检索结果-内蒙古大学图书馆

International Conference on Wireless and Optical Communications ( WOCC)

作者： Neelu Sinha Ryan F. Evans Mackenzie Carbo Department of Mathematics and Computer Science Fairleigh Dickinson University Madison NJ USA Dept. of Math and Comp Sci FDU CS Hub and Haskell Elementary School Wanaque School District Haskell NJ USA

The last decade has seen a surge in expanding access to computer science (CS) education, especially for K-12, with many states even stipulating student learning standards in CS and Computational Thinking (CT). Our 21st century K-12 students are no longer just computer users, but are now required to be computationally literate creators with proficient skills both in the concepts and practices of CS and CT. At the same time, technology continues to pervade our lives and expand at a relentless pace and all aspects of our lives are now embedded in technology surrounded by Artificial Intelligence (AI). AI in the form of Machine Learning (ML) is a key technology in a diversity of applications, where we use sensors to meaningfully perceive the world around us, analyze and organize the perceived data, and autonomously use that data to make predictions and decisions. In higher education, AI/ML courses proliferate, with many institutions now conferring degrees and certifications in these. To an extent, some high schools (grades 9–12) have started introducing these concepts in a technology class, or a robotics club, or as an after-school activity. As for middle (grades 6–8) and elementary school (grades K-5), there are very few examples of such instruction. In this paper, we present a complete framework for elementary and middle school teachers to help them prepare and incorporate AI/ML lessons in their classrooms using hands-on active learning strategies. We want to empower these teachers to impart improved learning to their students, which in turn will prepare their students to become effective thinkers, problem solvers, communicators, and gain necessary skills for high-skilled and high-demand jobs. We describe a detailed AI/ML lesson plan based on standards and framework, AI4K12 big ideas, art and science of curriculum design, active learning, and culturally responsive and inclusive pedagogy. Then we discuss our experiences in teaching the same to $\boldsymbolmath.^{\math.f{

关键词：

来源：评论

学校读者我要写书评

暂无评论

Ultraviolet spectrum downshifting in polymer nanocomposite films for the enhancement of optoelectronic devices 17

Ultraviolet spectrum downshifting in polymer nanocomposite f...

引用

Photonic Fiber and Crystal Devices: Advances in Materials and Innovations in Device Applications XVII 2023

作者： Darwish, Abdalla M. Sarkisov, Sergey S. Patel, Darayas N. Fedoseev, Alex Rossmanith, David Grayol, Brandon Hribljan, Anja Koplitz, Brent Rashedy, Remah El Physics and Pre-Engineering Dept. Dillard University 2601 Gentilly Blvd New OrleansLA70122 United States SSS optical Technologies 515 Sparkman Drive HuntsvilleAL35816 United States Math and Computer Science Dept Oakwood University 7000 Adventist Blvd HuntsvilleAL35896 United States Solestial Inc. TempeAZ85284 United States Chemistry Dept. Tulane University 6823 St Charles Ave New OrleansLA70118 United States f125 Putney Rd battleboroVT0530 United States

ISBN: (纸本)9781510665781

We report on polymer nanocomposite films with ultraviolet (UV) spectrum down-shifting that can be transferred using the open-air multi-beam multi-target pulsed laser deposition (MBMT-PLD) on opto-electronic devices, such as photovoltaic (PV) cells, for the enhancement of their performance. The nanocomposites were made of the space-grade polymer CORIN impregnated with nanoparticles (NPs) of rare-earth (RE) doped compound NaYF4: Eu3+. NPs had a peak of down-shifted photoluminescence (PL) at 623 nm and a PL quantum yield (PLQE) of ~ 50%. The enhancement of the coated PV cells was two-fold: (a) protection from harmful solar UV radiation and (b) the increase of the PV conversion efficiency. We describe the results of characterization of the NPs using dynamic light scattering, X-ray diffraction, and optical spectroscopy. The nanocomposite films were deposited on Silicon heterojunction (SHJ), Copper-Indium-Gallium-Selenide (CIGS) and inverted metamorphic multijunction (IMM) solar cells. The cells were exposed to 365-nm UV radiation from a light emitting diode (LED). The I-V characteristics of the cells were measured with a solar simulator using AM0 filter. The proposed films improved UV stability of all three cell types: the power degradation significantly slowed down, CIGSs (by half). The proposed films have great commercial potential, especially for the applications to space power. © 2023 SPIE. All rights reserved.

关键词： Nanocomposites

来源：评论

学校读者我要写书评

暂无评论

A Structure-Behavior Coalescence Process Algebra Approach to Unifying Multiple Views of a System

A Structure-Behavior Coalescence Process Algebra Approach to...

