检索结果-内蒙古大学图书馆

An agenda for climate change and mental health in the Philippines

The Lancet. Planetary health 2021年第11期5卷 e755-e757页

作者： Renzo R Guinto Julius Cesar P Alejandre Marianne K Bongcac Johnrev Guilaran Sena S Salcedo Jun Angelo Sunglao Planetary and Global Health Program St Luke's Medical Center College of Medicine of William H Quasha Memorial Quezon City 1112 Philippines PH Lab Manila Philippines Sunway Centre for Planetary Health Sunway University Selangor Malaysia. Electronic address: guinto.rl.f@slmc-cm.edu.ph. Department of Civil Engineering and Environmental Management School of Computing Engineering and Built Environment Glasgow Caledonian University Glasgow UK. PH Lab Manila Philippines. Division of Social Sciences College of Arts and Sciences University of the Philippines Visayas Miagao Philippines. Mental Health First Response Manila Philippines St Arnold Center for Integral Development Quezon City Philippines. Institute of Psychiatry Psychology and Neuroscience King's College London London UK London School of Hygiene & Tropical Medicine London UK.

来源：评论

学校读者我要写书评

暂无评论

Quantum Simulation for High-Energy Physics

引用

PRX Quantum 2023年第2期4卷 027001-027001页

作者： Christian W. Bauer Zohreh Davoudi A. Baha Balantekin Tanmoy Bhattacharya Marcela Carena Wibe A. de Jong Patrick Draper Aida El-Khadra Nate Gemelke Masanori Hanada Dmitri Kharzeev Henry Lamm Ying-Ying Li Junyu Liu Mikhail Lukin Yannick Meurice Christopher Monroe Benjamin Nachman Guido Pagano John Preskill Enrico Rinaldi Alessandro Roggero David I. Santiago Martin J. Savage Irfan Siddiqi George Siopsis David Van Zanten Nathan Wiebe Yukari Yamauchi Kübra Yeter-Aydeniz Silvia Zorzetti Physics Division Lawrence Berkeley National Laboratory Berkeley California 94720 USA Department of Physics Maryland Center for Fundamental Physics and the NSF Institute for Robust Quantum Simulation University of Maryland College Park Maryland 20742 USA Department of Physics University of Wisconsin Madison Wisconsin 53706 USA T-2 Los Alamos National Laboratory Los Alamos New Mexico 87545 USA Fermi National Accelerator Laboratory Batavia Illinois 60510 USA Enrico Fermi Institute University of Chicago Chicago Illinois 60637 USA Kavli Institute for Cosmological Physics University of Chicago Chicago Illinois 60637 USA Department of Physics University of Chicago Chicago Illinois 60637 USA Department of Physics and Illinois Center for the Advanced Study of the Universe and Illinois Quantum Information Science and Technology Center University of Illinois Urbana Illinois 61801 USA QuEra Computing Inc Boston Massachusetts 02135 USA Department of Mathematics University of Surrey Guildford Surrey GU2 7XH United Kingdom Center for Nuclear Theory Department of Physics and Astronomy Stony Brook University New York 11794-3800 USA Department of Physics Brookhaven National Laboratory Upton New York 11973 USA Peng Huanwu Center for Fundamental Theory Hefei Anhui 230026 China Interdisciplinary Center for Theoretical Study University of Science and Technology of China Hefei Anhui 230026 China Pritzker School of Molecular Engineering Chicago Quantum Exchange and Kadanoff Center for Theoretical Physics University of Chicago Illinois 60637 USA qBraid Co. Harper Court 5235 Chicago Illinois 60615 USA Department of Physics Harvard University Cambridge Massachusetts 02138 USA Department of Physics and Astronomy University of Iowa Iowa City Iowa 52242 USA Duke Quantum Center Duke University Durham North Carolina 27701 USA Department of Electrical and Computer Engineering Duke University Durham North Carolina 27708 USA Department of Physics Duke University

It is for the first time that quantum simulation for high-energy physics (HEP) is studied in the U.S. decadal particle-physics community planning, and in fact until recently, this was not considered a mainstream topic in the community. This fact speaks of a remarkable rate of growth of this subfield over the past few years, stimulated by the impressive advancements in quantum information sciences (QIS) and associated technologies over the past decade, and the significant investment in this area by the government and private sectors in the U.S. and other countries. High-energy physicists have quickly identified problems of importance to our understanding of nature at the most fundamental level, from tiniest distances to cosmological extents, that are intractable with classical computers but may benefit from quantum advantage. They have initiated, and continue to carry out, a vigorous program in theory, algorithm, and hardware co-design for simulations of relevance to the HEP mission. This Roadmap is an attempt to bring this exciting and yet challenging area of research to the spotlight, and to elaborate on what the promises, requirements, challenges, and potential solutions are over the next decade and beyond.

