检索结果-内蒙古大学图书馆

International Conference on Network and Service Management

作者： Lucas L. Nesi Maurício A. Pillon Marcos D. de Assunção Charles C. Miers Guilherme P. Koslovski Graduate Program in Applied Computing Santa Catarina State University Joinville Brazil Inria Avalon LIP Laboratory ENS Lyon University of Lyon France

ISBN: (纸本)9781538691939;9783903176140

Allocating IT resources to Virtual Infrastructures (VIs) (i.e., groups of VMs, virtual switches, and their network interconnections) is a problem which belongs to a class known to be NP-hard. Several approaches designed to run on CPUs have been proposed for reducing the search space and finding suitable allocation solutions. Most algorithms, however, face scalability issues when considering current cloud data centers comprising thousands of servers. To overcome these limitations, this work offers a set of allocation algorithms designed for Graphic Processing Units (GPUs). Experimental results evaluate the scalability of the algorithms and demonstrate their ability to handle three large-scale data center topologies.

关键词： Resource management Servers Cloud computing Graphics processing units Topology Clustering algorithms Network topology

来源：评论

学校读者我要写书评

暂无评论

Recommender systems in mobile apps for health a systematic review 12

Recommender systems in mobile apps for health a systematic r...

引用

12th Iberian Conference on Information Systems and Technologies, CISTI 2017

作者： Ferretto, Luciano Rodrigo Cervi, Cristiano Roberto De Marchi, Ana Carolina Bertoletti Graduate Program in Applied Computing - PPGCA/ICEG Universidade de Passo Fundo - UPF Passo Fundo Brazil

ISBN: (纸本)9789899843479

This paper aims to identify and analyze recommender systems developed for the health area, available in mobile applications. Therefore, literature was reviewed systematically from ACM, IEEE, Springer and Science Direct databases. 1006 studies were found, eight of which met the eligibility criteria. From the chosen studies, only one was not applied to the areas of nutrition and physical activity. The recommender techniques adopted were Collaborative Filtering and Content-based Filtering. The main mobile device identified was the Smartphone and the Operating System was Android. After analyzing the results, it was possible to realize that, although they are widely used in ecommerce, recommendation systems do not have many mobile healthcare applications, and the existing ones are recent. © 2017 AISTI.

关键词： Smartphones

来源：评论

学校读者我要写书评

暂无评论

Gamification strategies for mobile device applications: A systematic review 12

Gamification strategies for mobile device applications: A sy...

引用

12th Iberian Conference on Information Systems and Technologies, CISTI 2017

作者： Cechetti, Nathalia Pinto Biduki, Daiana De Marchi, Ana Carolina Bertoletti Graduate Program in Applied Computing - PPGCA/ICEG Universidade de Passo Fundo - UPF Passo Fundo Brazil

ISBN: (纸本)9789899843479

In the quest to engage and motivate users on the use of mobile applications, the gamification concept has been excelling in the market since incorporates game elements in a non-game context. Scoring systems, challenges, competitions and badges, are some of the elements implemented in many fields, such as health, education, ecological awareness, among others. In this context, this study aimed to systematically review available literature to identify gamification strategies used in mobile applications. A search was conducted in ACM, Science Direct and Scopus databases, from March to June 2016. A total of 402 studies were found, 23 of which met the eligibility criteria. The results demonstrated the heterogeneity of gamification elements being used and the impact they caused in the applications, especially as a motivational factor for users. This study provides the basis for future research on gamification methods and emphasizes the importance of this concept to increase engagement and provide enjoyment to users. © 2017 AISTI.

