检索结果-内蒙古大学图书馆

International Conference on Communications and Signal Processing

作者： S. Aghalya R. Sarasu Nilamadhab Mishra G. Arunachalam D. Gobinath Suresh Babu Thandullu Naganathan Department of Electronics and Communication Engineering St. Joseph’s College of Engineering OMR Chennai Tamil Nadu India Department of Spatial Informatics Saveetha School of Engineering Saveetha Institute of Medical and Technical Sciences Saveetha University Chennai Tamil Nadu India School of Computing Science and Engineering VIT Bhopal University Madhya Pradesh India Department of Electronics and Communication Engineering Gnanamani College of Technology (Autonomous) Namakkal Tamil Nadu India Department of Computer Science and Engineering Rajalakshmi Institute of Technology Chennai Tamil Nadu India Department of Electronics and Communication Engineering Adhiparasakthi Engineering College Melmaruvathur Tamil Nadu India

ISBN: (数字)9798350353068

ISBN: (纸本)9798350353075

The study presents an advanced neural network model for real-time remote evaluation and treatment of rheumatic diseases using sensor fusion. The model was developed for use in this investigation. The suggested system uses a wide variety of sensing modalities, such as image, motion, and biometric sensors. This is accomplished via artificial intelligence (AI) and the data gleaned from sensors. The neural network, which was trained on a dataset that was both varied and labeled, performs autonomous analyses of input data in order to accurately predict and categorize rheumatic diseases. The integration of the model into remote medical treatment is made easier by the fact that it is run on a Raspberry Pi inside a tele-rheumatology framework. This unique strategy not only improves diagnostic accuracy but also expands rheumatology services to geographically inaccessible or disadvantaged groups. As a result, the landscape of rheumatic healthcare delivery is completely transformed as a result of this new approach. For the purpose of ensuring the ethical use of this revolutionary technology, the procedures for data security and ethical concerns have been given priority.

关键词： Ethics Technological innovation Biological system modeling Neural networks Medical treatment Signal processing Sensor fusion

来源：评论

学校读者我要写书评

暂无评论

CCGRID 2023: A Holistic Approach to Inclusion and Belonging

CCGRID 2023: A Holistic Approach to Inclusion and Belonging

引用

IEEE/ACM International Symposium on Cluster computing and the Grid (CCGRID)

作者： Beth Plale Preeti Malakar Meenakshi D'Souza Hemangee K. Kapoor Yogesh Simmhan Ilkay Altintas Manohar Swaminathan School of Informatics Computing and Engineering Indiana University Bloomington IN USA Department of Computer Science and Engineering Indian Institute of Technology Kanpur Kalyanpur Kanpur India International Institute of Information Technology Bangalore Bengaluru Karnataka India Department of Computer Science and Engineering Indian Institute of Technology Guwahati Guwahati Assam India Department of Computational and Data Sciences Indian Institute of Science Bangalore India San Diego Supercomputer Center University of California San Diego MC USA Microsoft Research Lab - India Bengaluru Karnataka India

“CCGRID will act with responsibility as its primary consideration; with equity, diversity, and inclusion as its central goals.” from the CCGRID 2023 web site [1]

关键词：

来源：评论

学校读者我要写书评

暂无评论

Smart Donations: Event-Driven Conditional Donations Using Smart Contracts On The Blockchain 20

Smart Donations: Event-Driven Conditional Donations Using Sm...

引用

Proceedings of the 32nd Australian Conference on Human-Computer Interaction

作者： Ludwig Trotter Mike Harding Peter Shaw Nigel Davies Chris Elsden Chris Speed John Vines Aydin Abadi Josh Hallwright School of Computing and Communications Lancaster University United Kingdom Design Informatics University of Edinburgh United Kingdom Northumbria University United Kingdom School of Business and Technology University of Gloucestershire United Kingdom Oxfam Australia and RMIT University Australia

ISBN: (纸本)9781450389754

Recent work has questioned the largely unconditional nature of charitable donations and explored the value of conditional giving with contemporary donors. In this paper, we extend this work by exploring how to operationalise features of conditionality in charitable giving, situated in the context of large international non-governmental organisations (NGOs). Building on prior engagements with international aid organisations, we present design considerations and a conceptual architecture supporting real-time, conditional giving for individual and institutional donations. Our architecture leverages properties of distributed-ledger technologies (DLT) to empower donors to (i) attach conditions to their donation, (ii) store funds in a secure, decentralised escrow and (iii) automatically release funds once conditions are met. Unlike prior work that envisions radical disintermediation and the removal of intermediate NGOs using DLT, our work recognises the expertise of NGOs in tackling complex global problems and instead investigates compelling new way for charities to increase transparency and accountability by introducing dynamic pledge controls.

