检索结果-内蒙古大学图书馆

Evaluating and Constraining Hardware Assertions with Absent Scenarios

Journal of computer Science & technology 2020年第5期35卷 1198-1216页

作者： Hui-Na Chao Hua-Wei Li Xiaoyu Song Tian-Cheng Wang Xiao-Wei Li State Key Laboratory of Computer Architecture Institute of Computing TechnologyChinese Academy of Sciences Beijing 100190China University of Chinese Academy of Sciences Beijing 100049China Peng Cheng Laboratory Shenzhen 518052China Department of Electrical and Computing Engineering Portland State UniversityPortlandOR 97207U.S.A.

Mining from simulation data of the golden model in hardware design verification is an effective solution to assertion *** the simulation data is inherently incomplete,it is necessary to evaluate the truth values of the mined *** paper presents an approach to evaluating and constraining hardware assertions with absent scenarios.A Belief-fail Rate metric is proposed to predict the truth/falseness of generated *** considering both the occurrences of free variable assignments and the conflicts of absent scenarios,we use the metric to sort true assertions in higher ranking and false assertions in lower *** Belief-failRate guided assertion constraining method leverages the quality of generated *** experimental results show that the Belief-failRate framework performs better than the existing *** addition,the assertion evaluating and constraining procedure can find more assertions that cover new design functionality in comparison with the previous methods.

关键词： hardware formal verification assertion generation data mining assertion evaluation assertion coverage

来源：评论

学校读者我要写书评

暂无评论

Deep Learning-Based Object Pose Estimation: A Comprehensive Survey

arXiv

引用

arXiv 2024年

作者： Liu, Jian Sun, Wei Yang, Hui Zeng, Zhiwen Liu, Chongpei Zheng, Jin Liu, Xingyu Rahmani, Hossein Sebe, Nicu Mian, Ajmal The National Engineering Research Center for Robot Visual Perception and Control Technology College of Electrical and Information Engineering the State Key Laboratory of Advanced Design and Manufacturing for Vehicle Body Hunan University Changsha410082 China The School of Architecture and Art Central South University Changsha410082 China The Department of Automation Tsinghua University Beijing100084 China The School of Computing and Communications Lancaster University LA1 4YW United Kingdom The Department of Information Engineering and Computer Science University of Trento Trento38123 Italy The Department of Computer Science The University of Western Australia WA6009 Australia

Object pose estimation is a fundamental computer vision problem with broad applications in augmented reality and robotics. Over the past decade, deep learning models, due to their superior accuracy and robustness, have increasingly supplanted conventional algorithms reliant on engineered point pair features. Nevertheless, several challenges persist in contemporary methods, including their dependency on labeled training data, model compactness, robustness under challenging conditions, and their ability to generalize to novel unseen objects. A recent survey discussing the progress made on different aspects of this area, outstanding challenges, and promising future directions, is missing. To fill this gap, we discuss the recent advances in deep learning-based object pose estimation, covering all three formulations of the problem, i.e., instance-level, category-level, and unseen object pose estimation. Our survey also covers multiple input data modalities, degrees-of-freedom of output poses, object properties, and downstream tasks, providing the readers with a holistic understanding of this field. Additionally, it discusses training paradigms of different domains, inference modes, application areas, evaluation metrics, and benchmark datasets, as well as reports the performance of current state-of-the-art methods on these benchmarks, thereby facilitating the readers in selecting the most suitable method for their application. Finally, the survey identifies key challenges, reviews the prevailing trends along with their pros and cons, and identifies promising directions for future research. We also keep tracing the latest works at Awesome-Object-Pose-Estimation. Copyright © 2024, 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 the exploitation of neuroevolutionary information: Analyzing the past for a more efficient future

arXiv

引用

arXiv 2021年

作者： Garciarena, Unai Lourenço, Nuno Machado, Penousal Santana, Roberto Mendiburu, Alexander Department of Computer Science and Artificial Intelligence University of the Basque Country Donostia-San Sebastian Spain CISUC Department of Informatics Engineering Coimbra Portugal Department of Computer Architecture and Technology University of the Basque Country Donostia-San Sebastian Spain

Neuroevolutionary algorithms, automatic searches of neural network structures by means of evolutionary techniques, are computationally costly procedures. In spite of this, due to the great performance provided by the architectures which are found, these methods are widely applied. The final outcome of neuroevolutionary processes is the best structure found during the search, and the rest of the procedure is commonly omitted in the literature. However, a good amount of residual information consisting of valuable knowledge that can be extracted is also produced during these searches. In this paper, we propose an approach that extracts this information from neuroevolutionary runs, and use it to build a metamodel that could positively impact future neural architecture searches. More specifically, by inspecting the best structures found during neuroevolutionary searches of generative adversarial networks with varying characteristics (e.g., based on dense or convolutional layers), we propose a Bayesian network-based model which can be used to either find strong neural structures right away, conveniently initialize different structural searches for different problems, or help future optimization of structures of any type to keep finding increasingly better structures where uninformed methods get stuck into local optima. © 2021, CC BY.