关键词： Quantum simulation

来源：评论

学校读者我要写书评

暂无评论

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

引用

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

CEMCO: A Novel Competitive Evolutionary Multi-Colony Optimization Algorithm for Constrained Problems

CEMCO: A Novel Competitive Evolutionary Multi-Colony Optimiz...

引用

International Conference on Fuzzy Systems and Knowledge Discovery (FSKD)

作者： Mário Tasso Ribeiro Serra Neto Marco Antônio Florenzano Mollinetti Demison Rolins de Souza Alves Rodrigo Lisbôa Pereira Otávio Noura Teixeira University Centre of the State of Pará (CESUPA) Computational Intelligence Laboratory (LINCOMP) Belém Pará Brazil Systems Optimization Laboratory Tsukuba University Tsukuba Ibaraki Japan Federal Rural University of Amazon (UFRA) Electrical Engineering Post Graduation Program of the Federal University of Par (UFPA) Paragominas Pará Brazil Applied Computing Post Graduation Program (PPCA) Federal University of Pará Tucuruí (UFPA-TUC) Tucuruí Pará Brazil

ISBN: (纸本)9781538680988;9781538680971

The following paper presents a hybrid Swarm Intelligence algorithm, named Competitive Evolutionary Multi-Colony Optimization (CEMCO). CEMCO is based on the well-known bee inspired algorithm Artificial Bee Colony (ABC), introducing Evolutionary Strategies (ES)under a parallel master-slave architecture utilizing the General Purpose computing on Graphics Processing Units (GPGPU)paradigm. The goal of this approach is to enhance the overall performance of the master algorithm, producing high quality solutions, and significant solutions under a reduced processing time. Performance evaluation of CEMCO is performed by two large scale constrained optimization problems: Design of Pressure Vessel (DPV)and Welded Beam Design (WBD). Results obtained are compared against prominent techniques found in the literature.

关键词：

来源：评论

学校读者我要写书评

暂无评论

A survey of interdependency models for critical infrastructure networks

arXiv

引用

arXiv 2017年

作者： Banerjee, Joydeep Das, Arun Sen, Arunabha Computer Science and Engineering Program School of Computing Informatics and Decision System Engineering Arizona State University TempeAZ85287 United States

The critical infrastructures of the nation such as the power grid and the communication network are highly interdependent. Also, it has been observed that there exists complex interdependent relationships between individual entities of the power grid and the communication network that further obfuscates the analysis, and mitigation of faults in such multi-layered networks. In recent years, the research community has made significant efforts towards gaining insight and understanding of the interdependency relations in such multi-layered networks, and accordingly, a number of models have been proposed and analyzed towards realizing this goal. In this chapter we study existing interdependency models proposed in the recent literature and discuss their approach, and inherent features, towards modeling interdependent multi-layer networks. We also provide a brief discussion into the drawbacks of each of these models and propose an alternate model that addresses these drawbacks by capturing the interdependency relationships using a combination of conjunctive and disjunctive relations. Copyright © 2017, The Authors. All rights reserved.

关键词： Electric power transmission networks

来源：评论

学校读者我要写书评

暂无评论

Automated Lead Time Estimation for Manufacturing Networks with Dynamic Demand

Automated Lead Time Estimation for Manufacturing Networks wi...

引用

IEEE International Conference on Automation Science and engineering

作者： Ronald G. Askin Girish Jampani Hanumantha Faculty of Industrial Engineering Arizona State University Tempe Arizona Program in Industrial Engineering School of Computing Arizona State University Tempe Arizona

Efficient algorithms are essential for reliable lead time forecasting as they are often the basis for subsequent activities such as planned order releases and shop scheduling. Dynamic conditions are prevalent in modern manufacturing systems and reliable lead time forecasts can provide a competitive edge operationally. In this paper, we explore the use of efficient algorithms for steady state analysis to develop approximate estimates of lead times under dynamic conditions.

