检索结果-内蒙古大学图书馆

IEEE International Symposium on Information Theory

作者： Runyao Duan Markus Grassl Zhengfeng Ji Bei Zeng State Key Laboratory of Intelligent Technology and Systems Tsinghua National Laboratory for Information Science and Technology Department of Computer Science and Technology Tsinghua University Beijing China Centre for Quantum Computation and Intelligent Systems (QCIS) Faculty of Engineering and Information Technology University of Technology Sydney NSW Australia Centre for Quantum Technologies National University of Singapore Singapore Perimeter Institute of Theoretical Physics Waterloo ONT Canada State Key Laboratory of Computer Science Institute of Software Chinese Academy and Sciences Beijing China Institute for Quantum Computing and the Department of Combinatorics and Optimization University of Waterloo Waterloo ONT Canada

ISBN: (纸本)9781424478903

We construct new families of multi-error-correcting quantum codes for the amplitude damping channel. Our key observation is that, with proper encoding, two uses of the amplitude damping channel simulate a quantum erasure channel. This allows us to use concatenated codes with quantum erasure-correcting codes as outer codes for correcting multiple amplitude damping errors. Our new codes are degenerate stabilizer codes and have parameters which are better than the amplitude damping codes obtained by any previously known construction.

关键词： Damping Quantum mechanics Quantum computing Error correction codes Noise level Laboratories Phase noise Physics computing Intelligent systems computer science

来源：评论

学校读者我要写书评

暂无评论

On the Parameterised Complexity of Induced Multipartite Graph Parameters

arXiv

引用

arXiv 2020年

作者： Mann, Ryan L. Mathieson, Luke Greenhill, Catherine School of Mathematics University of Bristol BristolBS8 1UG United Kingdom Centre for Quantum Computation and Communication Technology Centre for Quantum Software and Information Faculty of Engineering & Information Technology University of Technology SydneyNSW2007 Australia School of Computer Science University of Technology SydneyNSW2007 Australia School of Mathematics and Statistics UNSW Sydney NSW2052 Australia

We introduce a family of graph parameters, called induced multipartite graph parameters, and study their computational complexity. First, we consider the following decision problem: an instance is an induced multipartite graph parameter p and a given graph G, and for natural numbers k ≥ 2 and , we must decide whether the maximum value of p over all induced k-partite subgraphs of G is at most . We prove that this problem is W[1]-hard. Next, we consider a variant of this problem, where we must decide whether the given graph G contains a sufficiently large induced k-partite subgraph H such that p(H) ≤ . We show that for certain parameters this problem is para-NP-hard, while for others it is fixed-parameter tractable. Copyright © 2020, The Authors. All rights reserved.

关键词： Graph theory

来源：评论

学校读者我要写书评

暂无评论

RETRACTED ‘Application of adaptive neuro-fuzzy technique to determine the most relevant variables for daily soil temperature prediction at different depths’

引用

CATENA 2017年 149卷 446-446页

作者： Kasra Mohammadi Shahaboddin Shamshirband Amirrudin Kamsin Raja Jamilah Raja Yusof Department of Mechanical and Industrial Engineering University of Massachusetts Amherst MA 01003 USA Department of Computer System and Technology Faculty of Computer Science and Information Technology University of Malaya Kuala Lumpur Malaysia Department of Software Engineering Faculty of Computer Science and Information Technology University Malaya 50603 Kuala Lumpur Malaysia

来源：评论

学校读者我要写书评

暂无评论

A comparative analysis on diagnosis of diabetes mellitus using different approaches – A survey

引用

Informatics in Medicine Unlocked 2020年 21卷

作者： Anwar, Fareeha Qurat-Ul-Ain Ejaz, Muhammad Yasir Mosavi, Amir Department of Computer Science and Software Engineering International Islamic University Islamabad (IIUI) Islamabad 44000 Pakistan School of Economics and Business Norwegian University of Life Sciences Ås 1430 Norway John von Neumann Faculty of Informatics Obuda University Budapest 1034 Hungary Department of Informatics J. Selye University Komarno 94501 Slovakia

