检索结果-内蒙古大学图书馆

Optimal cavity design for minimizing errors in cavity-QED-based atom-photon entangling gates with finite temporal duration

引用

Physical Review A 2025年第1期111卷 L011701-L011701页

作者： Takeru Utsugi Rui Asaoka Yuuki Tokunaga Takao Aoki Department of Applied Physics Waseda University 3-4-1 Okubo Shinjuku-ku Tokyo 169-8555 Japan Computer & Data Science Laboratories NTT Corporation Musashino Tokyo 180-8585 Japan

We investigate atom-photon entangling gates based on cavity quantum electrodynamics (QED) for a finite photon-pulse duration, where not only the photon loss but also the temporal mode-mismatch of the photon pulse becomes a severe source of error. We analytically derive relations between cavity parameters, including transmittance, length, and effective cross-sectional area of the cavity, that minimize both the photon loss probability and the error rate due to temporal mode-mismatch by taking it into account as state-dependent pulse delay. We also investigate the effects of pulse distortion using numerical simulations for the case of short pulse duration. We believe that these analyses are the first to suggest that a cavity has an optimal length for the atom-photon gate, providing a fundamental guideline for implementing quantum information processing.

关键词： Atoms

来源：评论

学校读者我要写书评

暂无评论

Millibots: Integrating Deep Learning Algorithms for Autonomous Control in Small-Scale Robotics 15

Millibots: Integrating Deep Learning Algorithms for Autonomo...

引用

15th International Conference on Computing Communication and Networking Technologies, ICCCNT 2024

作者： Sneha, A. Angel Diwan, B. Stella Maris College Of Engineering Artificial Intelligence and Data Science Department Nagercoil India Joesphs College Of Engineering Department of Computer Science St Chennai India

ISBN: (纸本)9798350370249

Millibots, miniature robotic platforms, have emerged as pivotal tools in various domains, ranging from medical interventions to environmental monitoring. However, their diminutive size presents formidable challenges in achieving autonomous navigation and control. In this paper, we delve into the realm of millibots and propose a groundbreaking approach to tackle these challenges by integrating deep learning algorithms for autonomous control. Leveraging the power of deep learning, we address the intricate interplay between perception, decision-making, and locomotion in small-scale robotics. Our methodology not only overcomes the limitations inherent to millibots but also unlocks new frontiers in their application. Through a comprehensive review of related work, meticulous experimentation, and insightful analysis, we demonstrate the unparalleled efficacy of our approach. This paper not only accelerates the advancement of small-scale robotics but also envisions a new era of autonomous exploration and innovation. © 2024 IEEE.

关键词： Motion planning

来源：评论

学校读者我要写书评

暂无评论

Deep Learning Classification Techniques on Detecting Diabetic Retinopathy dataset 7

Deep Learning Classification Techniques on Detecting Diabeti...

引用

7th International Conference on Inventive Computation Technologies, ICICT 2024

作者： Revathi, B. Usharani, C. Kezial Elizabeth, S.K. Nagaraj, P. Nithya, D. Ramco Institute of Technology Department of Artificial Intelligence And Data Science Virudhunagar India Mangayarkarasi College of Engineering Department of Computer Science And Engineering Madurai India Kalasalingam Academy of Research And Education Department of Computer Science And Engineering Virudhunagar Krishnankoil India Theni Kammavar Sangam College of Technology Department of Computer Science And Engineering Theni India

ISBN: (纸本)9798350359299

Deep learning algorithms can summarize images to understand how to carry out necessary tasks. The purpose of this study is to compare several deep learning methods. Both experience-based and explanation-based learning are possible in deep learning. The most widely utilized algorithms, such as Convolutional Neural Networks (CNN), Multilayer Perceptron (MLP), Generative Adversarial Networks (GAN), Radial Basis Function Networks (RBFN), and Deep Belief Networks (DBN), and the Diabetic Retinopathy dataset is utilized in this study to evaluate the effectiveness of the algorithms. A comparative study of the classifiers reveals that CNN performs more accurately than the other approaches. © 2024 IEEE.

关键词： Classification (of information)

来源：评论

学校读者我要写书评

暂无评论

Optimizing Hospital Patient Flow by Predicting Aftercare Requests from Fuzzy Time Series 29th

Optimizing Hospital Patient Flow by Predicting Aftercare Re...

