检索结果-内蒙古大学图书馆

Conference on Lasers and Electro-Optics (CLEO)

作者： Martin M. Stein Tatsuhiro Onodera Benjamin A. Ash Mandar M. Sohoni Melissa Bosch Ryotatsu Yanagimoto Marc Jankowski Timothy P. McKenna Tianyu Wang Gennady Shvets Maxim R. Shcherbakov Logan G. Wright Peter L. McMahon School of Applied and Engineering Physics Cornell University Ithaca NY USA NTT Physics and Informatics Laboratories NTT Research Inc. Sunnyvale CA USA E. L. Ginzton Laboratory Stanford University Stanford CA USA Department of Electrical Engineering and Computer Science UC Irvine Irvine CA USA Department of Applied Physics Yale University New Haven CT USA Kavli Institute at Cornell for Nanoscale Science Cornell University Ithaca NY USA

We introduce a device containing a planar waveguide whose spatial refractive index profile $n(x, z)$ can be programmed in real time. We demonstrate use this device as an optical neural network.

ISBN: (纸本)9798350369311

We introduce a device containing a planar waveguide whose spatial refractive index profile $n(x, z)$ can be programmed in real time. We demonstrate use this device as an optical neural network.

关键词： Optical planar waveguides Refractive index Waveguide lasers Optical fiber networks Optical variables control Real-time systems Planar waveguides System-on-chip Optical refraction Optical devices

来源：评论

学校读者我要写书评

暂无评论

Cutting-Edge Predictive Methods for Enhancing Short-Term Load Prediction

Cutting-Edge Predictive Methods for Enhancing Short-Term Loa...

引用

Electrical and computer engineering Researches (ICECER), International Conference on

作者： Taher M. Ghazal Jamshaid Iqbal Janjua Walid Abushiba Munir Ahmad Tahir Abbas Karamath Ateeq College of Arts & Science Applied Science University Manama Kingdom of Bahrain Center for Cyber Security Faculty of Information Science and Technology Universiti Kebangsaan Malaysia Bangi Selangor Malaysia Al-Khawarizimi Institute of Computer Science (KICS) University of Engineering & Technology (UET) Lahore Pakistan College of Engineering Applied Science University Bahrain College of Informatics Korea University Seoul Republic of Korea Department of Computer Science TIMES Institute Multan Pakistan School of Computing Skyline University College University City Sharjah Sharjah UAE

ISBN: (数字)9798331539733

ISBN: (纸本)9798331539740

Efficient management and cost-related factors in the power sector call for accurate short-term load forecasting as it enables better planning with the electric grid and achieving stability within it. This paper looks into the state-of-the-art forecasting strategies that enhance load forecasts made in shorter time frames. Such techniques include but are not limited to machine learning applications, effective data models, and multi-dimensional modeling leveraging historical, meteorological, and economic data. Their review is carried out in detail with their advantages and disadvantages and their application in practice. Furthermore, this study strives to understand the barriers that need to be overcome in the quest to increase the accuracy of the forecasting models especially concerning renewable energy sources. We illustrate how new trends relate to future developments of predictive models about supporting the decision-making in operating power systems and improving the reliability and sustainability of energy systems.

关键词： Renewable energy sources Accuracy Load forecasting Machine learning Predictive models Power system stability Data models Forecasting Sustainable development Load modeling

来源：评论

学校读者我要写书评

暂无评论

Deep and handcrafted feature supported diabetic retinopathy detection: A study

Deep and handcrafted feature supported diabetic retinopathy ...

