检索结果-内蒙古大学图书馆

On the particle approximation of lagged Feynman–Kac formulae

Stochastic Processes and their Applications 2025年 188卷

作者： Awadelkarim, Elsiddig Caffarel, Michel Del Moral, Pierre Jasra, Ajay Applied Mathematics and Computational Science Program Computer Electrical and Mathematical Sciences and Engineering Division King Abdullah University of Science and Technology Thuwal23955-6900 Saudi Arabia University of Toulouse CNRS-Lab. de Chimie et Physique Quantiques Toulouse31062 France Centre de Recherche Inria Bordeaux Sud-Ouest Talence33405 France School of Data Science The Chinese University of Hong Kong Shenzhen Shenzhen China

In this paper we examine the numerical approximation of the limiting invariant measure associated with Feynman–Kac formulae. These are expressed in a discrete time formulation and are associated with a Markov chain and a potential function. The typical application considered here is the computation of eigenvalues associated with non-negative operators as found, for example, in physics or particle simulation of rare-events. We focus on a novel lagged approximation of this invariant measure, based upon the introduction of a ratio of time-averaged Feynman–Kac marginals associated with a positive operator iterated l∈N times;a lagged Feynman–Kac formula. This estimator and its approximation using Diffusion Monte Carlo (DMC) are commonly used in the physics literature. In short, DMC is an iterative algorithm involving N∈N particles or walkers simulated in parallel, that undergo sampling and resampling operations. In this work, it is shown that for the DMC approximation of the lagged Feynman–Kac formula, one has an almost sure characterization of the L1-error as the time parameter (iteration) goes to infinity and this is at most of O(exp{−κl}/N), for κ>0. In addition a non-asymptotic in time, and time uniform L1−bound is proved which is O(l/N). We also prove a novel central limit theorem to give a characterization of the exact asymptotic in time variance. This analysis demonstrates that the strategy used in physics, namely, to run DMC with N and l small and, for long time enough, is mathematically justified. Our results also suggest how one should choose N and l in practice. We emphasize that these results are not restricted to physical applications;they have broad relevance to the general problem of particle simulation of the Feynman–Kac formula, which is utilized in a great variety of scientific and engineering fields. © 2025 Elsevier B.V.

关键词： Iterative methods

来源：评论

学校读者我要写书评

暂无评论

Land Use and Land Cover Classification for Temporal Analysis on Ganjam District Region, Odisha Using Remote Sensing and Google Earth Engine

Land Use and Land Cover Classification for Temporal Analysis...

引用

International Conference on ICT in Business Industry & Government (ICTBIG)

作者： Vinayak Sharma Ankur Singh Yashrai Prasad Suruchi Gupta Tanupriya Choudhury Ketan Kotecha School of Computer Science University of Petroleum and Energy Studies (UPES) Dehradun Uttarakhand India CSE Dept. Symbiosis Institute of Technology Symbiosis International(Deemed University) Pune Maharashtra India Symbiosis Center for Applied Artificial Intelligence Symbiosis Institute of Technology Symbiosis International (Deemed University) Pune Maharashtra India

Land use/land cover change (LULC) affects natural ecosystems and the environment, which can lead to changes in land resources, biodiversity, ecological functions, and environmental components. This is why LULC Change Analysis plays an important role in planning and using current and future natural resources for the sustainable development of any country. This paper performs LULC classification and analysis over a study region in Ganjam District, Odisha, India. Satellite data was extracted from Landsat 7 and 8 satellites that provide spectral and multi-temporal images. For the LULC classification, 5 LULC classes were considered such as water bodies, vegetation, urban areas, barren Land, and cropland. A machine learning-based approach was applied using Google Earth Engine (GEE) to compare different supervised classifiers such as Support Vector Machine (SVM), Classification and Regression Trees (CART), and Random Forest over the periods between 2010 and 2020. In this study, SVM gave the best results with 92 percent Overall Accuracy(OA) and 0.90 Kappa Value. Also, the change analysis showed that Urban areas increased by 112 percent, cropland by 9 percent, and barren land decreased by 68 percent between 2010 and 2020.