关键词： Blockchain conditionality charitable giving even-driven computing

来源：评论

学校读者我要写书评

暂无评论

Embedding-aided network dismantling

arXiv

引用

arXiv 2022年

作者： Osat, Saeed Papadopoulos, Fragkiskos Teixeira, Andreia Sofia Radicchi, Filippo Göttingen37077 Germany Department of Electrical Engineering Computer Engineering and Informatics Cyprus University of Technology 33 Saripolou Street Limassol3036 Cyprus LASIGE Departamento de Informática Faculdade de Ciências Universidade de Lisboa Lisboa1749-016 Portugal Center for Complex Networks and Systems Research Luddy School of Informatics Computing and Engineering Indiana University BloomingtonIN47408 United States

Optimal percolation concerns the identification of the minimum-cost strategy for the destruction of any extensive connected components in a network. Solutions of such a dismantling problem are important for the design of optimal strategies of disease containment based either on immunization or social distancing. Depending on the specific variant of the problem considered, network dismantling is performed via the removal of nodes or edges, and different cost functions are associated to the removal of these microscopic elements. In this paper, we show that network representations in geometric space can be used to solve several variants of the network dismantling problem in a coherent fashion. Once a network is embedded, dismantling is implemented using intuitive geometric strategies. We demonstrate that the approach well suits both Euclidean and hyperbolic network embeddings. Our systematic analysis on synthetic and real networks demonstrates that the performance of embedding-aided techniques is comparable to, if not better than, the one of the best dismantling algorithms currently available on the market. Copyright © 2022, The Authors. All rights reserved.

关键词： Cost functions

来源：评论

学校读者我要写书评

暂无评论

Entanglement-assisted phase estimation algorithm for calculating dynamical response functions

arXiv

引用

arXiv 2024年

作者： Sakuma, Rei Kanno, Shu Sugisaki, Kenji Abe, Takashi Yamamoto, Naoki Materials Informatics Initiative RD Technology & Digital Transformation Center JSR Corporation 3-103-9 Tonomachi Kawasaki-ku Kawasaki210-0821 Japan Quantum Computing Center Keio University 3-14-1 Hiyoshi Kohoku-ku Yokohama223-8522 Japan Mitsubishi Chemical Corporation Science & Innovation Center Yokohama227-8502 Japan Graduate School of Science and Technology Keio University 7-1 Shinkawasaki Saiwai-ku Kanagawa Kawasaki212-0032 Japan Centre for Quantum Engineering Research and Education TCG Centres for Research and Education in Science and Technology Sector V Salt Lake Kolkata700091 India Department of Applied Physics and Physico-Informatics Keio University 3-14-1 Hiyoshi Kohoku-ku Yokohama223-8522 Japan

Dynamical response functions are fundamental quantities to describe the excited-state properties in quantum many-body systems. Quantum algorithms have been proposed to evaluate these quantities by means of quantum phase estimation (QPE), where the energy spectra are directly extracted from the QPE measurement outcomes in the frequency domain. Accurate estimation of excitation energies and transition probabilities with these QPE-based approaches is, however, challenging because of the problem of spectral leakage (or peak broadening) which is inherent in the QPE algorithm. To overcome this issue, in this work we consider an extension of the QPE-based approach adopting the optimal entangled input states, which is known to achieve the Heisenberg-limited scaling for the estimation precision. We show that with this method the peaks in the calculated energy spectra are more localized than those calculated by the original QPE-based approaches, suggesting the mitigation of the spectral leakage problem. By analyzing the probability distribution with the entangled phase estimation, we propose a simple scheme to better estimate both the transition energies and the corresponding transition probabilities of the peaks of interest in the spectra. The validity of our prescription is demonstrated by numerical simulations in various quantum many-body problems: the spectral function of a simple electron-plasmon model in condensed-matter physics, the dipole transitions of the H2O molecule in quantum chemistry, and the electromagnetic transitions of the 6Li nucleus in nuclear physics. © 2024, CC BY-NC-ND.