Diabetes Mellitus is commonly known as diabetes. It is one of the most chronic diseases as the World Health Organization (WHO) report shows that the number of diabetes patients has risen from 108 million to 422 million in 2014. Early diagnosis of diabetes is important because it can cause different diseases that include kidney failure, stroke, blindness, heart attacks, and lower limb amputation. Different diabetes diagnosis models are found in literature, but there is still a need to perform a survey to analyze which model is best. This paper performs a literature review for diabetes diagnosis approaches using Artificial Intelligence (neural networks, machine learning, deep learning, hybrid methods, and/or stacked-integrated use of different machine learning algorithms). More than thirty-five papers have been shortlisted that focus on diabetes diagnosis approaches. Different datasets are available online for the diagnosis of diabetes. Pima Indian Diabetes Dataset (PIDD) is the most commonly used for diabetes prediction. In contrast with other datasets, it has key factors which play an important role in diabetes diagnosis. This survey also throws light on the weaknesses of the existing approaches that make them less appropriate for a diabetes diagnosis. In artificial intelligence techniques, deep learning is widespread and in medical research, heart rate is getting more attention. Deep learning combined with other algorithms can give better results in diabetes diagnosis and heart rate should be used for other cardiac disease diagnoses. © 2020 The Authors

关键词： Accuracy Deep learning Diabetes mellitus Machine learning

来源：评论

学校读者我要写书评

暂无评论

A Brief Review of Explainable Artificial Intelligence in Healthcare

SSRN

引用

SSRN 2023年

作者： Sadeghi, Zahra Alizadehsani, Roohallah Cifci, Mehmet Akif Kausar, Samina Rehman, Rizwan Mahanta, Priyakshi Bora, Pranjal Kumar Almasri, Ammar Alkhawaldeh, Rami S. Hussain, Sadiq Alatas, Bilal Shoeibi, Afshin Moosaei, Hossein Hladík, Milan Nahavandi, Saeid Pardalo, Panos M. Institute for Big Data Analytics Faculty of Computer Science Dalhousie University Canada Deakin University Geelong Australia The Institute of Computer Technology Tu Wien University Vienna1040 Austria University of Kotli Azad Jammu and Kashmir Azad Kashmir Kotli Pakistan Centre for Computer Science and Applications Dibrugarh University Assam India Department of Management Information Sys Al-Balqa Applied University Salt19117 Jordan Department of Computer Information Systems The University of Jordan Aqaba77110 Jordan Examination Branch Dibrugarh University Assam Dibrugarh India Department of Software Eng. Firat University Elazig23100 Turkey Data Science and Computational Intelligence Institute University of Granada Spain Department of Informatics Faculty of Science Jan Evangelista Purkyně University in Ústí nad Labem Czech Republic Department of Applied Mathematics School of Computer Science Faculty of Mathematics and Physics Charles University Prague Czech Republic Harvard Paulson School of Engineering and Applied Sciences Harvard University AllstonMA02134 United States Swinburne University of Technology HawthornVIC3122 Australia Center for Applied Optimization Department of Industrial and Systems Engineering University of Florida Gainesville32611 United States

XAI refers to the techniques and methods for building AI applications which assist end users to interpret output and predictions of AI models. Black box AI applications in high-stakes decision-making situations, such as medical domain have increased the demand for transparency and explainability since wrong predictions may have severe consequences. Model explainability and interpretability are vital successful deployment of AI models in healthcare practices. AI applications' underlying reasoning needs to be transparent to clinicians in order to gain their trust. This paper presents a systematic review of XAI aspects and challenges in the healthcare domain. The primary goals of this study are to review various XAI methods, their challenges, and related machine learning models in healthcare. The methods are discussed under six categories: Features-oriented methods, global methods, concept models, surrogate models, local pixel-based methods, and human-centric methods. Most importantly, the paper explores XAI role in healthcare problems to clarify its necessity in safety-critical applications. The paper intends to establish a comprehensive understanding of XAI-related applications in the healthcare field by reviewing the related experimental results. To facilitate future research for filling research gaps, the importance of XAI models from different viewpoints and their limitations are investigated. © 2023, The Authors. All rights reserved.

关键词： Decision making

来源：评论

学校读者我要写书评

暂无评论

Reversible Fragile Watermarking based on Difference Expansion Using Manhattan Distances for 2D Vector Map

引用

Procedia Technology 2013年 11卷 614-620页

作者： Shelvie Nidya Neyman Benhard Sitohang Sobar Sutisna Department of Computer Science– Faculty of Mathematics and Natural Sciences (FMIPA) Institut Pertanian Bogor (IPB) Gedung FMIPA Kampus IPB Dramaga Jl. Meranti Dramaga Bogor 16680 Indonesia Software Engineering & Data – Research Group School of Electrical Engineering and Informatics (STEI) nstitut Teknologi Bandung(ITB) Achmad Bakrie Building 2nd Floor Jl. Ganesha No 10 Bandung 40132 Indonesia Peneliti Utama Badan Informasi Geospasial (BIG) Jl.Raya Jakarta-Bogor Km.46 Cibinong 16911 Indonesia