关键词：

来源：评论

学校读者我要写书评

暂无评论

Watershed delineation in South Bengal Ganges Delta Region of Bangladesh using satellite imagery and digital elevation model

引用

Arabian Journal of Geosciences 2022年第10期15卷 1-10页

作者： Karmaker, Sourav Sheikh, Shahjahan Islam, Md. Shafiqul Nisha, Rifat Sharmin Department of Geo-Information Science and Earth Observations Patuakhali Science and Technology University Patuakhali Bangladesh Faculty of Computer Science Mathematics and Geoinformatics Stuttgart University of Applied Sciences Stuttgart Germany Faculty of Environmental Science and Disaster Management Patuakhali Science and Technology University Patuakhali Bangladesh Key Lab of Urban Environment and Health Institute of Urban Environment Chinese Academy of Sciences Xiamen China University of Chinese Academy of Sciences Beijing China

Coastal Bangladesh has experienced large scale changes in erosion and deposition in the Meghna Estuary and the big islands due to the Ganges–Brahmaputra-Meghna stream background. Also, the coastal area is prone to natural disasters almost in every year which creates a change in the ground water level, increases the surface water infiltration, soil salinity, and flood level. Considering these facts of the coastal area of Bangladesh, watershed delineation can contribute to proper planning and management of watershed to mitigate the surface and groundwater problems. Therefore, in this paper GIS and remote sensing techniques were used to identify the exact water course using spatial data to know the current watershed condition of the South Ganges Delta Region of Bangladesh. Here, Hydrology Toolset was utilized to analyze and identify correct watershed flow direction, network density, and confluence thresholds using digital elevation model (DEM) of the study area. The well-known D8 algorithm deployed to calculate the stream flow from each cell to its downslope neighbor and 100–1500 thresholds to determine the flow directions and transform the streams into line features for watershed network density measurement. The results showed that the length and density of the networks were proportional to the threshold. In consequence, the density of the stream network increased dramatically with the soaring of thresholds. Therefore, the results also revealed that when the convergence threshold set to 900, the extracted stream network appeared the closest to the exact water flow in the research area. It showed various sharp flows of the stream network, their length and density, as well as the convergence threshold. The findings of this study can help to quantify the watershed basin and river flow watercourses that can contribute to plan and manage future flood forecasting method of the study region.

关键词：

来源：评论

学校读者我要写书评

暂无评论

Intelligent Energy-Aware Thermal Exchange Optimization with Deep Learning Model for IoT-Enabled Smart Healthcare

引用

Journal of Healthcare Engineering 2023年第1期2023卷 3830857页

作者： Ragab, Mahmoud Binyamin, Sami Saeed Information Technology Department Faculty of Computing and Information Technology King Abdulaziz University Jeddah21589 Saudi Arabia Department Faculty of Science Al-Azhar University Nasr City Cairo11884 Egypt Centre for Artificial Intelligence in Precision Medicines King Abdulaziz University Jeddah21589 Saudi Arabia Computer and Information Technology Department Applied College King Abdulaziz University Jeddah21589 Saudi Arabia