关键词： Quantum chemistry

来源：评论

学校读者我要写书评

暂无评论

Skeleton structure inherent in discrete-time quantum walks

arXiv

引用

arXiv 2022年

作者： Yamagami, Tomoki Segawa, Etsuo Tanaka, Keńichiro Mihana, Takatomo Röhm, André Horisaki, Ryoichi Naruse, Makoto Department of Information Physics and Computing Graduate School of Information Science and Technology The University of Tokyo 7-3-1 Hongo Bunkyo Tokyo113-8656 Japan Graduate School of Environment and Information Sciences Yokohama National University 79-1 Tokiwadai Hodogaya Kanagawa Yokohama240-8501 Japan Department of Mathematical Informatics Graduate School of Information Science and Technology The University of Tokyo 7-3-1 Hongo Bunkyo Tokyo113-8656 Japan

In this paper, we claim that a common underlying structure—a skeleton structure—is present behind discrete-time quantum walks (QWs) on a one-dimensional lattice with a homogeneous coin matrix. This skeleton structure is independent of the initial state, and partially, even of the coin matrix. This structure is best interpreted in the context of quantum-walk-replicating random walks (QWRWs), i.e., random walks that replicate the probability distribution of quantum walks, where this newly found structure acts as a simplified formula for the transition probability. Additionally, we construct a random walk whose transition probabilities are defined by the skeleton structure and demonstrate that the resultant properties of the walkers are similar to both the original QWs and QWRWs. Copyright © 2022, The Authors. All rights reserved.

关键词： Probability distributions

来源：评论

学校读者我要写书评

暂无评论

A Survey on Deep Learning Technique for Video Segmentation

arXiv

引用

arXiv 2021年

作者： Zhou, Tianfei Porikli, Fatih Crandall, David J. Van Gool, Luc Wang, Wenguan ETH Zurich Switzerland The School of Computer Science Australian National University Australia The Luddy School of Informatics Computing and Engineering Indiana University United States ReLER Lab Australian Artificial Intelligence Institute University of Technology Sydney Australia

Video segmentation-partitioning video frames into multiple segments or objects-plays a critical role in a broad range of practical applications, from enhancing visual effects in movie, to understanding scenes in autonomous driving, to creating virtual background in video conferencing. Recently, with the renaissance of connectionism in computer vision, there has been an influx of deep learning based approaches for video segmentation that have delivered compelling performance. In this survey, we comprehensively review two basic lines of research - generic object segmentation (of unknown categories) in videos, and video semantic segmentation - by introducing their respective task settings, background concepts, perceived need, development history, and main challenges. We also offer a detailed overview of representative literature on both methods and datasets. We further benchmark the reviewed methods on several well-known datasets. Finally, we point out open issues in this field, and suggest opportunities for further research. We also provide a public website to continuously track developments in this fast advancing field: https://***/tfzhou/VS-Survey. Copyright © 2021, The Authors. All rights reserved.

关键词： Video conferencing

来源：评论

学校读者我要写书评

暂无评论

An Efficient Learning Weight of Elman Neural Network with Chicken Swarm Optimization Algorithm

引用

Procedia Computer Science 2021年 192卷 3060-3069页

作者： Barkat Ali Saima Anwar Lashari Wareesa Sharif Abdullah Khan Kamran ullah Dzati Athiar Ramli Institute of Computer Science and Information Technology The University of Agriculture Peshawar Pakistan College of Computing and Informatics Saudi Electronic University Riyadh KSA Faculty of Computing The Islamia University of Bahawalpur Pakistan Intelligent Biometrics Group (IBG) School of Electrical and Electronic Engineering USM Engineering Campus University Sains Malaysia 14300 Nibong Tebal Pulau Pinang

Data classification is one of the most frequently used tasks carried out to label information into predefined classes. The most commonly used models for data classification are Feed Forward Artificial Neural Networks (FFANN), and recurrent neural networks. The connection paths of these two structures are different from each other. Generally, the trained algorithm for these structures is back propagation (BP) algorithm which has many defects. For instance, due to the uncertain number of hidden layer neuron and fixed learning rate, it is easy to fall into local minimum, and it will never reach global minimum error function, it may stay at local minimum. Therefore, to make the slow learning process faster, it is necessary to carefully select the initial weight value. Therefore Meta heuristic search techniques play an important role for selection initial weights for the network. Chicken Swarm Optimization algorithm is one of the Meta heuristic technique effectively for selecting the initial weights values to converge to the optimal solution. However, this study proposed the Chicken Swarm Optimization for efficiently learn the initial weights value of Elman Neural Network algorithm. To validate the proposed algorithm, it is compared with existing algorithms such as Back Propagation Neural Network, Artificial Bee Colony Back Propagation and Genetic Algorithm Neural Network, and verified by two classification problems namely: IRIS and 7-bit parity. Simulation results shows that proposed algorithm outperforms with existing algorithms in terms of accuracy and mean square error.

