检索结果-内蒙古大学图书馆

Author Correction: Greengenes2 unifies microbial data in a single reference tree

Nature biotechnology 2024年第5期42卷 813页

作者： Daniel McDonald Yueyu Jiang Metin Balaban Kalen Cantrell Qiyun Zhu Antonio Gonzalez James T Morton Giorgia Nicolaou Donovan H Parks Søren M Karst Mads Albertsen Philip Hugenholtz Todd DeSantis Se Jin Song Andrew Bartko Aki S Havulinna Pekka Jousilahti Susan Cheng Michael Inouye Teemu Niiranen Mohit Jain Veikko Salomaa Leo Lahti Siavash Mirarab Rob Knight Department of Pediatrics University of California San Diego School of Medicine La Jolla CA USA. Department of Electrical and Computer Engineering University of California San Diego La Jolla CA USA. Bioinformatics and Systems Biology Program University of California San Diego La Jolla CA USA. Department of Computer Science and Engineering University of California San Diego La Jolla CA USA. School of Life Sciences Arizona State University Tempe AZ USA. Biodesign Center for Fundamental and Applied Microbiomics Arizona State University Tempe AZ USA. Biostatistics & Bioinformatics Branch Eunice Kennedy Shriver National Institute of Child Health and Human Development National Institutes of Health Bethesda MD USA. Halicioglu Data Science Institute University of California San Diego La Jolla CA USA. Australian Centre for Ecogenomics School of Chemistry and Molecular Biosciences The University of Queensland St Lucia Queensland Australia. Department of Obstetrics and Gynecology Columbia University New York NY USA. Department of Chemistry and Bioscience Aalborg University Aalborg Denmark. Department of Informatics Second Genome Brisbane CA USA. Center for Microbiome Innovation Jacobs School of Engineering University of California San Diego La Jolla CA USA. Finnish Institute for Health and Welfare Helsinki Finland. Institute for Molecular Medicine Finland FIMM-HiLIFE Helsinki Finland. Division of Cardiology Brigham and Women's Hospital Boston MA USA. Cedars-Sinai Medical Center Los Angeles CA USA. Cambridge Baker Systems Genomics Initiative Baker Heart and Diabetes Institute Melbourne Victoria Australia. Cambridge Baker Systems Genomics Initiative Department of Public Health and Primary Care University of Cambridge Cambridge UK. Division of Medicine Turku University Hospital and University of Turku Turku Finland. Sapient Bioanalytics LLC San Diego CA USA. Department of Computing University of Turku Turku Finland. Department of Pediatrics Uni

来源：评论

学校读者我要写书评

暂无评论

Susceptibility of Large Language Models to User-Driven Factors in Medical Queries

arXiv

引用

arXiv 2025年

作者： Lim, Kyung Ho Kang, Ujin Li, Xiang Kim, Jin Sung Jung, Young-Chul Park, Sangjoon Kim, Byung-Hoon Department of Psychiatry Yonsei University College of Medicine 50-1 Yonsei-ro Seodaemun-gu Seoul03722 Korea Republic of Institute of Behavioral Science in Medicine Yonsei University College of Medicine 50-1 Yonsei-ro Seodaemun-gu Seoul03722 Korea Republic of Department of Computer Science and Engineering Yonsei University 50-1 Yonsei-ro Seodaemun-gu Seoul03722 Korea Republic of Center for Advanced Medical Computing and Analysis Massachusetts General Hospital Harvard Medical School 55 Fruit Street BostonMA02114 United States Department of Radiation Oncology Yonsei University College of Medicine 50-1 Yonsei-ro Seodaemun-gu Seoul03722 Korea Republic of Institute for Innovation in Digital Healthcare Yonsei University 50-1 Yonsei-ro Seodaemun-gu Seoul03722 Korea Republic of Oncosoft Inc. Teheran-ro 26-gil Gangnam-gu Seoul06236 Korea Republic of Department of Biomedical Systems Informatics Yonsei University College of Medicine 50-1 Yonsei-ro Seodaemun-gu Seoul03722 Korea Republic of