关键词： Generative adversarial networks

来源：评论

学校读者我要写书评

暂无评论

Evaluating Large Language Model–Supported Instructions for Medication Use: First Steps Toward a Comprehensive Model

Mayo Clinic Proceedings: Digital Health

引用

Mayo Clinic Proceedings: Digital Health 2024年第4期2卷 632-644页

作者： Reis, Zilma Silveira Nogueira Pagano, Adriana Silvina Ramos de Oliveira, Isaias Jose Dias, Cristiane dos Santos Lage, Eura Martins Mineiro, Erico Franco Varella Pereira, Glaucia Miranda de Carvalho Gomes, Igor Basilio, Vinicius Araujo Cruz-Correia, Ricardo João de Jesus, Davi dos Reis de Souza Júnior, Antônio Pereira da Rocha, Leonardo Chaves Dutra Health Informatics Center Faculty of Medicine Universidade Federal de Minas Gerais Minas Gerais Belo Horizonte Brazil Arts Faculty Universidade Federal de Minas Gerais Minas Gerais Belo Horizonte Brazil Department of Pediatrics Faculty of Medicine Universidade Federal de Minas Gerais Minas Gerais Belo Horizonte Brazil Department of Design Technology School of Architecture Universidade Federal de Minas Gerais Minas Gerais Belo Horizonte Brazil Department of Obstetrics and Gynecology Faculty of Medical Sciences Universidade Estadual de Campinas São Paulo Campinas Brazil Departamento de Medicina da Comunidade Informação e Decisão em Saúde National Secretary of Primary Care of the Brazilian Ministry of Health Brasília Brazil MEDCIDS Porto University Porto Portugal Department of Computer Science Universidade Federal de São João Del Rei São João del Rei Minas Gerais Brazil

Objective: To assess the support of large language models (LLMs) in generating clearer and more personalized medication instructions to enhance e-prescription. Patients and Methods: We established patient-centered guidelines for adequate, acceptable, and personalized directions to enhance e-prescription. A dataset comprising 104 outpatient scenarios, with an array of medications, administration routes, and patient conditions, was developed following the Brazilian national e-prescribing standard. Three prompts were submitted to a closed-source LLM. The first prompt involved a generic command, the second one was calibrated for content enhancement and personalization, and the third one requested bias mitigation. The third prompt was submitted to an open-source LLM. Outputs were assessed using automated metrics and human evaluation. We conducted the study between March 1, 2024 and September 10, 2024. Results: Adequacy scores of our closed-source LLM's output showed the third prompt outperforming the first and second one. Full and partial acceptability was achieved in 94.3% of texts with the third prompt. Personalization was rated highly, especially with the second and third prompts. The 2 LLMs showed similar adequacy results. Lack of scientific evidence and factual errors were infrequent and unrelated to a particular prompt or LLM. The frequency of hallucinations was different for each LLM and concerned prescriptions issued upon symptom manifestation and medications requiring dosage adjustment or involving intermittent use. Gender bias was found in our closed-source LLM's output for the first and second prompts, with the third one being bias-free. The second LLM's output was bias-free. Conclusion: This study demonstrates the potential of LLM-supported generation to produce prescription directions and improve communication between health professionals and patients within the e-prescribing system. © 2024 The Authors

关键词： AI artificial intelligence EHR electronic health record ICPC-2 International Classification of Primary Care, 2nd edition LLM large language model e-SUS electronic Sistema Único de Saúde

来源：评论

学校读者我要写书评

暂无评论

HealthyBlockchain for Global Patients

引用

computers, Materials & Continua 2021年第8期68卷 2431-2449页

作者： Shada A.Alsalamah Hessah A.Alsalamah Thamer Nouh Sara A.Alsalamah College of Computer and Information Sciences King Saud UniversityRiyadh11451Saudi Arabia Digital Health and Innovation Science DivisionWorld Health OrganizationGenevaCH-1211Switzerland MIT Department of Mechanical Engineering Massachusetts Institute of Technology(MIT)Cambridge02139MAUSA College of Engineering and Architecture Al Yamamah UniversityRiyadh11451Saudi Arabia Trauma and Acute Care Surgery Unit College of MedicineKing Saud UniversityRiyadh11451Saudi Arabia College of Computer and Information Sciences Al Imam Mohammad Ibn Saud Islamic UniversityRiyadh13318Saudi Arabia

An emerging healthcare delivery model is enabling a new era of clinical care based on well-informed decision-making *** healthcare information systems(HISs)fall short of adopting this model due to a conflict between information security needed to implement the new model and those already enforced locally to support traditional care ***,in recent times,the healthcare sector has shown a substantial interest in the potential of using blockchain technology for providing quality care to *** blockchain solution proposed so far has fully addressed emerging cross-organization information-sharing needs in *** this paper,we aim to study the use of blockchain in equipping struggling HISs to cope with the demands of the new healthcare delivery model,by proposing HealthyBlockchain as a granular patient-centered ledger that digitally tracks a patient’s medical transactions all along the treatment pathway to support the care *** patient-centered ledger is a neutral tamper-proof trail timestamp block sequence that governs distributed patient information across the decentralized discrete *** connects patients,clinicians,and healthcare providers to facilitate a transparent,trustworthy,and secure supporting platform.