The need for publishing maps in secure digital format, especially guarantees data integrity which motivated us to propose a scheme that detects and locates modification data with high accuracy while ensuring exact recovery of the original content. In particular, using fragile watermarking algorithm based on reversible manner to embed hidden data in 2D vector map for each spatial features. In this paper, a reversible data-hiding scheme is explored based on the idea of difference expansion with Manhattan distances. A set of invertible integer mappings is defined to extract Manhattan distances from coordinates and the hidden data are embedded by modifying the differences between the adjacent distances. Experiments results show that the proposed scheme has good performance in term invisibility and tamper modification ability. The scheme could detect modification data such addition and deletion some features, and exactly recovery the original content of the 2D vector map.

关键词： Reversible Watermarking Fragile Watermarking Difference Expansion Manhattan Distances Vector Map

来源：评论

学校读者我要写书评

暂无评论

Conceptual Design of a Generic Nodal Abstraction (GNA) for a Human-Agent Collaboration Systems

引用

IOP Conference Series: Materials science and engineering 2019年第1期551卷

作者： Khudhair Abbas Mohammed Mazlina Abdul Majid Mohd Sharifuddin Ahmad Faculty of Computer Systems & Software Engineering University Malaysia Pahang Kuantan Pahang Malaysia College of Computer Science and Information Technology Universiti Tenaga Nasional 43000 Kajang Selangor Malaysia

The issues of modelling software agents in collaborative systems present some problems and difficulties caused by the diversity of tasks and the procedures attached to them. Consequently, such diversity poses a critical challenge to implement scheduled tasks. In this paper, we propose collaborative human-agent system in which a software agent collaborates and cooperates with its human counterpart in several job positions of an organization. The goal of the GNA approach is to improve collaboration between humans when performing tasks within a workflow process. The GNA is built based on the concept of a node which comprises of a human, agents, and their shared functions. This concept espouses the notion that agents could be deployed to assist humans in many common workflow processes and to handle mundane tasks. Furthermore, a multi-agent system is advocated as an application or platform for managing distributed data. Specifically, this paper describes a conceptual design of a generic approach based on the notion of nodes to construct a Generic Nodal Abstraction (GNA) approach that is deployable as a modeling and simulation platform for organizational processes.

关键词：

来源：评论

学校读者我要写书评

暂无评论

Continuous Evolution of Digital Twins using the DarTwin Notation

arXiv

引用

arXiv 2024年

作者： Mertens, Joost Klikovits, Stefan Bordeleau, Francis Denil, Joachim Haugen, Øystein Faculty of Applied engineering: Electronics and ICT University of Antwerp Groenenborgerlaan 171 Antwerp Antwerp2020 Belgium Institute for Business Informatics - Software Engineering Johannes Kepler University Altenberger Strasse 69 Linz4040 Austria Montreal Canada Flanders Make @UAntwerpen University of Antwerp Groenenborgerlaan 171n Antwerpen Antwerp2020 Belgium Department of Computer Science and Communication Østfold University College B R A veien 4 Halden1757 Norway

Despite best efforts, various challenges remain in the creation and maintenance processes of digital twins (DTs). One of those primary challenges is the constant, continuous and omnipresent evolution of systems, their user’s needs and their environment, demanding the adaptation of the developed DT systems. DTs are developed for a specific purpose, which generally entails the monitoring, analysis, simulation or optimization of a specific aspect of an actual system, referred to as the actual twin (AT). As such, when the twin system changes, that is either the AT itself changes, or the scope/purpose of a DT is modified, the DTs usually evolve in close synchronicity with the AT. As DTs are software systems, the best practices or methodologies for software evolution can be leveraged. This paper tackles the challenge of maintaining a (set of) DT(s) throughout the evolution of the user’s requirements and priorities and tries to understand how this evolution takes place. In doing so, we provide two contributions: (i) we develop DarTwin, a visual notation form that enables reasoning on a twin system, its purposes, properties and implementation, and (ii) we introduce a set of architectural transformations that describe the evolution of DT systems. The development of these transformations is driven and illustrated by the evolution and transformations of a family home’s DT, whose purpose is expanded, changed and re-prioritized throughout its ongoing lifecycle. Additionally, we evaluate the transformations on a lab-scale gantry crane’s DT. © 2024, CC BY.