Background Large language models (LLMs) are increasingly used in healthcare;however, their reliability is influenced by query phrasing and the completeness of provided information. Via this study, we aim to assess how user-driven factors, including misinformation framing, source authority, model personas, and omission of critical clinical details, influence the diagnostic accuracy and reliability of LLM-generated medical responses. Method This study incorporates two tests: (1) perturbation—evaluating LLM persona (assistant vs. expert AI), misinformation source authority (inexperienced vs. expert), and tone (assertive vs. hedged);and (2) ablation—omission of key clinical data, utilizing publicly available medical datasets, including MedQA, and Medbullets. Proprietary LLMs (GPT-4o (OpenAI), Claude-3·5 Sonnet(Anthropic), Claude-3·5 Haiku(Anthropic), Gemini-1·5 Pro(Google), Gemini-1·5 Flash(Google)) and open-source LLMs (LLaMA-3 8B, LLaMA-3 Med42 8B, DeepSeek-R1 8B) was used for evaluation. Findings All LLMs were susceptible to user-driven misinformation;however, proprietary models were more influenced by definitive, authoritative misinformation, and assertive tone had the most significant impact. In the ablation test, omitting physical examination findings and laboratory results caused the largest accuracy decline. Proprietary models showed higher baseline accuracy;however, their performance declined with misinformation exposure. Interpretation Structured prompts and complete clinical context are essential for accurate responses. Users should avoid authoritative misinformation framing and provide a complete clinical context, especially for complex and challenging queries. Funding Bio&Medical Technology Development Program of the National Research Foundation (NRF), Korean government (MSIT;RS-2024-00509289) Basic Science Research Program through the National Research Foundation of Korea(NRF), Ministry of Education(NRF-2022R1I1A1A01069589 and RS-2023-0024216). © 2025, CC

关键词： Diagnosis

来源：评论

学校读者我要写书评

暂无评论

A Unifying framework for UML profile-based cognitive modeling: Development and experience 17

A Unifying framework for UML profile-based cognitive modelin...

引用

10th EAI International Conference on Simulation Tools and Techniques, SIMUTOOLS 2017

作者： Zhu, Zhi Lei, Yonglin Zhu, Yifan Alshareef, Abdurrahman Sarjoughian, Hessam S. Institute of Simulation Engineering College of Information System and Management National University of Defense Technology Changsha410073 China Arizona Center for Integrated Modeling and Simulation School of Computing Informatics and Decision Systems Engineering Arizona State University TempeAZ85281 United States

ISBN: (纸本)9781450363884

To achieve model reuse, cognitive decision behaviors are usually implemented using a scripting language which is separate from the programming language used to implement simulation models. Therefore, it is desirable to establish a much better grounding for cognitive modeling. In the context of Domain-Specific Modeling (DSM), metamodeling from scratch for designing such a scripting language poses some limitations, among which is the issue of integrating various models that are represented by different customized languages, together with a large expenditure of designing, implementing, and maintaining these languages and their supporting resources. Instead, UML Profile-based metamodeling is adopted in this research, as a light weighted extension to capture the cognitive domain concepts, relationships, and constraints. Moreover, we propose a unifying framework for designing the domain specific profile where the expressiveness of cognitive domain specification is increased and the development cost and time decreased. Also, we present the development process by constructing a profile of Anti-Submarine Tactics (AST) and illustrate it by demonstrating an example with a scenario of armed escort. © 2017 Association for computing Machinery.

关键词： Submarines

来源：评论

学校读者我要写书评

暂无评论

From the lab to the desert: Fast prototyping and learning of robot locomotion

From the lab to the desert: Fast prototyping and learning of...

引用

2017 Robotics: Science and systems, RSS 2017

作者： Luck, Kevin Sebastian Campbell, Joseph Jansen, Michael Andrew Aukes, Daniel M. Amor, Heni Ben School of Computing Informatics and Decision Systems Engineering Arizona State University TempeAZ85281 United States School of Life Sciences Arizona State University TempeAZ85281 United States Polytechnic School Arizona State University TempeAZ85281 United States

ISBN: (纸本)9780992374730

We present a methodology for fast prototyping of morphologies and controllers for robot locomotion. Going beyond simulation-based approaches, we argue that the form and function of a robot, as well as their interplay with realworld environmental conditions are critical. Hence, fast design and learning cycles are necessary to adapt robot shape and behavior to their environment. To this end, we present a combination of laminate robot manufacturing and sampleefficient reinforcement learning. We leverage this methodology to conduct an extensive robot learning experiment. Inspired by locomotion in sea turtles, we design a low-cost crawling robot with variable, interchangeable fins. Learning is performed using both bio-inspired and original fin designs in an artificial indoor environment as well as a natural environment in the Arizona desert. The findings of this study show that static policies developed in the laboratory do not translate to effective locomotion strategies in natural environments. In contrast to that, sample-efficient reinforcement learning can help to rapidly accommodate changes in the environment or the robot. © 2017 MIT Press Journals. All rights reserved.