关键词： Queueing Networks Lead Time Forecasting Dynamic Demand

来源：评论

学校读者我要写书评

暂无评论

Directing Intentional Superposition Manipulation 13

Directing Intentional Superposition Manipulation

引用

13th AAAI Conference on Artificial Intelligence and Interactive Digital Entertainment, AIIDE 2017

作者： Robertson, Justus Amos-Binks, Adam Michael Young, R. Liquid Narrative Group Department of Computer Science NC State University RaleighNC27695 United States Liquid Narrative Group School of Computing The Entertainment Arts and Engineering Program University of Utah Salt Lake CityUT84112 United States

ISBN: (纸本)9781577357926

Strong story interactive narratives (IN) are stories that branch based on participant actions where all branches conform to a set of predefined constraints. However, participants in these systems may create branches where the constraints no longer hold. Strong story experience management, the process of generating IN trees, can be viewed as a game where the experience management agent wins if the story constraints hold during gameplay and loses if they are broken. In domains where the player has incomplete information of the story world, the experience manager can take action by shifting the player between alternate states that are consistent with the player's observations in order to maximize the probability that constraints will hold. This process is called superposition manipulation. In this paper we present a method of estimating the number of goal states reachable from different states in order to make informed decisions during superposition manipulation. Copyright © 2017, Association for the Advancement of Artificial Intelligence (***). All rights reserved.

关键词： Artificial intelligence

来源：评论

学校读者我要写书评

暂无评论

Generating Stories that Include Failed Actions by Modeling False Character Beliefs 13

Generating Stories that Include Failed Actions by Modeling F...

引用

13th AAAI Conference on Artificial Intelligence and Interactive Digital Entertainment, AIIDE 2017

作者： Thorne, Brandon R. Michael Young, R. Liquid Narrative Group Department of Computer Science NC State University RaleighNC27695 United States Liquid Narrative Group School of Computing The Entertainment Arts and Engineering Program University of Utah Salt Lake CityUT84112 United States

ISBN: (纸本)9781577357926

Previous work on story planning has lacked a knowledge representation for characters that make mistakes in the execution of their actions. In particular, characters' execution mistakes that arise from errors in belief have not been modeled. In this paper, we describe a state-space planning system and its belief model, together called HEADSPACE, that generates stories that track and manipulates characters' belief about the story world around them. This model is used to produce actions in stories that are attempted but that fail. We show an example story plan that contains failed-action content that cannot be generated by typical planning-based approaches to story creation. Copyright © 2017, Association for the Advancement of Artificial Intelligence (***). 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

Planning Graphs for Efficient Generation of Desirable Narrative Trajectories 13

Planning Graphs for Efficient Generation of Desirable Narrat...

引用

13th AAAI Conference on Artificial Intelligence and Interactive Digital Entertainment, AIIDE 2017

作者： Amos-Binks, Adam Potts, Colin Michael Young, R. Liquid Narrative Group Department of Computer Science NC State University RaleighNC27695 United States Liquid Narrative Group School of Computing The Entertainment Arts and Engineering Program University of Utah Salt Lake CityUT84112 United States

ISBN: (纸本)9781577357926

A goal of Experience Managers (EM) is to guide users through a space of narrative trajectories, or story branches, in an Interactive Narrative (IN). When a user performs an action that deviates from the intended trajectory, the EM uses a mediation strategy called accommodation to transition the user to a new desirable trajectory. However, generating the trajectory options then selecting the appropriate one is computationally expensive and at odds with the low-latency needs of an IN. We define three desirable properties (exemplar trajectories, narrative-theoretic comparison, and efficiency) that general solutions would possess and demonstrate how our plan-based Intention Dependency Graph addresses them. Copyright © 2017, Association for the Advancement of Artificial Intelligence (***). All rights reserved.

关键词： Trajectories

来源：评论

学校读者我要写书评

暂无评论

Narrative Mediation as Probabilistic Planning 13

Narrative Mediation as Probabilistic Planning

引用

13th AAAI Conference on Artificial Intelligence and Interactive Digital Entertainment, AIIDE 2017

作者： Robertson, Justus Michael Young, R. Liquid Narrative Group Department of Computer Science NC State University RaleighNC27695 United States Liquid Narrative Group School of Computing The Entertainment Arts and Engineering Program University of Utah Salt Lake CityUT84112 United States

ISBN: (纸本)9781577357926

Narrative mediation is a plan-based process that converts a planning problem into a mediation tree that models an interactive story. Probabilistic planning relaxes the classical planning constraint of deterministic action outcomes by containing domain operators with nondeterministic effects. This paper shows narrative mediation can be viewed as a probabilistic planning problem where the outcomes of user actions are modeled with nondeterministic effects in the domain. The paper gives a process for automatically converting a deterministic mediation planning problem into a probabilistic interactive narrative planning problem. Copyright © 2017, Association for the Advancement of Artificial Intelligence (***). All rights reserved.

关键词： Human robot interaction

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：