引用

2022 International Conference on Machine Learning and Data engineering, ICMLDE 2022

作者： Kadry, Seifedine Crespo, Rubén González Herrera-Viedma, Enrique Krishnamoorthy, Sujatha Rajinikanth, Venkatesan Faculty of Applied Computing and Technology Noroff University College Kristiansand94612 Norway Computer Science Department School of Engineering and Technology Universidad Internacional de la Rioja Andalusia26006 Spain Research Institute in Data Science and Computational Intelligence University of Granada Granada Spain Zhejiang Bioinformatics International Science and Technology Cooperation Center Wenzhou-Kean University Zhejiang Province China Wenzhou Municipal Key Lab of Applied Biomedical and Biopharmaceutical Informatics Wenzhou-Kean University Zhejiang Province China Department of Electronics and Instrumentation Engineering St. Joseph's College of Engineering OMR Tamil Nadu Chennai600119 India

The eye is the prime sensory organ in physiology, and the abnormality in the eye severely influences the vision system. Therefore, eye irregularity is commonly assessed using imaging schemes, and Fundus Retinal Image (FRI) supported eye screening is one of the ophthalmological practices. This work proposed a Deep-Learning Procedure (DLP) to recognize Diabetic Retinopathy (DR) in FI. The proposed work presents the experimental work with different DLP methods found in the literature. This work is executed with two modes;(i) DR detection using conventional deep-features and (ii) DR discovery using deep ensemble features. To demonstrate this work, 1800 fundus images (900 regular and 900 DR class) are considered for the assessment, and the advantage of proposed plan is confirmed using various performance metrics. The experimental outcome of this study confirms that the AlexNet-based detection provides a better detection (>96%), and the deep ensemble features of AlexNet, VGG16, and ResNet18 provide a detection accuracy of >98% on the chosen FRI database. © 2022 Elsevier B.V.. All rights reserved.

关键词： Deep learning

来源：评论

学校读者我要写书评

暂无评论

Chaos and proportional integral derivative (PID) control on cancer dynamics with fractal fractional operator

Results in Engineering

引用

Results in engineering 2025年 26卷

作者： Farman, Muhammad Nisar, Kottakkaran Sooppy Jamil, Khadija Akgül, Ali Sambas, Aceng Bayram, Mustafa Habib, Mustafa Hassani, Murad Khan Faculty of Arts and Science Department of Mathematics Near East University Nicosia99138 Cyprus Faculty of Informatics and Computing Universiti Sultan Zainal Abidin Campus Besut Terengganu 22200 Malaysia Research Center of Applied Mathematics Khazar University Baku1096 Azerbaijan Department of Mathematics College of Science and Humanities in Alkharj Prince Sattam Bin Abdulaziz University Alkharj11942 Saudi Arabia Institute of Mathematics Khwaja Fareed University of Engineering and Information Technology Rahim Yar Khan Pakistan 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 Topkapi Istanbul34010 Turkey Near East University Mathematics Research Center Department of Mathematics Near East Boulevard Nicosia/Mersin 10 PC: 99138 Turkey Department of Mechanical Engineering Universitas Muhammadiyah Tasikmalaya Tamansari Gobras Tasikmalaya46196 Indonesia Department of Mathematics University of Engineering and Technology Lahore Pakistan Ghazni University Department of Mathematics Afghanistan Applied Science Research Center Applied Science Private University Amman11937 Jordan

This study presents a cancer dynamics model incorporating a fractal-fractional operator with a Mittag-Leffler kernel to capture complex interactions among cancer cells, tumor suppressor cells, immune cells, and oncolytic viruses. The model aims to enhance understanding of tumor-immune dynamics and improve treatment strategies. The existence and uniqueness of the solution are established using fixed point theory under the Lipschitz condition. Lyapunov stability of the system is also analyzed in the context of the fractal-fractional operator. To address chaotic behavior in cancer progression, chaos and Proportional-Integral-Derivative (PID) control techniques are implemented. These control methods effectively stabilize the system and regulate treatment administration. Numerical simulations illustrate the influence of fractional-order derivatives on tumor suppression and immune response, confirming the model's effectiveness in reflecting real-world cancer dynamics. © 2025 The Author(s)