关键词： Mobile computing

来源：评论

学校读者我要写书评

暂无评论

3D DATA ACQUISITION USING STEREO CAMERA

3D DATA ACQUISITION USING STEREO CAMERA

引用

IEEE International Geoscience and Remote Sensing Symposium

作者： Evandro Kirsten Leonardo Campos Inocencio Mauricio Roberto Veronez Luiz Gonzaga da Silveira Fabiane Bordin Fernando Pinho Marson UNISINOS - São Leopoldo Advanced Visualization & Geoinformatics Laboratory RS Brazil Graduate Program on Applied Computing - UNISINOS São Leopoldo RS Brazil

Computer vision systems allow digital reconstruction of targets by capturing information through remote sensors such as video cameras and scanners. In this context, the objective of this work was to evaluate the capacity and quality of three-dimensional reconstruction of static targets using the ZED stereoscopic camera. For this goal, we took images of several environments and objects with different surfaces, textures, lighting, distances and acquisition speeds. The results were compared with high-density and high precision point clouds obtained from the targets using a Leica Viva TS15 total station. The data were processed in the CloudCompare software to calculate the displacement between the models generated by the camera and the total station. Under certain circumstances, this technology is able to reconstruct three-dimensional objects and environments with an error of a few centimeters.

关键词：

来源：评论

学校读者我要写书评

暂无评论

FUTURE-AI: International consensus guideline for trustworthy and deployable artificial intelligence in healthcare

arXiv

引用

arXiv 2023年

作者： Lekadir, Karim Feragen, Aasa Fofanah, Abdul Joseph Frangi, Alejandro F. Buyx, Alena Emelie, Anais Lara, Andrea Porras, Antonio R. Chan, An-Wen Navarro, Arcadi Glocker, Ben Botwe, Benard O. Khanal, Bishesh Beger, Brigit Wu, Carol C. Cintas, Celia Langlotz, Curtis P. Rueckert, Daniel Mzurikwao, Deogratias Fotiadis, Dimitrios I. Zhussupov, Doszhan Ferrante, Enzo Meijering, Erik Weicken, Eva González, Fabio A. Asselbergs, Folkert W. Prior, Fred Krestin, Gabriel P. Collins, Gary S. Tegenaw, Geletaw S. Kaissis, Georgios Misuraca, Gianluca Tsakou, Gianna Dwivedi, Girish Kondylakis, Haridimos Jayakody, Harsha Woodruf, Henry C. Mayer, Horst Joachim Aerts, Hugo JWL Walsh, Ian Chouvarda, Ioanna Buvat, Irène Tributsch, Isabell Rekik, Islem Duncan, James Kalpathy-Cramer, Jayashree Zahir, Jihad Park, Jinah Mongan, John Gichoya, Judy W. Schnabel, Julia A. Kushibar, Kaisar Riklund, Katrine Mori, Kensaku Marias, Kostas Amugongo, Lameck M. Fromont, Lauren A. Maier-Hein, Lena Alberich, Leonor Cerdá Rittner, Leticia Phiri, Lighton Marrakchi-Kacem, Linda Donoso-Bach, Lluís Martí-Bonmatí, Luis Cardoso, M. Jorge Bobowicz, Maciej Shabani, Mahsa Tsiknakis, Manolis Zuluaga, Maria A. Bielikova, Maria Fritzsche, Marie-Christine Camacho, Marina Linguraru, Marius George Wenzel, Markus De Bruijne, Marleen Tolsgaard, Martin G. Ghassemi, Marzyeh Ashrafuzzaman, Md Goisauf, Melanie Yaqub, Mohammad Abadía, Mónica Cano Mahmoud, Mukhtar M.E. Elattar, Mustafa Rieke, Nicola Papanikolaou, Nikolaos Lazrak, Noussair Díaz, Oliver Salvado, Olivier Pujol, Oriol Sall, Ousmane Guevara, Pamela Gordebeke, Peter Lambin, Philippe Brown, Pieta Abolmaesumi, Purang Dou, Qi Lu, Qinghua Osuala, Richard Nakasi, Rose Zhou, S. Kevin Napel, Sandy Colantonio, Sara Albarqouni, Shadi Joshi, Smriti Carter, Stacy Klein, Stefan Petersen, Steffen E. Aussó, Susanna Awate, Suyash Raviv, Tammy Riklin Cook, Tessa Mutsvangwa, Tinashe E.M. Rogers, Wendy A. Niessen, Wiro J. Puig-Bosch, Xènia Zeng, Yi Mohammed, Yunusa G. Aquino, Yves Saint James Salahuddin, Zohaib Starmans, Martijn P.A. Department de Matemàtiques i Informàtica Universitat de Barcelona Barcelona Spain Barcelona Spain DTU Compute Technical University of Denmark Kgs Lyngby Denmark Department of Mathematics and Computer Science Faculty of Science and Technology Milton Margai Technical University Freetown Sierra Leone Center for Computational Imaging & Simulation Technologies in Biomedicine Schools of Computing and Medicine University of Leeds Leeds United Kingdom Cardiovascular Science and Electronic Engineering Departments KU Leuven Leuven Belgium Institute of History and Ethics in Medicine Technical University of Munich Munich Germany Faculty of Engineering of Systems Informatics and Sciences of Computing Galileo University Guatemala City Guatemala Department of Biostatistics and Informatics Colorado School of Public Health University of Colorado Anschutz Medical Campus AuroraCO United States Department of Medicine Women’s College Research Institute University of Toronto Toronto Canada Universitat Pompeu Fabra BarcelonaBeta Brain Research Center Barcelona Spain Department of Computing Imperial College London London United Kingdom School of Biomedical & Allied Health Sciences University of Ghana Accra Ghana Department of Midwifery & Radiography School of Health & Psychological Sciences City University of London United Kingdom Kathmandu Nepal European Heart Network Brussels Belgium Department of Thoracic Imaging University of Texas MD Anderson Cancer Center Houston United States IBM Research Africa Nairobi Kenya Departments of Radiology Medicine and Biomedical Data Science Stanford University School of Medicine Stanford United States Institute for AI and Informatics in Medicine Klinikum rechts der Isar Technical University Munich Munich Germany Department of Computing Imperial College London London United Kingdom Muhimbili University of Health and Allied Sciences Dar es Salaam Tanzania United Republic of Ioannina Greece Almaty AI Lab Almaty Kazakhstan