In recent years, Internet of Things (IoT) and advanced sensor technologies have gained considerable interest in linking different medical devices, patients, and healthcare professionals to improve the quality of medical services in a cost-effective manner. The evolution of the smart healthcare sector has considerably enhanced patient safety, accessibility, and operational competence while minimizing the costs incurred in healthcare services. In this background, the current study develops intelligent energy-aware thermal exchange optimization with deep learning (IEA-TEODL) model for IoT-enabled smart healthcare. The aim of the proposed IEA-TOEDL technique is to group the IoT devices into clusters and make decisions in the smart healthcare sector. The proposed IEA-TEODL technique constructs clusters using the energy-aware chaotic thermal exchange optimization-based clustering (EACTEO-C) scheme. In addition, the disease diagnosis model also intends to classify the collected healthcare data as either presence or absence of the disease. To accomplish this, the proposed IEA-TODL technique involves several subprocesses such as preprocessing, K-medoid clustering-based outlier removal, multihead attention bidirectional long short-term memory (MHA-BLSTM), and weighted salp swarm algorithm (WSSA). The utilization of outlier removal and WSSA-based hyperparameter tuning process assist in achieving enhanced classification outcomes. In order to demonstrate the enhanced outcomes of the IEA-TEODL approach, a wide range of simulations was conducted against benchmark datasets. The simulation results inferred the enhanced outcomes of the IEA-TEODL technique over recent techniques under distinct evaluation metrics. © 2023 Mahmoud Ragab and Sami Saeed Binyamin.

关键词： Internet of things

来源：评论

学校读者我要写书评

暂无评论

Secured Banking Systems for Critical Fraud Detection using Machine Learning Model

Secured Banking Systems for Critical Fraud Detection using M...

引用

International Conference on Computing and Networking technology (ICCNT)

作者： Sagar Varma Samanthapudi Piyush Rohella Sheetal Temara T. Kiruthiga Applied Data Science The Polis Center at Indiana University Purdue University Indianapolis Indiana polis Indiana USA Payments & Commerce GoDaddy Edmonds Washington USA Dept of Computer & Information Sciences University of the Cumberlands Williamsburg KY USA Department of ECE Vetri Vinayaha College of Engineering and Technology Trichy Tamil Nadu INDIA

ISBN: (数字)9798350370249

ISBN: (纸本)9798350370270

The goal of computerized fraud detection in online banking systems is to identify and save you fraudulent transactions in actual time. Device-gaining knowledge of strategies can provide a powerful means to detect anomalies in consumer behavior that might suggest feasible fraud. This consists of spotting transactions that can be out of the norm, primarily based on purchaser spending habits, and using exceptionally sophisticated algorithms to discover complex styles of fraudulent pastimes. Similarly, gadgets gaining knowledge of fashions may be used to identify suspicious consumer behavior and expect future fraudulent sports. With the aid of leveraging device learning, banks can proactively screen accounts for signs of fraud and speedy cope with online safety threats.

关键词： Consumer behavior Online banking Computational modeling Machine learning Fraud Safety Sports

来源：评论

学校读者我要写书评

暂无评论

Enhancing Cooperative Spectrum Sensing Performance with Fusion Rule in Cognitive Radio: Hybrid Techniques

Enhancing Cooperative Spectrum Sensing Performance with Fusi...

引用

International Conference on Computational and Characterization Techniques in Engineering & sciences (CCTES)

作者： K.Deepthi N. Sreevani Vijilius Helena Raj A Sangeetha Rajeev Sobti Z. Salman Department of Mechanical Engineering Avanthi Insistute of Engineering and Technology India Department of CSE(Cyber Security) Institute of Aeronautical Engineering Hyderabad India Department of Applied Sciences New Horizon College of Engineering Bangalore India Department of Computer Science and Engineering MLR Institute of Technology Hyderabad Telangana India Lovely Professional University Phagwara India Hilla University College Babylon Iraq

ISBN: (数字)9798350364699

ISBN: (纸本)9798350364705

The issue of limited wireless spectrum may be addressed with the use of Cognitive Radio (CR). Without affecting the primary users (PU), or licenced users, it allows other users, known as secondary users or unlicensed users, to exploit spectrum gaps, improving spectrum efficiency. Energy detection, a matching filter, and cyclostationary detection make up the CR, which determines whether the spectrum is idle or not. Cognitive Radio Networks (CRNS) are hindered in their ability to improve performance by noise. No signal-to-noise ratio (SNR) may be efficiently achieved with a cooperative spectrum employing a set sensing time in terms of throughput performance. There are two ways that this research suggests they might improve the effectiveness of energy detectors in the wireless spectrum. At its core, the first method is an energy detector-based hybrid of the Additive Wavelet Transform as well as the Homomorphic (AWTH). Mixing the Haar Discrete Wavelet Transform with the Homomorphic technique (HDWTH) is the basis of the second approach. The Two Quality Metrics Used: False Alarm Probability (Pf) and Probability Detection (Pd). The efficiency of the energy detector is enhanced by implementing the two methods that have been suggested. Metrics for quality demonstrate that the first method improves the wireless spectrum's Pd point perspective. But from a throughput perspective, the second strategy succeeds in maximising.