关键词： Fractals

来源：评论

学校读者我要写书评

暂无评论

Mechanically Laser-Induced Acoustic Cavitation in Viscoelastic Tissue: Theoretical Study

引用

Bulletin of the Russian Academy of Sciences: Physics 2023年第Suppl 3期87卷 S348-S355页

作者： Zain Abu Shaeer Amerah M. Hakami Abu-Bakr, Ali F. Ahmed K. Abu-Nab Department of Basic Science Higher Institute of Engineering and Technology Kafrelsheikh33511 Egypt Department of Mathematics Faculty of Science Jazan University Jazan82723 Saudi Arabia Department of Mathematics and Computer Science Faculty of Science Menoufia University Shebin El-Koom32511 Egypt Phystech School of Applied Mathematics and Informatics Moscow Institute of Physics and Technology Moscow oblast Dolgoprudny141700 Russia

Abstract: Laser-induced acoustic cavitation microbubble dynamics have exhibited significant development in biological systems such as lithotripsy. Investigating the mechanically laser-induced acoustic cavitation microbubble in viscoelastic tissue is the goal of this work. Based on surface tension and viscous forces, the laser-induced cavitation model (also known as the modified Rayleigh–Plesset model), the theoretical model is developed and numerically solved using exponential cubic B-spline Collocation Method. In addition, the energy released in viscoelastic tissue by laser-induced acoustic cavitation as well as mechanically induced cavitation is investigated. The findings of our work provide valuable insight into the application of laser-induced acoustic cavitation microbubbles such as kidney stones and lithotripsy. © Pleiades Publishing, Ltd. 2023. ISSN 1062-8738, Bulletin of the Russian Academy of Sciences: Physics, 2023, Vol. 87, Suppl. 3, pp. S348–S355. Pleiades Publishing, Ltd., 2023. ISSN 1062-8738, Bulletin of the Russian Academy of Sciences: Physics, 2023. Pleiades Publishing, Ltd., 2023.

关键词： Tissue

来源：评论

学校读者我要写书评

暂无评论

RERRFACT: Reduced Evidence Retrieval Representations for Scientific Claim Verification

arXiv

引用

arXiv 2022年

作者： Rana, Ashish Khanna, Deepanshu Ghosal, Tirthankar Singh, Muskaan Singh, Harpreet Rana, Prashant Singh School of Business Informatics and Mathematics University of Mannheim Germany Department of Electronics & Communication Engineering Thapar Institute of Engineering & Technology India Institute of Formal and Applied Linguistics Faculty of Mathematics and Physics Charles University Czech Republic Department of Computer Science & Engineering Thapar Institute of Engineering & Technology India

Exponential growth in digital information outlets and the race to publish has made scientific misinformation more prevalent than ever. However, the task to fact-verify a given scientific claim is not straightforward even for researchers. Scientific claim verification requires in-depth knowledge and great labor from domain experts to substantiate supporting and refuting evidence from credible scientific sources. The SCIFACT dataset and corresponding task provide a benchmarking leaderboard to the community to develop automatic scientific claim verification systems via extracting and assimilating relevant evidence rationales from source abstracts. In this work, we propose a modular approach that sequentially carries out binary classification for every prediction subtask as in the SCIFACT leaderboard. Our simple classifier-based approach uses reduced abstract representations to retrieve relevant abstracts. These are further used to train the relevant rationale-selection model. Finally, we carry out two-step stance predictions that first differentiate non-relevant rationales and then identify supporting or refuting rationales for a given claim. Experimentally, our system RERRFACT with no fine-tuning, simple design, and a fraction of model parameters fairs competitively on the leaderboard against large-scale, modular, and joint modeling approaches. We make our codebase available at https://***/ashishrana160796/RerrFact. © 2022, CC BY.

