leverage the functional delta method after embedding the domain of the Wasserstein distance into a certain dual Sobolev space, characterizing its Hadamard directional derivative for the dual Sobolev norm, and establishing weak convergence of the smooth empirical process in the dual space. To estimate the distributional limits, we also establish consistency of the nonparametric bootstrap. Finally, we use the limit distribution theory to study applications to generative modeling via minimum distance estimation with the smooth Wasserstein distance, showing asymptotic normality of optimal solutions for the quadratic cost. Copyright © 2022, The Authors. All rights reserved.

关键词： Sobolev spaces

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Recent advancement in MXene-based nanomaterials for flame retardant polymers and composites

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Advanced Industrial and engineering Polymer Research 2025年

作者： Alli, Yakubu Adekunle Bamisaye, Abayomi Ejeromedoghene, Onome Jimoh, Olusegun Oluwaseun Oni, Samuel Oluwadadepo Ezeamii, Gerald Chekwube Ozoemezim, Chukwurimazu Ogunlaja, Adeniyi Sunday Abdul Rashid, Suraya Kandola, Baljinder K. Department of Chemistry Nelson Mandela University Port Elizabeth South Africa Department of Chemistry Faculty of Natural and Applied Sciences Lead City University Oyo State Ibadan Nigeria College of Chemistry Chemical Engineering and Materials Science Soochow University 199 Renai Road Jiangsu Province Suzhou215123 China Department of Pharmacology Southern Illinois University Carbondale62702 United States Department of Physics Georgia Southern University Statesboro30458 United States Department of Applied Instrumentation and Control School of Computing Engineering and Built Environment Glasgow Caledonian University United Kingdom Department of Electrical and Computer Engineering University of Florida United States Institute of Nanoscience & Nanotechnology Universiti Putra Malaysia Malaysia Institute for Materials Research and Innovation University of Bolton BoltonBL3 5AB United Kingdom

This review explores the advancements in MXene-based nanomaterials as flame-retardant additives for polymers and composites, driven by increasing fire safety demands across industries. It highlights the critical role of flame-retardant materials in mitigating fire hazards in structures, electronics, transportation, and textiles, emphasizing the need for innovative solutions due to stricter safety regulations. MXenes, a class of two-dimensional nanomaterials with unique structural properties such as high surface area, tunable composition, and superior thermal stability, are presented as promising candidates. The review discusses various synthesis and incorporation techniques for MXenes in polymer matrices, showcasing improvements in flame retardancy, mechanical properties, and thermal stability. Additionally, it emphasizes the multifunctionality of MXenes, which offer conductivity, electromagnetic shielding, and mechanical reinforcement alongside flame suppression. In conclusion, the review underscores MXenes' potential to address challenges in flame-retardant materials, advocating for further research to optimize their applications and explore synergies with other agents to enhance safety and sustainability in engineering materials. © 2025 Kingfa Scientific and Technological Co. Ltd.

关键词： Nanocomposites

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Intelligent Distributed Grid's Reactive Overcurrent, or over Prevention: computer Intelligence in Power Grid

Intelligent Distributed Grid's Reactive Overcurrent, or over...

引用

Communication, Security and Artificial Intelligence (ICCSAI), International Conference on

作者： K. Suneeta Preeti Verma Pankaj Tripathi A. Sivasangari Pawan Kumar Veeraswamy Ammisetty Department of EEE Pallavi Engineering College Hyderabad School of Electronic and Electrical Engineering Uttarakhand University Uttarakhand India Department of Electrical Engineering Invertis University Bareilly Uttar Pradesh India Sathyabama Institute of Science and Technology Chennai Tamil Nadu School of Basic & Applied Sciences K. R. Mangalam University Gurugram Haryana India Department of Computer Science & Engineering Koneru Lakshmaiah Education Foundation Vaddeswaram India

Decentralized energy assets (DERs- DCE) that have substantial penetration pose a number of protection-related problems, including protection blindness, false falling, unsynchronized reclosing, et. Demand responses & reconfiguration of networks are two more active managerial technologies that pose a danger to current security measures. Relay configurations are continuously adjusted upon online detection of network architectures plus the state of renewable energy sources in this research's mix of regional adaptable adaptive telecommunication helped centralized defense. The centrally located protection improvements relay environments during significant alterations in grid layouts, such as rewiring the network as well as transferring across islanded alongside networked transportation methods. Moreover, the local adapting safeguards information communicate settings to reflect Distributed energy resources (status (ON/OFF) using locally gathered facts. These digital model (RTDS) simulation findings distribution grid is used to show the usefulness of the proposed method. The suggested algorithm offers effective fault detection & selection under various networking conditions, according to simulation findings.