关键词： Measurement Wireless sensor networks Additives Detectors Throughput Discrete wavelet transforms Sensors Cognitive radio Signal to noise ratio Radio spectrum management

来源：评论

学校读者我要写书评

暂无评论

Temporal mode shaping of single photons from a solid-state quantum emitter

Temporal mode shaping of single photons from a solid-state q...

引用

CLEO: science and Innovations, S and I 2022

作者： Kim, Kyu Young Richardson, Christopher J.K. Waks, Edo Kim, Je-Hyung Department of Physics Ulsan National Institute of Science and Technology Ulsan44919 Korea Republic of Laboratory for Physical Sciences University of Maryland College ParkMD20740 United States Department of Electrical and Computer Engineering Institute for Research in Electronics and Applied Physics University of Maryland College ParkMD20742 United States Joint Quantum Institute University of Maryland The National Institute of Standards and Technology College ParkMD20742 United States

Through multi-exciton cascade recombination in a quantum dot and engineered Purcell effect in a photonic crystal cavity, we demonstrate the single-photon emission with Gaussian-like spatial and temporal modes and temp... 详细信息

ISBN: (纸本)9781557528209

关键词： Photons

来源：评论

学校读者我要写书评

暂无评论

Routing Single Photons from a Trapped Ion Using a Photonic Integrated Circuit

引用

Physical Review applied 2023年第3期19卷 034001-034001页

作者： Uday Saha James D. Siverns John Hannegan Mihika Prabhu Qudsia Quraishi Dirk Englund Edo Waks Department of Electrical and Computer Engineering University of Maryland College Park Maryland 20742 USA Institute for Research in Electronics and Applied Physics (IREAP) University of Maryland College Park Maryland 20742 USA Department of Physics University of Maryland College Park Maryland 20742 USA Department of Electrical Engineering and Computer Science Massachusetts Institute of Technology Cambridge Massachusetts 02139 USA United States Army Research Laboratory Adelphi Maryland 20783 USA Joint Quantum Institute (JQI) University of Maryland College Park Maryland 20742 USA

Trapped ions are promising candidates for nodes of a scalable quantum network due to their long-lived qubit coherence times and high-fidelity single- and two-qubit gates. Future quantum networks based on trapped ions will require a scalable way to route photons between different nodes. Photonic integrated circuits from fabrication foundries provide a compact solution to this problem. However, these circuits typically operate at telecommunication wavelengths that are incompatible with the strong dipole emissions of trapped ions. In this work, we demonstrate the routing of single photons from a trapped ion using a photonic integrated circuit. We employ quantum frequency conversion to match the emission of the ion to the operating wavelength of a foundry-fabricated silicon nitride photonic integrated circuit, achieving a total transmission of 31.0% ± 0.9% through the device. Using programmable phase shifters, we switch the single photons between the output channels of the circuit and demonstrate a 50:50 beam splitting condition. These results constitute an important step towards programmable routing and entanglement distribution in large-scale quantum networks and distributed quantum computers.