引用

IEEE Eurasia Conference on IOT, Communication and Engineering (ECICE)

作者： Hsien-Tzu Wang Wei-Ming Ma William S. Chao College of Management National Kaohsiung University of Science and Technology Kaohsiung Taiwan Math. and Phy. Group General Education Center R.O.C. Air Force Academy Kaohsiung Taiwan Dept. of Information Management National Sun Yat-sen University Kaohsiung Taiwan

We proposed a system metamodel called channel-based multi-queue structure-behavior coalescence process algebra (CM-SBC-PA). An example of a system metamodel using CM-SBC-PA and diagramming techniques was shown. CM-SBC-PA can be used as the basis for unifying multiple views of the system. Possible ways for CM-SBC-PA to project their views on the system are presented.

关键词：

来源：评论

学校读者我要写书评

暂无评论

Graph Fourier MMD for Signals on Graphs

arXiv

引用

arXiv 2023年

作者： Leone, Samuel Venkat, Aarthi Huguet, Guillaume Tong, Alexander Wolf, Guy Krishnaswamy, Smita Applied Math Program New HavenCT United States Computational Biology & Bioinformatics Program Yale University New HavenCT United States Dept. of Math. & Stat Université de Montréal Mila - Quebec AI Institute MontrealQC Canada Dept. of Comp. Sci. & Oper. Res. Université de Montréal Mila - Quebec AI Institute MontrealQC Canada Department of Computer Science Department of Genetics Yale University New HavenCT United States

While numerous methods have been proposed for computing distances between probability distributions in Euclidean space, relatively little attention has been given to computing such distances for distributions on graphs. However, there has been a marked increase in data that either lies on graph (such as protein interaction networks) or can be modeled as a graph (single cell data), particularly in the biomedical sciences. Thus, it becomes important to find ways to compare signals defined on such graphs. Here, we propose Graph Fourier MMD (GFMMD), a novel distance between distributions and signals on graphs. GFMMD is defined via an optimal witness function that is both smooth on the graph and maximizes difference in expectation between the pair of distributions on the graph. We find an analytical solution to this optimization problem as well as an embedding of distributions that results from this method. We also prove several properties of this method including scale invariance and applicability to disconnected graphs. We showcase it on graph benchmark datasets as well on single cell RNA-sequencing data analysis. In the latter, we use the GFMMD-based gene embeddings to find meaningful gene clusters. We also propose a novel type of score for gene selection called gene localization score which helps select genes for cellular state space characterization. Copyright © 2023, The Authors. All rights reserved.

关键词： Genes

来源：评论

学校读者我要写书评

暂无评论

Hierarchical Federated Learning based Anomaly Detection using digital twins for smart healthcare

arXiv

引用

arXiv 2021年

作者： Gupta, Deepti Kayode, Olumide Bhatt, Smriti Gupta, Maanak Tosun, Ali Saman Dept. of Computer Science University of Texas at San Antonio San AntonioTX78249 United States Dept. of Computer Science Frostburg State University FrostburgMD21532 United States Dept. of Computer and Information Technology Purdue University West LafayetteIN47907 United States Dept. of Computer Science Tennessee Technological University CookevilleTN38505 United States Dept. of Math. and Comp. Sci. University of North Carolina at Pembroke PembrokeNC28372 United States

Internet of Medical Things (IoMT) is becoming ubiquitous with a proliferation of smart medical devices and applications used in smart hospitals, smart-home based care, and nursing homes. It utilizes smart medical devices and cloud computing services along with core Internet of Things (IoT) technologies to sense patients' vital body parameters, monitor health conditions and generate multivariate data to support just-in-time health services. Mostly, this large amount of data is analyzed in centralized servers. Anomaly Detection (AD) in a centralized healthcare ecosystem is often plagued by significant delays in response time with high performance overhead. Moreover, there are inherent privacy issues associated with sending patients' personal health data to a centralized server, which may also introduce several security threats to the AD model, such as possibility of data poisoning. To overcome these issues with centralized AD models, here we propose a Federated Learning (FL) based AD model which utilizes edge cloudlets to run AD models locally without sharing patients' data. Since existing FL approaches perform aggregation on a single server which restricts the scope of FL, in this paper, we introduce a hierarchical FL that allows aggregation at different levels enabling multiparty collaboration. We introduce a novel disease-based grouping mechanism where different AD models are grouped based on specific types of diseases. Furthermore, we develop a new Federated Time Distributed (FEDTIMEDIS) Long Short-Term Memory (LSTM) approach to train the AD model. We present a Remote Patient Monitoring (RPM) use case to demonstrate our model, and illustrate a proof-of-concept implementation using Digital Twin (DT) and edge cloudlets. © 2021, CC BY.