关键词：

来源：评论

学校读者我要写书评

暂无评论

Spatial Adaptive Cooperative Graph Convolution Attention for Person Re-Identification

SSRN

引用

SSRN 2023年

作者： Xiong, Mingfu Xiong, Jiefan Wang, Zhongyuan Chen, Jia Hu, Ruimin Muhammad, Khan Xiong, Zixiang School of Computer Science and Artificial Intelligence Wuhan Textile University Wuhan430200 China Wuhan University Wuhan430072 China Department of Applied Artificial Intelligence School of Convergence College of Computing and Informatics Sungkyunkwan University Seoul03063 Korea Republic of The Department of Electrical and Computer Engineering Texas A&M University College StationTX7784 United States

Recently, person re-identification (person Re-ID) equipped with attention mechanism (AM) has gradually emerged as one of the prevalent study highlights. In fact, the existing attention-based methods still remain the challenges for recognizing the different persons with similar appearances in the unpredictable realistic environments: (1) the adaptability of the learned a single and local attention to the hostile scenes cannot be guaranteed;(2) most existing methods originated from the attention features usually try to find a simple linear transformation, which is easy to lost the function of distinguishing different pedestrians with similar appearance attributes. To tackle these issues, this paper proposed a spatial adaptive cooperative graph convolution attention (SACGCA) method to excavate the relevances of individual body local regions for each person. The proposed framework encompasses a dual-attention mechanism model (DAMM) and a spatial adaptive graph convolution model (SAGCM). In particular, the DAMM consists of the multi-region (local and global) association structure and a feature channel attention network to extract person features. Then, the SAGCM is primed for constructing the spatial nonlinear transformation relationships among the various body regions for each person by the virtue of graph optimization. Extensive experiments have conducted on the person Re-ID public datasets (Market-1501, DukeMTMC-reid and CUHK-03), which results indicate that the performance of our proposed algorithm is better than existing methods by 2%, 2%, 10% at Rank-1 or mAP respectively. © 2023, The Authors. All rights reserved.

关键词： Convolution

来源：评论

学校读者我要写书评

暂无评论

Position: Bayesian Deep Learning is Needed in the Age of Large-Scale AI 41

Position: Bayesian Deep Learning is Needed in the Age of Lar...

引用

41st International Conference on Machine Learning, ICML 2024

作者： Papamarkou, Theodore Skoularidou, Maria Palla, Konstantina Aitchison, Laurence Arbel, Julyan Dunson, David Filippone, Maurizio Fortuin, Vincent Hennig, Philipp Hernández-Lobato, José Miguel Hubin, Aliaksandr Immer, Alexander Karaletsos, Theofanis Khan, Mohammad Emtiyaz Kristiadi, Agustinus Li, Yingzhen Mandt, Stephan Nemeth, Christopher Osborne, Michael A. Rudner, Tim G.J. Rügamer, David Teh, Yee Whye Welling, Max Wilson, Andrew Gordon Zhang, Ruqi Department of Mathematics The University of Manchester Manchester United Kingdom Eric and Wendy Schmidt Center Broad Institute of MIT and Harvard Cambridge United States Spotify London United Kingdom Computational Neuroscience Unit University of Bristol Bristol United Kingdom Centre Inria de l'Université Grenoble Alpes Grenoble France Department of Statistical Science Duke University United States Statistics Program KAUST Saudi Arabia Helmholtz AI Munich Germany Department of Computer Science Technical University of Munich Munich Germany Munich Center for Machine Learning Munich Germany Tübingen AI Center University of Tübingen Tübingen Germany Department of Engineering University of Cambridge Cambridge United Kingdom Department of Mathematics University of Oslo Oslo Norway Bioinformatics and Applied Statistics Norwegian University of Life Sciences Ås Norway Department of Computer Science ETH Zurich Switzerland Chan Zuckerberg Initiative CA United States Center for Advanced Intelligence Project RIKEN Tokyo Japan Vector Institute Toronto Canada Department of Computing Imperial College London London United Kingdom Department of Computer Science UC Irvine Irvine United States Department of Mathematics and Statistics Lancaster University Lancaster United Kingdom Department of Engineering Science University of Oxford Oxford United Kingdom Center for Data Science New York University New York United States Department of Statistics LMU Munich Munich Germany DeepMind London United Kingdom Department of Statistics University of Oxford Oxford United Kingdom Informatics Institute University of Amsterdam Amsterdam Netherlands Courant Institute of Mathematical Sciences Center for Data Science Computer Science Department New York University New York United States Department of Computer Science Purdue University West Lafayette United States