关键词： Integrated optics Optical quantum information processing Quantum communication Quantum information with trapped ions Quantum interconnects Quantum networks Trapped ions

来源：评论

学校读者我要写书评

暂无评论

Quantum Computing based Channel and Signal Modeling for 6G Wireless System

TechRxiv

引用

TechRxiv 2023年

作者： Farouk, Ahmed AbuAli, Najah Abed Mumtaz, Shahid The Department of Computer Science Faculty of Computers and Artificial Intelligence South Valley University Hurghada Egypt United Arab Emirates Department of Applied Informatics Silesian University of Technology Akademicka 16 Gliwice44-100 Poland Nottingham Trent University Engineering Department United Kingdom

Sixth-generation wireless technology (6G) introduces a paradigm shift and fundamental transformation of digital wireless connectivity by converging pillars of softwarization, virtualization, and wireless networks. Terahertz (THz) communication technologies are predicted to become more significant in 6G applications as the requirement for bandwidth grows and wireless cell sizes shrink. As a result, 6G will be able to deal with and manage numerous devices and services requiring enhanced spectral throughput and efficiently work with high interference levels. This convergence highlights the increased threat surface of 6G networks and the potentially severe impacts of sophisticated cyber incidents. Furthermore, the heterogeneity of connected devices and provided services will generate a huge amount of data to be processed and managed efficiently. Quantum computing (QC) can efficiently solve several 6G computationally hard problems with a quadratic speedup and provide adaptive techniques for controlling the current and future significant security threats of the 6G network. This article will discuss the role of various QC components on 6G and explore the opportunities and challenges to achieving such transformation. © 2023, CC BY.

关键词： Quantum cryptography

来源：评论

学校读者我要写书评

暂无评论

Advanced Deep Learning Models for Groundwater Contaminant Dynamics at the Savannah River Site

Advanced Deep Learning Models for Groundwater Contaminant Dy...

引用

Future Machine Learning and Data science (FMLDS), IEEE International Conference on

作者： Jayesh Soni Himanshu Upadhyay Haruko Wainwright Zexuan Xu Leonel Lagos Applied Research Center Florida International University Miami USA Electrical and Computer Engineering Florida International University Miami USA Nuclear Science and Engineering Massachusetts Institute of Technology Cambridge USA Climate Dept Lawrence Berkeley National Laboratory Berkeley USA Moss Department Of Construction Management Florida International University Miami USA

ISBN: (数字)9798350391213

ISBN: (纸本)9798350391220

Advances in sensor technology have greatly enhanced the monitoring and assessment of environmental conditions. However, groundwater monitoring presents unique challenges, primarily in accurately detecting anomalies amidst sensor noise, fluctuations, and other inconsistencies in the data. The introduction of low-cost in-situ sensors has dramatically increased data volumes, requiring more advanced analytical techniques. This paper investigates the potential of Artificial Intelligence and Machine Learning (AI/ML), specifically Long Short-Term Memory (LSTM) Autoencoder models and Transformers, to tackle these challenges. LSTM Autoencoders, a specialized form of recurrent neural networks, are well-suited for sequential data analysis and anomaly detection, particularly in time-based sensor readings. The LSTM Autoencoder can compress the data and reconstruct normal patterns by training on historical sensor data representing normal groundwater conditions, thus identifying deviations that signal potential contamination. Meanwhile, transformer models, known for their attention mechanism and ability to capture long-range dependencies, are incorporated to enhance further their ability to distinguish between natural data variations and significant anomalies in complex, dynamic groundwater environments. We apply these LSTM Autoencoder and Transformer approaches to US-DoE Savannah River Site F-Area datasets, demonstrating their robustness and adaptability in identifying subtle and progressive groundwater contamination. This approach improves the accuracy of groundwater monitoring and supports a proactive stance in environmental preservation and public health protection.

关键词： Attention mechanisms Groundwater Autoencoders Transformers Data models Rivers Public healthcare Protection Long short term memory Contamination

来源：评论

学校读者我要写书评

暂无评论

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案：

请选择收藏分类：

通借通还

建议与咨询 留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案： 新增检索档案 确定 取消

请选择收藏分类： 新增自定义分类 确定 取消

通借通还

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

请选择保存的检索档案：

请选择收藏分类：