引用

29th International Conference on Cooperative Information Systems, CoopIS 2023

作者： M. de Carvalho, Renata van der Sommen, Stef F. de Carvalho, Danilo Department of Mathematics and Computer Science Eindhoven University of Technology Eindhoven Netherlands Jheronimus Academy of Data Science Eindhoven University of Technology Eindhoven Netherlands

ISBN: (纸本)9783031468452

Predictive modelling can be a huge benefit when it comes to optimizing patient flows in a hospital. Hospital beds are considered critical resources, thus the need for optimizing patient flow is evident. This paper focuses on predicting the out-flow of hospital patients to external aftercare facilities, to mitigate the waiting times that currently dominate this flow and have a negative influence on the patient recovery process. In order to achieve this, we analyze hospital patient time series data in the form of aftercare requests. Such predictions allow hospital and aftercare facilities to be aligned such that, as soon as a patient is medically ready for discharge, the aftercare facility can immediately allocate the patient, avoiding for such patient to stay longer in the hospital occupying a bed while waiting for a place in the aftercare facility. © 2024, The Author(s), under exclusive license to Springer Nature Switzerland AG.

关键词： Time series

来源：评论

学校读者我要写书评

暂无评论

Cryptocurrency Forecasting using Financial Indicators 15

Cryptocurrency Forecasting using Financial Indicators

引用

15th International Conference on Computing Communication and Networking Technologies, ICCCNT 2024

作者： Deb, Sagar Sankhe, Atharva Dalvi, Indrajit Vartak, Pooja Dwarkadas J. Sanghvi College of Engineering Department of Computer Engineering and Data Science Mumbai India

ISBN: (纸本)9798350370249

With the rise of digital financial systems, cryptocurrencies have become a prime example of blockchain's potential. This paper presents a deep learning approach targeting the time series data of Bitcoin, which is known for its high volatility. By implementing a long short-term memory (LSTM) model, this study aims to capture the underlying trends in cryptocurrency pricing for future price prediction. © 2024 IEEE.

关键词： Decentralized finance

来源：评论

学校读者我要写书评

暂无评论

ABLE: Personalized Disability Support with Politeness and Empathy Integration

ABLE: Personalized Disability Support with Politeness and Em...

引用

2024 Conference on Empirical Methods in Natural Language Processing, EMNLP 2024

作者： Mishra, Kshitij Burja, Manisha Ekbal, Asif Department of Computer Science and Engineering Indian Institute of Technology Patna India School of AI and Data Science Indian Institute of Technology Jodhpur India

ISBN: (纸本)9798891761643

In today's dynamic world, providing inclusive and personalized support for individuals with physical disabilities is imperative. With diverse needs and preferences, tailored assistance according to user personas is crucial. In this paper, we introduce ABLE (Adaptive, Bespoke, Listen and Empathetic), a Conversational Support System for Physical Disabilities. By tracking user personas, including gender, age, and personality traits based on the OCEAN model, ABLE ensures that support interactions are uniquely tailored to each user's characteristics and preferences. Moreover, integrating politeness and empathy levels in responses enhances user satisfaction and engagement, fostering a supportive and respectful environment. The development of ABLE involves compiling a comprehensive conversational dataset enriched with user profile annotations. Leveraging reinforcement learning techniques and diverse reward mechanisms, ABLE trains a model to generate responses aligned with individual user profiles while maintaining appropriate levels of politeness and empathy. Based on rigorous empirical analysis encompassing automatic and human evaluation metrics based on persona-consistency, politeness accuracy, empathy accuracy, perplexity, and conversation coherence, the efficacy of ABLE is assessed. Our findings underscore ABLE's success in delivering tailored support to individuals grappling with physical disabilities. To the best of our knowledge, this is the very first attempt towards building a user's persona-oriented physical disability support system. © 2024 Association for Computational Linguistics.

关键词： Computational linguistics

来源：评论

学校读者我要写书评

暂无评论

Privacy Preserving data Imputation via Multi-party Computation for Medical Applications

Privacy Preserving Data Imputation via Multi-party Computati...

引用

2024 IEEE International Conference on E-Health Networking, Application and Services, HealthCom 2024

作者： Jentsch, Julia Ünal, Ali Burak Mağara, Şeyma Selcan Akgün, Mete Department of Computer Science Medical Data Privacy and Privacy Preserving Machine Learning Tübingen Germany

ISBN: (数字)9798350350548

ISBN: (纸本)9798350350548

Handling missing data is crucial in machine learning, but many datasets contain gaps due to errors or non-response. Unlike traditional methods such as listwise deletion, which are simple but inadequate, the literature offers more sophisticated and effective methods, thereby improving sample size and accuracy. However, these methods require accessing the whole dataset, which contradicts the privacy regulations when the data is distributed among multiple sources. Especially in the medical and healthcare domain, such access reveals sensitive information about patients. This study addresses privacy-preserving imputation methods for sensitive data using secure multi-party computation, enabling secure computations without revealing any party’s sensitive information. In this study, we realized the mean, median, regression, and kNN imputation methods in a privacy-preserving way. We specifically target the medical and healthcare domains considering the significance of protection of the patient data, showcasing our methods on a diabetes dataset. Experiments on the diabetes dataset validated the correctness of our privacy-preserving imputation methods, yielding the largest error around 3 × 10-3, closely matching plaintext methods. We also analyzed the scalability of our methods to varying numbers of samples, showing their applicability to real-world healthcare problems. Our analysis demonstrated that all our methods scale linearly with the number of samples. Except for kNN, the runtime of all our methods indicates that they can be utilized for large datasets. © 2024 IEEE.