In the current landscape of deep learning research, there is a predominant emphasis on achieving high predictive accuracy in supervised tasks involving large image and language datasets. However, a broader perspective reveals a multitude of overlooked metrics, tasks, and data types, such as uncertainty, active and continual learning, and scientific data, that demand attention. Bayesian deep learning (BDL) constitutes a promising avenue, offering advantages across these diverse settings. This paper posits that BDL can elevate the capabilities of deep learning. It revisits the strengths of BDL, acknowledges existing challenges, and highlights some exciting research avenues aimed at addressing these obstacles. Looking ahead, the discussion focuses on possible ways to combine large-scale foundation models with BDL to unlock their full potential. Copyright 2024 by the author(s)

关键词： Contrastive Learning

来源：评论

学校读者我要写书评

暂无评论

Observation of Su-Schrieffer-Heeger Topological Model Band Structure in Integrated LNOI Coupled Ring Cavities

Observation of Su-Schrieffer-Heeger Topological Model Band S...

引用

Pacific Rim Conference on Lasers and Electro-Optics (CLEO/Pacific Rim)

作者： Hiep X. Dinh Armandas Balcytis Tomoki Ozawa Yasutomo Ota Toshihiko Baba Satoshi Iwamoto Arnan Mitchell Thach G. Nguyen Integrated Photonics and Applications Centre RMIT University Melbourne VIC Australia Advanced Institute for Materials Research Tohoku University Sendai Japan Department of Applied Physics and Physico-Informatics Keio University Yokohama Japan Department of Electrical and Computer Engineering Yokohama National University Yokohama Japan Research Center for Advanced Science and Technology The University of Tokyo Tokyo Japan

We report synthetic frequency dimension Su-Schrieffer-Heeger model and its band structure observation using coupled ring cavities on an integrated photonic chip. Intra-cell and inter-cell couplings between hybridized ... 详细信息

ISBN: (数字)9798350372076

ISBN: (纸本)9798350372083

关键词： Structural rings Band structures Couplings Frequency modulation Scalability Electro-optic modulators Ring lasers

来源：评论

学校读者我要写书评

暂无评论

The dynamics simulation of knowledge potentials of agents including the feedback 12

The dynamics simulation of knowledge potentials of agents in...

引用

12th International Conference on Mathematics, Science and Technology Education, ICon-MaSTEd 2020

作者： Pasichnyk, V.V. Bomba, A.Y. Nazaruk, M.V. Kunanets, N.E. Information Systems and Networks Department Lviv Polytechnic National University 12 Bandera Str. Lviv79000 Ukraine Computer Science and Applied Mathematics Department National University of Water and Environmental Engineering 11 Soborna Str. Rivne33028 Ukraine Informatics and Applied Mathematics Department Rivne State Humanitarian University 31 Plastova Str. Rivne33000 Ukraine

The conceptual and mathematical models of the agents' knowledge potential redistribution considering their constituent components are constructed in the paper. A nonlinear model describing the dynamics of agents' knowledge potentials is developed taking into account the feedback effects (agent-student) on the source of knowledge (teacher / lecturer). In particular, the procedure of constructing a multicomponent two-dimensional array of discrete values of the knowledge potential constituent components for generating procedures to enhance (improve) the professional competences of knowledge sources, is generalized and specified. © 2021 Published under licence by IOP Publishing Ltd.

关键词：

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：