关键词： Reinforcement learning

来源：评论

学校读者我要写书评

暂无评论

Balancing explicability and explanations

arXiv

引用

arXiv 2017年

作者： Chakraborti, Tathagata Sreedharan, Sarath Kambhampati, Subbarao School of Computing Informatics Decision Systems Engineering Arizona State University TempeAZ85281 United States

Human aware planning requires an agent to be aware of the intentions, capabilities and mental model of the human in the loop during its decision process. This can involve generating plans that are explicable to a human observer as well as the ability to provide explanations when such plans cannot be generated. In this paper, we bring these two concepts together and show how an agent can account for both these needs and achieve a trade-off during the plan generation process itself by means of a model-space search method MEGA. This in effect provides a comprehensive perspective of what it means for a decision-making agent to be "human-aware" by bringing together existing principles of planning under the umbrella of a single plan generation process. We situate our discussion in the context of recent work on explicable planning and explanation generation, and illustrate these concepts in modified versions of two well-known planning domains, as well as in a demonstration of a robot involved in a typical search and reconnaissance task with an external supervisor. Human factor studies in the latter highlight the usefulness of the proposed approaches. Copyright © 2017, 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

Plan explanations as model reconciliation: Moving beyond explanation as soliloquy

arXiv

引用

arXiv 2017年

作者： Chakraborti, Tathagata Sreedharan, Sarath Zhang, Yu Kambhampati, Subbarao School of Computing Informatics Decision Systems Engineering Arizona State University TempeAZ85281 United States

When AI systems interact with humans in the loop, they are often called on to provide explanations for their plans and behavior. Past work on plan explanations primarily involved the AI system explaining the correctness of its plan and the rationale for its decision in terms of its own model. Such soliloquy is wholly inadequate in most realistic scenarios where the humans have domain and task models that differ significantly from that used by the AI system. We posit that the explanations are best studied in light of these differing models. In particular, we show how explanation can be seen as a "model reconciliation problem" (MRP), where the AI system in effect suggests changes to the human's model, so as to make its plan be optimal with respect to that changed human model. We will study the properties of such explanations, present algorithms for automatically computing them, and evaluate the performance of the algorithms. Copyright © 2017, The Authors. All rights reserved.

关键词：

来源：评论

学校读者我要写书评

暂无评论

On the manipulation of articulated objects in human-robot cooperation scenarios

arXiv

引用

arXiv 2018年

作者： Capitanelli, Alessio Maratea, Marco Mastrogiovanni, Fulvio Vallati, Mauro Department of Informatics Bioengineering Robotics and Systems Engineering University of Genoa via Opera Pia 13 Genoa16145 Italy School of Computing and Engineering University of Huddersfield Queensgate HuddersfieldHD13DH United Kingdom

MSC codes 68T40Articulated and flexible objects constitute a challenge for robot manipulation tasks, but are present in different real-world settings, including home and industrial environments. Current approaches to the manipulation of articulated and flexible objects employ ad hoc strategies to sequence and perform actions on them depending on a number of physical or geometrical characteristics related to those objects, as well as on an a priori classification of target object configurations. In this paper, we propose an action planning and execution framework, which (i) considers abstract representations of articulated or flexible objects, (ii) integrates action planning to reason upon such configurations and to sequence an appropriate set of actions with the aim of obtaining a target configuration provided as a goal, and (iii) is able to cooperate with humans to collaboratively carry out the plan. On the one hand, we show that a trade-off exists between the way articulated or flexible objects are perceived and how the system represents them. Such a trade-off greatly impacts on the complexity of the planning process. On the other hand, we demonstrate the system's capabilities in allowing humans to interrupt robot action execution, and - in general - to contribute to the whole manipulation process. Results related to planning performance are discussed, and examples with a Baxter dual-arm manipulator performing actions collaboratively with humans are shown. Copyright © 2018, The Authors. All rights reserved.

关键词： Knowledge representation

来源：评论

学校读者我要写书评

暂无评论

Navigating the landscape for real-time localisation and mapping for robotics and virtual and augmented reality

arXiv

引用

arXiv 2018年

作者： Saeedi, Sajad Bodin, Bruno Wagstaff, Harry Nisbet, Andy Nardi, Luigi Mawer, John Melot, Nicolas Palomar, Oscar Vespa, Emanuele Spink, Tom Gorgovan, Cosmin Webb, Andrew Clarkson, James Tomusk, Erik Debrunner, Thomas Kaszyk, Kuba Gonzalez-de-Aledo, Pablo Rodchenko, Andrey Riley, Graham Kotselidis, Christos Franke, Björn O’Boyle, Michael F.P. Davison, Andrew J. Kelly, Paul H.J. Luján, Mikel Furber, Steve Department of Computing Imperial College London United Kingdom School of Informatics University of Edinburgh United Kingdom School of Computer Science University of Manchester United Kingdom Electrical Engineering - Computer Systems Stanford University United States