关键词： Internet of things

来源：评论

学校读者我要写书评

暂无评论

Context matters for fairness - a case study on the effect of spatial distribution shifts

arXiv

引用

arXiv 2022年

作者： Ghodsi, Siamak Alani, Harith Ntoutsi, Eirini L3S Research Center Leibniz Universität Hannover Germany Freie Universität Berlin Dept. of Math. and Comp. Science Germany The Open University Milton Keynes United Kingdom

With the ever growing involvement of data-driven AI-based decision making technologies in our daily social lives, the fairness of these systems is becoming a crucial phenomenon. However, an important and often challenging aspect in utilizing such systems is to distinguish validity for the range of their application especially under distribution shifts, i.e., when a model is deployed on data with different distribution than the training set. In this paper, we present a case study on the newly released American Census datasets, a reconstruction of the popular Adult dataset, to illustrate the importance of context for fairness and show how remarkably can spatial distribution shifts affect predictive- and fairness-related performance of a model. The problem persists for fairness-aware learning models with the effects of context-specific fairness interventions differing across the states and different population groups. Our study suggests that robustness to distribution shifts is necessary before deploying a model to another context. © 2022, CC BY.

关键词： Spatial distribution

来源：评论

学校读者我要写书评

暂无评论

Wigner function of accelerated and non-accelerated Greenberger-Horne-Zeilinger State 8

Wigner function of accelerated and non-accelerated Greenberg...

引用

8th International Conference on Modeling Simulation and Applied Optimization, ICMSAO 2019

作者： Metwally, N. Abd-Rabbou, M.Y. Obada, A.-S.F. Ahmed, M.M.A. Math. Dept. College of Science University of Bahrain Bahrain Math. Dept. Faculty of Science Al-Azhar University Cairo Egypt

ISBN: (纸本)9781538676844

The Wigner function's behavior of accelerated and non-accelerated Greenberger-Horne-Zeilinger (GHZ) state is discussed. For the non-accelerated GHZ state, the minimum/maximum peaks of the Wigner function depends on the distribution's angles, where they are displayed regularly at fixed values of the distribution's angles. We show that, for the accelerated GHZ state, the minimum bounds increases as the acceleration increases. The increasing rate depends on the number of accelerated qubits. Due to the positivity/ negativity behavior of the Wigner function, one can use it as an indicators of the presences of the classical/quantum correlations, respectively. The maximum bounds of the quantum and the classical correlations depend on the purity of the initial GHZ state. The classical correlation that depicted by the behavior of Wigner function independent of the acceleration, but depends on the degree of its purity. © 2019 IEEE.

关键词： Wave functions

来源：评论

学校读者我要写书评

暂无评论

Brain Latent Progression: Individual-based Spatiotemporal Disease Progression on 3D Brain MRIs via Latent Diffusion

arXiv

引用

arXiv 2025年

作者： Puglisi, Lemuel Alexander, Daniel C. Ravì, Daniele Dept. of Math and Computer Science University of Catania Viale Andrea Doria 6 Catania Italy Centre for Medical Image Computing University College London 90 High Holborn London United Kingdom MIFT Department University of Messina Viale Ferdinando Stagno d’Alcontres 31 Messina Italy

The growing availability of longitudinal Magnetic Resonance Imaging (MRI) datasets has facilitated Artificial Intelligence (AI)-driven modeling of disease progression, making it possible to predict future medical scans for individual patients. However, despite significant advancements in AI, current methods continue to face challenges including achieving patient-specific individualization, ensuring spatiotemporal consistency, efficiently utilizing longitudinal data, and managing the substantial memory demands of 3D scans. To address these challenges, we propose Brain Latent Progression (BrLP), a novel spatiotemporal model designed to predict individual-level disease progression in 3D brain MRIs. The key contributions in BrLP are fourfold: (i) it operates in a small latent space, mitigating the computational challenges posed by high-dimensional imaging data;(ii) it explicitly integrates subject metadata to enhance the individualization of predictions;(iii) it incorporates prior knowledge of disease dynamics through an auxiliary model, facilitating the integration of longitudinal data;and (iv) it introduces the Latent Average Stabilization (LAS) algorithm, which (a) enforces spatiotemporal consistency in the predicted progression at inference time and (b) allows us to derive a measure of the uncertainty for the prediction. We train and evaluate BrLP on 11,730 T1-weighted (T1w) brain MRIs from 2,805 subjects and validate its generalizability on an external test set comprising 2,257 MRIs from 962 subjects. Our experiments compare BrLP-generated MRI scans with real follow-up MRIs, demonstrating state-of-the-art accuracy compared to existing methods. The code is publicly available at: https://***/LemuelPuglisi/BrLP. © 2025, CC BY.