Background: Despite major advances in artificial intelligence (AI) research for healthcare, the deployment and adoption of AI technologies remain limited in clinical practice. In recent years, concerns have been raised about the clinical, technical, ethical and legal risks associated with healthcare AI. To increase adoption in the real world, it is essential that AI technologies are trusted and accepted by patients, clinicians, health organisations and authorities. This paper describes the FUTURE-AI framework as the first international consensus guideline for trustworthy AI in healthcare. Methods: The FUTURE-AI consortium was founded in 2021 and now comprises 117 interdisciplinary experts from 50 countries representing all continents, including AI scientists, clinical researchers, biomedical ethicists, and social scientists. Over a two-year period, the consortium established guiding principles and best practices for trustworthy and deployable AI through an iterative process comprising an in-depth literature review, a modified Delphi survey, and online consensus meetings. Findings: The FUTURE-AI framework was established based on six guiding principles for trustworthy AI in healthcare, i.e. Fairness, Universality, Traceability, Usability, Robustness and Explainability. Through consensus, a set of 30 best practices were defined, addressing technical, clinical, socio-ethical and legal dimensions of trustworthy AI. The recommendations cover the entire lifecycle of healthcare AI, from design, development and validation to regulation, deployment, and monitoring. Interpretation: FUTURE-AI is a structured, risk-informed framework which provides guidance for constructing healthcare AI tools that will be trusted, deployed and adopted in real-world clinical practice. Researchers are encouraged to take the recommendations into account in proof-of-concept stages to facilitate future translation towards clinical practice of healthcare AI. Copyright © 2023, The Authors. All rights

关键词： Clinical research

来源：评论

学校读者我要写书评

暂无评论

An Adjustable Face Recognition System for Illumination Compensation Based on Differential Evolution 44th

An Adjustable Face Recognition System for Illumination Compe...