Visual understanding of 3D environments in real-time, at low power, is a huge computational challenge. Often referred to as SLAM (Simultaneous Localisation and Mapping), it is central to applications spanning domestic and industrial robotics, autonomous vehicles, virtual and augmented reality. This paper describes the results of a major research effort to assemble the algorithms, architectures, tools, and systems software needed to enable delivery of SLAM, by supporting applications specialists in selecting and configuring the appropriate algorithm and the appropriate hardware, and compilation pathway, to meet their performance, accuracy, and energy consumption goals. The major contributions we present are (1) tools and methodology for systematic quantitative evaluation of SLAM algorithms, (2) automated, machine-learning-guided exploration of the algorithmic and implementation design space with respect to multiple objectives, (3) end-to-end simulation tools to enable optimisation of heterogeneous, accelerated architectures for the specific algorithmic requirements of the various SLAM algorithmic approaches, and (4) tools for delivering, where appropriate, accelerated, adaptive SLAM solutions in a managed, JIT-compiled, adaptive runtime context. Copyright © 2018, The Authors. All rights reserved.

关键词： Mapping

来源：评论

学校读者我要写书评

暂无评论

SLAMBench2: Multi-objective head-to-head benchmarking for visual SLAM

arXiv

引用

arXiv 2018年

作者： Bodin, Bruno Wagstaff, Harry Saeedi, Sajad Nardi, Luigi Vespa, Emanuele Mawer, John Nisbet, Andy Luján, Mikel Furber, Steve Davison, Andrew J. Kelly, Paul H.J. O’Boyle, Michael F.P. School of Informatics University of Edinburgh United Kingdom Department of Computing Imperial College London United Kingdom School of Computer Science University of Manchester United Kingdom Electrical Engineering - Computer Systems Stanford University United States

SLAM is becoming a key component of robotics and augmented reality (AR) systems. While a large number of SLAM algorithms have been presented, there has been little effort to unify the interface of such algorithms, or to perform a holistic comparison of their capabilities. This is a problem since different SLAM applications can have different functional and non-functional requirements. For example, a mobile phone-based AR application has a tight energy budget, while a UAV navigation system usually requires high accuracy. SLAMBench2 is a benchmarking framework to evaluate existing and future SLAM systems, both open and close source, over an extensible list of datasets, while using a comparable and clearly specified list of performance metrics. A wide variety of existing SLAM algorithms and datasets is supported, e.g. ElasticFusion, InfiniTAM, ORB-SLAM2, OKVIS, and integrating new ones is straightforward and clearly specified by the framework. SLAMBench2 is a publicly-available software framework which represents a starting point for quantitative, comparable and validatable experimental research to investigate trade-offs across SLAM systems. Copyright © 2018, The Authors. All rights reserved.

关键词： Benchmarking

来源：评论

学校读者我要写书评

暂无评论

On Autonomous systems: From Reflexive, Imperative and Adaptive Intelligence to Autonomous and Cognitive Intelligence

On Autonomous Systems: From Reflexive, Imperative and Adapti...

引用

IEEE International Conference on Cognitive informatics

作者： Yingxu Wang Konstantinos N. Plataniotis Sam Kwong Henry Leung Svetlana Yanushkevich Fakhri Karray Ming Hou Newton Howard Rodolfo A. Fiorini Paolo Soda Edward Tunstel Jianmin Wang Shushma Patel International Institute of Cognitive Informatics and Cognitive Computing (ICIC) Schulich School of Engineering and Hotchkiss Brain Institute University of Calgary Canada University of Toronto Canada City University of Hong Kong Hong Kong University of Waterloo Canada Toronto Research Centre DRDC Canada Computational Neurosciences Lab University of Oxford UK Information & Bioengg. Politecnico di Milano University Italy Univ. Campus Bio-Medico of Rome Italy Autonomous and Intelligent Systems President IEEE SMC School of Software Tsinghua University China School of Engineering London South Bank University UK

ISBN: (数字)9781728114194

ISBN: (纸本)9781728104966

Autonomous systems underpinned by cognitive intelligence represent advanced forms of artificial intelligence studied in intelligence science, systems science, and computational intelligence. Traditional theories and technologies of autonomous systems put emphases on human-system interactions and humans in-the-loop. This paper explores the intelligence and system foundations of autonomous systems. It focuses on what structural and behavioral properties constitute the intelligence power of autonomous systems. It explains how system intelligence aggregates from reflexive, imperative, adaptive intelligence to autonomous and cognitive intelligence. A Hierarchical Intelligence Model (HIM) is introduced to elaborate the evolution of human and system intelligence as an inductive process. A set of properties of system autonomy is formally analyzed towards a wide range of autonomous system applications in computational intelligence and systems engineering.

关键词： Frequency modulation Electronic mail Handheld computers Cognitive systems Robots Animals

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：