关键词： Smart homes

来源：评论

学校读者我要写书评

暂无评论

Using deep learning for predicting the dynamic evolution of breast cancer migration

引用

computers in Biology and Medicine 2024年 180卷 108890页

作者： Garcia-Moreno, Francisco M. Ruiz-Espigares, Jesús Gutiérrez-Naranjo, Miguel A. Marchal, Juan Antonio Department of Software Engineering Computer Science School University of Granada C/ Periodista Daniel Saucedo Aranda s/n Granada18014 Spain University of Granada Granada Spain University of Granada GranadaE-18016 Spain University of Granada Granada18016 Spain Department of Human Anatomy and Embryology Faculty of Medicine University of Granada GranadaE-18016 Spain University Hospitals of Granada-University of Granada GranadaE-18071 Spain Department of Computer Sciences and Artificial Intelligence University of Sevilla Avda. Reina Mercedes s/n Sevilla41012 Spain

Background: Breast cancer (BC) remains a prevalent health concern, with metastasis as the main driver of mortality. A detailed understanding of metastatic processes, particularly cell migration, is fundamental to improve therapeutic strategies. The wound healing assay, a traditional two-dimensional (2D) model, offers insights into cell migration but presents scalability issues due to data scarcity, arising from its manual and labor-intensive nature. Method: To overcome these limitations, this study introduces the Prediction Wound Progression Framework (PWPF), an innovative approach utilizing Deep Learning (DL) and artificial data generation. The PWPF comprises a DL model initially trained on artificial data that simulates wound healing in MCF-7 BC cell monolayers and spheres, which is subsequently fine-tuned on real-world data. Results: Our results underscore the model's effectiveness in analyzing and predicting cell migration dynamics within the wound healing context, thus enhancing the usability of 2D models. The PWPF significantly contributes to a better understanding of cell migration processes in BC and expands the possibilities for research into wound healing mechanisms. Conclusions: These advancements in automated cell migration analysis hold the potential for more comprehensive and scalable studies in the future. Our dataset, models, and code are publicly available at https://***/frangam/wound-healing. © 2024 The Author(s)

关键词： Forecasting

来源：评论

学校读者我要写书评

暂无评论

Real-Time Detection of UAV Small Target’s Infrared Imaging via OSTD-YOLOv8

Real-Time Detection of UAV Small Target’s Infrared Imaging ...

引用

IEEE URUCON

作者： Fida Hussain Dahri Asif Ali Laghari Nisar Ahmed Dahri Ghulam E Mustafa Abro Vania V. Estrela G. G. de Oliveira Y. Iano Euclides L. Chuma School of Computer Science and Engineering Southeast University Nanjing China Software College Shenyang Normal University Shenyang China Faculty of Educational Sciences and Technology University Teknologi Malaysia Johor Bahru Malaysia Interdisciplinary Research Centre for Aviation and Space Exploration King Fahd University of Petroleum and Minerals Dhahran Kingdom of Saudi Arabia Department of Telecommunications Federal Fluminense University (UFF) Niteroi Brazil School of Electrical and Computer Engineering Universidade Estadual de Campinas (UNICAMP) Campinas Brazil School of Technology Universidade Estadual de Campinas (UNICAMP) Limeira Brazil

ISBN: (数字)9798350355383

ISBN: (纸本)9798350355390

Unmanned aerial vehicles (UAVs) have boosted modern living. Tiny, frail high-density targets, low resolution, complicated backgrounds, noise, and poor real-time exposure performance have augmented due to UAV firms. Realtime recognition in high-altitude (HA) infrared thermal images is intricate. Our fresh OSTD-YOLOv8 is a multi-class target recognition tactic to tackle these issues and spot and classify objects on the HIT-UAV dataset. YOLOv8 is an effective advanced object detection model. Our OSTD-YOLOv8 model detects small objects in HA thermal images with ${90 \%}$ precision, ${91.5 \%}$ recall, ${90.5 \%}$ F1-score, ${89.1 \%}$ AP, and 98% mAP. Our unique approach delivers effective object recognition in difficult thermal imaging conditions. Consequently, this distinctive UAV-focused HA, thermal, target detection scheme can be used.

关键词： Image resolution Image recognition Accuracy Target recognition Object detection Infrared imaging Autonomous aerial vehicles Real-time systems Background noise computer security

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：