关键词： Classification ANN RNN ENN BPNN ABCBP GANN CSENN Local minima Global minima

来源：评论

学校读者我要写书评

暂无评论

Opara: Exploiting Operator Parallelism for Expediting DNN Inference on GPUs

arXiv

引用

arXiv 2023年

作者： Chen, Aodong Xu, Fei Han, Li Dong, Yuan Chen, Li Zhou, Zhi Liu, Fangming The Shanghai Key Laboratory of Multidimensional Information Processing School of Computer Science and Technology East China Normal University 3663 N. Zhongshan Road Shanghai200062 China The School of Software Engineering East China Normal University 3663 N. Zhongshan Road Shanghai200062 China The School of Computing and Informatics University of Louisiana at Lafayette 301 East Lewis Street LafayetteLA70504 United States The Guangdong Key Laboratory of Big Data Analysis and Processing School of Computer Science and Engineering Sun Yat-sen University 132 E. Waihuan Road Guangzhou510006 China Peng Cheng Laboratory Huazhong University of Science and Technology China

GPUs have become the defacto hardware devices for accelerating Deep Neural Network (DNN) inference workloads. However, the conventional sequential execution mode of DNN operators in mainstream deep learning frameworks cannot fully utilize GPU resources, even with the operator fusion enabled, due to the increasing complexity of model structures and a greater diversity of operators. Moreover, the inadequate operator launch order in parallelized execution scenarios can lead to GPU resource wastage and unexpected performance interference among operators. In this paper, we propose Opara, a resource- and interference-aware DNN Operator parallel scheduling framework to accelerate DNN inference on GPUs. Specifically, Opara first employs CUDA Streams and CUDA Graph to parallelize the execution of multiple operators automatically. To further expedite DNN inference, Opara leverages the resource demands of operators to judiciously adjust the operator launch order on GPUs, overlapping the execution of compute-intensive and memory-intensive operators. We implement and open source a prototype of Opara based on PyTorch in a non-intrusive manner. Extensive prototype experiments with representative DNN and Transformer-based models demonstrate that Opara outperforms the default sequential CUDA Graph in PyTorch and the state-of-the-art operator parallelism systems by up to 1.68× and 1.29×, respectively, yet with acceptable runtime overhead. Copyright © 2023, The Authors. All rights reserved.

关键词： Deep neural networks

来源：评论

学校读者我要写书评

暂无评论

Using Business Intelligence Dashboard for Sustainable Urban Water Security Monitoring

Using Business Intelligence Dashboard for Sustainable Urban ...

引用

Emerging Technologies (GlobConET), IEEE IAS Global Conference on

作者： Zada Zainuddin Farashazillah Yahya Wee Bui Lin Bashirah Mohd Fazli Harlisa Zulkifli Mohammad Fikry Abdullah Faculty of Computing and Informatics Universiti Malaysia Sabah Kota Kinabalu Sabah Malaysia Faculty of Computer Science and Information Technology Universiti Malaysia Sarawak Sarawak Malaysia Water Quality and Environment Research Centre National Water Research Institute of Malaysia Selangor Malaysia Information Management Division National Water Research Institute of Malaysia Selangor Malaysia Leeds University Business School University of Leeds Leeds United Kingdom

This paper presents the findings from the experts on the effective factor of monitoring dashboards for urban water security. The urban water security dashboard monitors the water quality, availability, and other relevant indicators. Although monitoring dashboards exist, there are potential improvements in the context of urban water security. The study integrates the technological factors in the domain area. An expert review is conducted to get confirmation from professionals in the chosen sector about the effective factors for the dashboards from the IT perspective. This methodology uses qualitative via face-to-face and online sessions. Thematic analysis and content validity index (CVI) have been used to evaluate the experts' review. The findings show security and knowledge discovery is the main factor emphasised. The experts deemed visual design the least priority when creating a business intelligence dashboard. Experts also recommend embedding Artificial Intelligence (AI) with the data analysis for dashboards. The discussion identified challenges and future work for this research. The discussion identified three potential areas of future research in water security and informatics: i) investigating other dimensions of effective dashboards, ii) conducting additional research on the environmental dashboard, and iii) investigating dashboards' real-world application in urban water security.

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：