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Relative magnetic field and slipping effect on Casson dusty fluid of two phase fluctuating flow over inclined parallel plate

引用

South African Journal of Chemical engineering 2023年 44卷 135-146页

作者： khan, Dolat Kumam, Poom Kumam, Wiyada Suttiarporn, Panawan Rehman, Ali Fixed Point Research Laboratory Fixed Point Theory and Applications Research Group Center of Excellence in Theoretical and Computational Science (TaCS-CoE) Faculty of Science King Mongkut's University of Technology Thonburi (KMUTT) 126 Pracha Uthit Rd. Bang Mod Bangkok Thung Khru 10140 Thailand Center of Excellence in Theoretical and Computational Science (TaCS-CoE) Faculty of Science King Mongkut's University of Technology Thonburi (KMUTT) 126 Pracha Uthit Rd. Bang Mod Bangkok Thung Khru 10140 Thailand Applied Mathematics for Science and Engineering Research Unit (AMSERU) Program in Applied Statistics Department of Mathematics and Computer Science Faculty of Science and Technology Rajamangala University of Technology Thanyaburi (RMUTT) Pathum Thani 12110 Thailand Faculty of Science Energy and Environment King Mongkut's University of Technology North Bangkok Rayong Campus Rayong 21120 Thailand Special Interest Group for Modelling and Data Analytics Faculty of Ocean Engineering Technology and Informatics Universiti Malaysia Terengganu Terengganu Kuala Nerus 21030 Malaysia

Due to its significant applications in magnetic devices for cell separation, magnetic drugs for cancer tumor treatment, blood flow adjustment during surgery, magnetic endoscopy, and fluid pumping in industrial and engineering processes, magnetohydrodynamics (MHD) has a wide range of applications. Therefore, the aim of this study to investigate the Relative Magnetic Field and slipping effect on Casson dusty fluid of two-phase fluctuating flow over inclined parallel plate. More exactly, the relative magnetic phenomena are fixed relatively to the plate (MFFRP) or fixed relatively to the fluid (MFFRF). The mathematical modeling was established as the set of partial differential equations for dusty Casson fluid. Buckingham's pi theorem is used to find out the dimensionless variables, to make our system dimensionless. The solution in perturb form is to find out by incorporating Poincare–Lighthill perturbation technique (PLPT). To know in-depth different parameters the graphical results for both velocities are plotted with the help of software mathcad- 15. It is clearly detected that the relative magnetic field performs a vital part in the fluid as well as particle motion. Moreover, the relative magnetic field play a vital role in the decreasing of skin friction of both plates. © 2023

关键词： Brinkman fluid Dust particles Fluctuating vertical plate Inclined relative magnetic field PLPT

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Comparative analysis of deep learning and machine learning techniques for forecasting new malaria cases in Cameroon's Adamaoua region

引用

Intelligence-Based Medicine 2025年 11卷 100220-100220页

作者： Naroum, Esaie Maka, Ebenezer Maka Abboubakar, Hamadjam Dayang, Paul Bamana, Appolinaire Batoure Garga, Benjamin Daouda, Hassana Daouda Bakouri, Mohsen Khan, Ilyas University of Ngaoundéré Department of Mathematics and computer Science Faculty of Science P.O. Box 455 Ngaoundéré Cameroon University of Douala National Higher Polytechnic School Department of Computer Engineering and Telecommunications P.O. Box 2701 Douala Cameroon University of Ngaoundéré University Institute of Technology Department of Computer Engineering P.O. Box 455 Ngaoundéré Cameroon University of Ngaoundéré Laboratory of Analysis Simulation and Test (LASE) P.O. Box 455 Ngaoundéré Cameroon University of Ngaoundéré School of Geology and Mining Engineering Department Applied Mathematics and Computer Science P.O. Box 115 Meiganga Cameroon University of Ngaoundéré ENSAI Department of Electrical Electronic and Automatic Engineering P.O. Box 455 Ngaoundéré Cameroon Majmaah University College of Applied Medical Science Department of Medical Equipment Technology Al-Majmaah 11952 Saudi Arabia Department of Mathematics College of Science Al-Zulfi Majmaah University Al-Majmaah 11952 Saudi Arabia