关键词： Magnetic resonance imaging

来源：评论

学校读者我要写书评

暂无评论

Millimeter-Wave Radar-Based Unsteady Vital Signs Monitoring for Smart Home

Millimeter-Wave Radar-Based Unsteady Vital Signs Monitoring ...

引用

IEEE International Conference on Communications (ICC)

作者： Jinhong Zhang Jiefan Qiu Ke Wang Kai Fang Ali Kashif Bashir Wei Wang ZJUTDeus Robot Team College of Computer Sci. and Tech. Zhejiang Univ. of Tech. Hangzhou China School of Math. and Computer Sci. Zhejiang A&F Univ. Hangzhou China Dept. of Computing and Mathematics Manchester Metropolitan Univ. Manchester UK Guangdong-Hong Kong-Macao Joint Lab for Emotion Intelligence and Pervasive Computing Artificial Intelligence Research Institute Shenzhen MSU-BIT Univ. Shenzhen China

ISBN: (数字)9781728190549

ISBN: (纸本)9781728190556

The millimeter-wave(mm-Wave) radar based on frequency-modulated continuous wave (FMCW) owns the advantages of non-contact, privacy protection, high resolution, and anti-interference, and it became the hot point that applying the radar in monitoring vital signs for smart home. However, most of current studies focus on how to improve the detection performance under the steady scenarios and give little consideration on the unsteady scenarios with physical interference. In this paper, we propose a method to detect vital signs under unsteady scenarios by a best-effort way. This method automatically differentiates between the steady state and motion state (unsteady) by identifying the motion type, and extracts the vital sign under steady state without physical motion interference. For this end, we first figure out feature spectrograms with range-main velocity information from motion features. And then, employ a sliding windows sampling method to construct data set, and apply ResNet-18 network model in the motion type identification (including steady state). Based on the motion type, the phase signal during steady state and leverage the variational mode decomposition (VMD) algorithm to analyze respiration/heart rate. Experiment results show that using ResNet-18, the recognition accuracy of the motion state and motion type is close to 97%, and the recognition delay is less than 1.1s. Meanwhile, the mean absolute errors of the respiration rate and heart rate drop to 1.7bpm and 3.4bpm respectively.

关键词： Privacy Smart homes Interference Millimeter wave radar Sampling methods Steady-state Object recognition

来源：评论

学校读者我要写书评

暂无评论

Harmful information spreading and its impact on vaccination campaigns modeled through fractal-fractional operators

arXiv

引用

arXiv 2025年

作者： Akgül, Ali Usman, Auwalu Hamisu Conejero, J. Alberto Department of Electronics and Communication Engineering Saveetha School of Engineering SIMATS Tamilnadu Chennai India Siirt University Art and Science Faculty Department of Mathematics Siirt56100 Turkey Department of Computer Engineering Biruni University Topkapı Istanbul34010 Turkey Near East University Mathematics Research Center Department of Mathematics Near East Boulevard Nicosia/Mersin 10 MersinPC: 99138 Turkey Dept. Mathematics Faculty of Science King Mongkut’s University of Technology Thonburi Bangkok Thailand Bangkok10140 Thailand Dept. Math. Sci. Faculty of Physical Sciences Bayero University Kano Nigeria Instituto de Matemática Pura y Aplicada Universitat Politècnica de València Spain

Despite the huge efforts to develop and administer vaccines worldwide to copewith the COVID-19 pandemic, misinformation spreading through fake news in mediaand social networks about vaccination safety, make that people refuse to bevaccinated, which harms not only these people but also the whole population. In this work, we model the effects of harmful information spreading inimmunization acquisition through vaccination. Our model is posed for severalfractional derivative operators. We have conducted a comprehensive foundationanalysis of this model for the different fractional derivatives. Additionally,we have incorporated a strength parameter that shows the combined impact ofnonlinear and linear components within an epidemiological model. We have usedthe second derivative of the Lyapunov function to ascertain the detection ofwave patterns within the vaccination *** Codes 26A33, 34A08, 35R11 Copyright © 2025, The Authors. All rights reserved.

关键词： Fractals

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：