关键词： Differential privacy

来源：评论

学校读者我要写书评

暂无评论

Localization and Local Motion Magnification of Pulsatile Regions in Endoscopic Surgery Videos 1

引用

30th International Conference on MultiMedia Modeling, MMM 2024

作者： Zheng, Honglei Fan, Wenkang Chen, Yinran Luo, Xiongbiao Department of Computer Science and Technology Xiamen University Xiamen China National Institute for Data Science in Health and Medicine Xiamen University Xiamen China

ISBN: (数字)9783031533112

ISBN: (纸本)9783031533105

Localization of neurovascular bundles or vessels is critical in endoscopic surgery. It still remains challenging to identify neurovascular bundles and vessels due to limited field-of-view and tactile perception loss. This paper presents a new framework for local motion magnification of the pulsatile region in endoscopic surgical videos, which can help surgeons localize these pulsatile regions from complex surgical fields. Our method consists of an autocorrelated dynamic linear model, a pulsatile region localization module, and a local motion magnification module. Specifically, the autocorrelated dynamic linear model and pulsatile region localization module can extract periodic features and position information of pulsatile regions. Then, the local motion magnification module performs local motion magnification, minimizing post-magnification artifacts. Importantly, our method also avoids distorting the surgical instruments during magnification. Experimental validations on both synthetic and clinical surgical videos demonstrate that our method outperforms the existing methods in both qualitative and quantitative assessments. © 2024, The Author(s), under exclusive license to Springer Nature Switzerland AG.

关键词： Endoscopy

来源：评论

学校读者我要写书评

暂无评论

A Deterministic Search Approach for Solving Stochastic Drone Search and Rescue Planning Without Communications 17th

A Deterministic Search Approach for Solving Stochastic Drone...

引用

17th International Symposium on Combinatorial Search, SoCS 2024

作者： Mishlyakov, Evgeny Gruntov, Mikhail Shleyfman, Alexander Karpas, Erez Faculty of Data and Decision Sciences Technion Israel Department of Computer Science Bar-Ilan University Israel

ISBN: (纸本)9781577358916

In disaster relief efforts, delivering aid to areas with no communication poses a significant challenge. Unmanned aerial vehicles (UAVs) can be utilized to deliver aid kits to survivors in hard-to-reach areas;unfortunately, in some areas, lack of communication and infrastructure presents a key problem. In this paper, we address a stochastic planning problem of planning for a set of UAVs that deliver aid kits to areas that lack communications, where we do not know in advance the locations where aid kits need to be delivered, but rather have probabilistic information about the locations of aid targets. Our main insight is that, despite the stochastic nature of this problem, we can solve it through deterministic search by monitoring the expected reward for each partial solution. This insight enables the application of deterministic planning techniques, empirically demonstrating a notable improvement in efficiency and response speed. Our approach presents a promising solution to addressing the challenge of delivering aid in regions with limited radio infrastructure, as well as similar planning problems. © 2024, Association for the Advancement of Artificial Intelligence (***). All rights reserved.

关键词： Drones

来源：评论

学校读者我要写书评

暂无评论

Variational quantum neural network with optimized ansatz for predicting malignant ventricular arrhythmias 9th

Variational quantum neural network with optimized ansatz for...

引用

9th International Conference on computer science and Computational Intelligence, ICCSCI 2024

作者： Dominic, Nicholas Pardamean, Bens Bioinformatics and Data Science Research Center Bina Nusantara University Jakarta11480 Indonesia Computer Science Department BINUS Graduate Program Computer Science Program Bina Nusantara University Jakarta11480 Indonesia

Preventive strategies should be the utmost priority when dealing with diverse patients suffering from malignant ventricular arrhythmia (MVA) that can lead to sudden cardiac death (SCD). Electrocardiogram (ECG) data is commonly used as a predictor for MVA predictive models. In this study, all ECG signals from MIT-BIH databases were fragmented into five-minute durations with a frequency sampling of 128 Hz. To solve the absence of hybrid optimizations in Machine Learning (ML) models, a novel Variational Quantum Neural Network (VQNN) was invented. Empowered by deep learning capabilities and optimized quantum circuits design, VQNN achieved remarkable performances designated by an accuracy of up to 95.1%, a perfect 100% recall, and a 95.2% score of the area under the Receiver Operating Characteristic curve (AUC ROC) with Conjugate Gradient as an optimizer and EfficientSU2 as a quantum ansatz. Despite the susceptibility to quantum noise, this research settles a new trajectory of utilizing quantum variational algorithms to predict and expand its applicability for MVA cases. © 2024 The Authors.

关键词： Quantum computers

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：