The Plasmodium parasite, which causes malaria is transmitted by Anopheles mosquitoes, and remains a major development barrier in Africa. This is particularly true considering the conducive environment that promotes the spread of malaria. This study examines several machine learning approaches, such as long short term memory (LSTM), random forests (RF), support vector machines (SVM), and data regularization models including Ridge, Lasso, and ElasticNet, in order to forecast the occurrence of malaria in the Adamaoua region of Cameroon. The LSTM, a recurrent neural network variant, performed the best with 76% accuracy and a low error rate (RMSE = 0.08). Statistical evidence indicates that temperatures exceeding 34 degrees halt mosquito vector reproduction, thereby slowing the spread of malaria. However, humidity increases the morbidity of the condition. The survey also identified high-risk areas in Ngaoundéré Rural and Urban and Meiganga. Between 2018 and 2022, the Adamaoua region had 20.1%, 12.3%, and 10.0% of malaria cases, respectively, in these locations. According to the estimate, the number of malaria cases in the Adamaoua region will rise gradually between 2023 and 2026, peaking in 2029 before declining in 2031. © 2025 The Authors

关键词： Adamaoua-Cameroon Deep learning Machine learning Malaria Metric evaluation Time-series forecasting

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Consumer Technology in Task Offloading and Edge Resource Allocation: AIoT and Edge Computing for Next-Generation Communication

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IEEE Transactions on Consumer Electronics 2025年

作者： Byeon, Haewon Alsaadi, Mahmood Quraishi, Aadam Alghamdi, Azzah Ahanger, Tariq Ahamed Keshta, Ismail Xalikovich, Pardayev Abdunabi Soni, Mukesh Bhatt, Mohammed Wasim Convergence Department Korea University of Technology and Education Cheonan Korea Republic of Department of Computer Sciences College of Science University of Al Maarif Al Anbar31001 Iraq M.D. Research Intervention Treatment Institute HoustonTX United States Computer Information Systems Department College of Computer Science and Information Technology Imam Abdalrhman Bin Faisal University Khobar Saudi Arabia Department of Management Information Systems CoBA Prince Sattam Bin Abdulaziz University Saudi Arabia Computer Science and Information Systems Department College of Applied Sciences AlMaarefa University Riyadh Saudi Arabia The Department of Accounting and Reporting Tashkent State University of Economics Tashkent Uzbekistan Division of Research and Development Lovely Professional University Phagwara India Dr. D. Y. Patil Vidyapeeth Dr. D. Y. Patil School of Science & Technology Pune Tathawade Pune India Model Institute of Engineering and Technology J&K Jammu India

Artificial Intelligence of Things (AIoT) edge computing has emerged as a critical enabler for consumer technology, easing the load on distribution grid networks through enhanced data transmission and processing capabilities. The Internet of Things (IoT), a modern network paradigm, connects devices using sensors and communication mediums to enable seamless information exchange. However, the limited computational capacity of edge nodes poses challenges in optimizing AIoT edge resources compared to cloud computing. To address this, a cloud-edge three-layer framework for task offloading and edge resource allocation is proposed in the context of consumer technology and distribution grids. This model incorporates random tasks, limited resources, unequal processing power, and high latency requirements. It features two key phases: a resource auction using a multi-round iterative process and compute offloading managed by a Deep Reinforcement Learning (DRL) approach. Enhanced algorithms such as Double DQN and Dueling DQN are integrated into the job offloading process to improve performance. Simulations validate the convergence of the task offloading algorithm and demonstrate that the proposed methods significantly enhance computational efficiency and resource utilization for edge nodes. These advancements offer promising solutions for the dynamic needs of consumer technology and future communication networks. © 2025 IEEE.

关键词： Computation offloading

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A New Approach to Line-Sphere and Line-Quadrics Intersection Detection and Computation

arXiv

引用

arXiv 2022年

作者： Skala, Vaclav Department of Computer Science and Engineering Faculty of Applied Sciences University of West Bohemia Univerzitni 8 PlzenCZ 306 14 Czech Republic

Line intersection with convex and un-convex polygons or polyhedron algorithms are well known as line clipping algorithms and very often used in computer graphics. Rendering of geometrical problems often leads to ray tracing techniques, when an intersection of many lines with spheres or quadrics is a critical issue due to ray-tracing algorithm complexity. A new formulation of detection and computation of the intersection of line (ray) with a quadric surface is presented, which separates geometric properties of the line and quadrics that enables pre-computation. The presented approach is especially convenient for implementation with SSE instructions or on *** Codes 68xx, 68U05 © 2022, CC BY.

关键词： Ray tracing

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