引用

Conferencia Latinoamericana En Informatica (CLEI)

作者： Guilherme Felippe Plichoski Chidambaram Chidambaram Rafael Stubs Parpinelli Graduate Program in Applied Computing State University of Santa Catarina Joinville Santa Catarina Brazil Department of Production Engineering State University of Santa Catarina Joinville Brazil

ISBN: (纸本)9781728104386

It is well known that face recognition (FR) systems cannot perform well under uncontrolled conditions, but there are no general and robust approaches with total immunity to all conditions. Hence, we present an adjustable FR framework with the aid of the Differential Evolution (DE) optimization algorithm. This approach implements several preprocessing and feature extraction techniques aiming to compensate the illumination variation. The main feature of the present work stands on the use of the DE which is responsible for choosing which strategies to use, as well as tunning the parameters involved. In this case study, we aim to address the illumination compensation problem applying on the well known Yale Extended B face dataset. According to the proposed FR framework, the DE can choose any combination of the following techniques and tune its necessary parameters achieving optimized values: the Gamma Intensity Correction (GIC), the Wavelet-based Illumination Normalization (WBIN), the Gaussian Blur, the Laplacian Edge Detection, the Discrete Wavelet Transform (DWT), the Discrete Cosine Transform (DCT), and the Local Binary Patterns (LBP). Our experimental analysis confirms that the proposed approach is suitable for FR using images under varying conditions. It is proved by the average recognition rate of 99.95% obtained using four different datasets.

关键词： Lighting Feature extraction Discrete wavelet transforms Discrete cosine transforms Optimization Image edge detection

来源：评论

学校读者我要写书评

暂无评论

Virtual Infrastructures on the Move: Containers and Virtual Network Migration

Virtual Infrastructures on the Move: Containers and Virtual ...

引用

Conferencia Latinoamericana En Informatica (CLEI)

作者： Euclides Cardoso Charles C. Miers Maurício A. Pillon Fernando Redigolo Guilherme P. Koslovski Graduate Program in Applied Computing – Santa Catarina State University – Joinville SC – Brazil Universidade de Sao Paulo Sao Paulo SÃ£o Paulo BR

ISBN: (纸本)9781728104386

The cloud computing model enables users to view computational resources as unlimited and that can be dynamically reserved. In addition, users are charged according to a contracted configuration and effective reservation time. Thus, it became possible to dynamically provision Virtual Infrastructures (VIs) composed of virtual machines, containers and virtualized network resources. Due to the flexibility in resource provisioning and configuration, VI is being increasingly adopted for hosting data storage services, development platforms and distributed applications. However, when migrating applications to a cloud, users are faced with a significant amount of providers, brokers and services offered. Above all, cloud computing technologies, although innovative, do not ease the migration of virtualized resources between distinct providers, inducing in vendor lock-in. A wide range of cloud providers, APIs, models and management tools further limit the development of VI migration solutions between providers, characterizing an open challenge. This work proposes a mechanism to perform VI migration among providers, based on an architecture agnostic to source and destination providers, as well as VI-hosted applications. In addition, a prototype based on Docker containers and OpenStack clouds was developed both to validate the proposed mechanism and to serve as a reference implementation.

关键词： IP networks Cloud computing Containers Computational modeling Data centers Computer architecture

来源：评论

学校读者我要写书评

暂无评论

A Proposal for Postpartum Support Based on Natural Language Generation Model

A Proposal for Postpartum Support Based on Natural Language ...

引用

International Conference on Computational Science and Computational Intelligence (CSCI)

作者： João Luis Zeni Montenegro Cristiano André Da Costa Rodrigo Da Rosa Righi Alex Roehrs Elson Romeu Farias Universidade do Vale do Rio dos Sinos Sao Leopoldo Brazil SOFTWARELAB Applied Computing Graduate Program Universidade do Vale do Rio dos Sinos Sao Leopoldo Brazil

ISBN: (纸本)9781728113616

This article presents a Multifaceted Natural Language Generation Model to help women in a postpartum. This proposal supports speech and text interactions, developing responses through an ontology model and retrieval based-method techniques oriented to the welfare of women after the birth of their baby. We show a case study, introducing an architecture model of conversational agents, a scenario and a simulation of this proposal. Our results presented a better performance in response time generated from a retrieval based-method(two seconds), and similar response accuracy, slightly better for semantic queries (20% better).

关键词： Pediatrics Natural languages Ontologies Pregnancy Task analysis Proposals Semantics

来源：评论

学校读者我要写书评

暂无评论

MOSIS - Multi-outcrop sharing & interpretation system 37

MOSIS - Multi-outcrop sharing & interpretation system

引用

37th Annual IEEE International Geoscience and Remote Sensing Symposium, IGARSS 2017

作者： Gonzaga, Luiz Veronez, Mauricio Roberto Alves, Demetrius Nunes Bordin, Fabiane Kannenberg, Gabriel Lanzer Marson, Fernando P. Tognoli, Francisco M.W. Inocencio, Leonardo C. Graduate Program on Applied Computing UNISINOS São Leopoldo RS Brazil Graduate Program on Geology UNISINOS São Leopoldo RS Brazil Advanced Visualization and Geoinformatics Laboratory UNISINOS São Leopoldo RS Brazil

ISBN: (纸本)9781509049516

The use of LiDAR and multiples digital images jointly with 3-D reconstruction techniques for creating 3-D models of natural outcrops and surfaces studies have increased dramatically in the last few years. These techniques have provided an enormous amount of data for interpretation by geoscientists. However, these researchers have no available software capable of offering a user experience comparable to the fieldwork. The majority of solutions have considered desktop systems, which presents inherent limitations due to the 2-D characteristics of displays and loss of immersion into the 3-D model, or up until expensive and complex stereoscopic based approaches to improve the 3-D user experience do not offer well suitable solutions. To address these limitations, this paper presents a low-cost completely disruptive solution for processing, visualizing, sharing and directly handling Digital Outcrop Models with the support of a full interpretation toolset, the MOSIS System. The proposed system provides a fully immersive computational environment, capable of teleporting virtually geoscientists to the fieldwork, giving an awareness of being there physically with an extensible toolset for the DOM's interpretation. Besides, desktop, web and mobile versions of MOSIS have been under development and fulfill the lack of tools for digital outcrop modeling. © 2017 IEEE.

关键词： Three-dimensional displays Geology Data visualization Solid modeling Tools Visualization Standards

来源：评论

学校读者我要写书评

暂无评论

EAVIRA: Energy-Aware Virtual Infrastructure Reallocation Algorithm

EAVIRA: Energy-Aware Virtual Infrastructure Reallocation Alg...

引用

Brazilian Symposium on computing System Engineering (SBESC)

作者： Denivy B. Ruck Maurício A. Pillon Charles C. Miers Guilherme P. Koslovski Department of Computer Science Graduate Program in Applied Computing

The elastic provisioning of Virtual Infrastructures (VIs) enables a dynamic management of cloud resources (computing and communication) in order to meet the hosted application's requirements. Thus, to perform elasticity requests, providers usually rely on reallocation mechanisms and policies. The concerns regarding the environment and the operational costs indicate energy consumption of the data centers as recurring topic in providers policies. Moreover, energy-aware provisioning is beneficial for tenants also. Recent cost models have introduced an implicit incentive to use computing and networking resources just when need to avoid high rent costs. However, reallocation and elasticity requests can unbalance the Data Center (DC) unnecessarily increasing the number of active servers. In this paper we propose EAVIRA algorithm, which takes into account the proportional sharing of CPU usage of DC servers to calculate individual usage costs to: disable idle equipments, and reallocate VIs. EAVIRA acts on online requests for elasticity configuration and performs an offline load balancing, triggered by the Infrastructure as a Service (IaaS) provider. Our experimental analysis indicates a reduction of energy consumption and an increasing on acceptance ratio of allocation requests.

关键词： Resource management Servers Energy consumption Elasticity Cloud computing Load management Computational modeling

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：