关键词： Blockchain eHealth electronic health record global patient healthcare information system information security legacy system patient-centered care privacy smart contract trust

来源：评论

学校读者我要写书评

暂无评论

Energy-aware load balancing of parallel evolutionary algorithms with heavy fitness functions in heterogeneous CPU-GPU architectures

Energy-aware load balancing of parallel evolutionary algorit...

引用

作者： Escobar, Juan José Ortega, Julio Díaz, Antonio Francisco González, Jesús Damas, Miguel Department of Computer Architecture and Technology CITIC University of Granada Spain

By means of the availability of mechanisms such as Dynamic Voltage and Frequency Scaling (DVFS) and heterogeneous architectures including processors with different power consumption profiles, it is possible to devise scheduling algorithms that are aware of both runtime and energy consumption in parallel programs. In this paper, we propose and evaluate a multi-objective (more specifically, a bi-objective) approach to distribute the workload among the processing cores in a given heterogeneous parallel CPU-GPU architecture. The aim of this distribution may be either to save energy without increasing the running time or to reach a trade-off among time and energy consumption. The parallel programs considered here are master-worker evolutionary algorithms where the evaluation of the fitness function for the individuals in the population demands the most part of the computing time. As many useful bioinformatics and data mining applications exhibit this kind of parallel profile, the proposed energy-aware approach for workload scheduling could be frequently applied. © 2018 John Wiley & Sons, Ltd.

关键词： Energy utilization

来源：评论

学校读者我要写书评

暂无评论

EPRD: Exploiting prior knowledge for evidence-providing automatic rumor detection

引用

Neurocomputing 2024年 563卷

作者： Li, Jiawen Li, Ronghui Ni, Shiwen Kao, Hung-Yu Naval Architecture and Shipping College Guangdong Ocean University Guangdong Zhanjiang524000 China Technical Research Center for Ship Intelligence and Safety Engineering of Guangdong Province Guangdong Zhanjiang524000 China Intelligent Knowledge Management Lab National Cheng Kung University Tainan Taiwan Department of Computer Science and Information Engineering National Cheng Kung University Tainan Taiwan Shenzhen Institute of Advanced Technology Chinese Academy of Sciences Shenzhen China

With the prevalence of social media platforms, rumors have been a serious social problem. Notably, existing rumor detection methods simply provide detection labels while ignoring their explanation. However, illustrating the reasons why a suspicious statement is a rumor is essential. To address this realistic scenario, we propose a novel Evidence-Providing Rumor Detection model called EPRD. EPRD incorporates a wide variety of information from both prior knowledge sources and current comments. It also learns bilaterally friendly representations for interpretable rumor detection. EPRD first retrieves evidence from prior knowledge sources and checks the relationship between the given statement and its evidence. Our model then constructs two heterogeneous graph objects to simulate the propagation layout of the current comments and evidence relationships. Finally, EPRD integrates the GraphSAGE component and attention mechanism to detect rumors. To the best of our knowledge, we propose the first model that incorporates prior knowledge to verify rumors and boost credibility. Experiments on two real-world Twitter datasets demonstrate that EPRD consistently exhibits the best rumor detection performance. Moreover, EPRD outperforms other baselines in the early rumor detection task. © 2023

关键词： Graph neural networks

来源：评论

学校读者我要写书评

暂无评论

A cluster of FPAAs to recognize images using neural networks

TechRxiv

引用

TechRxiv 2021年

作者： Daniel, García Moreno Alberto, Del Barrio A. Guillermo, Botella Jennifer, Hasler The Department of Computer Architecture and Automation Complutense University of Madrid Madrid28040 Spain Georgia Institute of Technology GA Atlanta30332-0250 United States

Analog computing has been recovering its relevance in the recent years. FPAAs are the equivalent to FPGAs but in the analog domain. The main drawback of FPAAs is their reduced integration capacity. In order to increase the amount of analog resources, in this paper a cluster of 40 FPAAs is proposed. As a use case, a 19-8-6-4 feedforward Neural Network has been implemented on such cluster. With the help of a DCT-based software framework, this NN is able to classify 28x28 MNIST images. Results show that the analog network is able to obtain almost the same results as the software baseline network. I © 2021, CC BY-NC-SA.

关键词： computer programming

来源：评论

学校读者我要写书评

暂无评论

Cacheap:Portable and Collaborative I/O Optimization for Graph Processing

引用

Journal of computer Science & technology 2019年第3期34卷 690-706页

作者： Peng Zhao Chen Ding Lei Liu Jiping Yu Wentao Han Xiao-Bing Feng State Key Laboratory of Computer Architecture Institute of Computing TechnologyChinese Academy of Sciences Beijing 100190China University of Chinese Academy of Sciences Beijing 100049China Department of Computer Science University of RochesterRochester 14623U.S.A. Department of Computer Science and Technology Tsinghua UniversityBeijing 100084China

Increasingly there is a need to process graphs that are larger than the available memory on today's *** systems have been developed with grapli representations that are efficient and compact for out-of-core processing.A necessary task in these systems is memory *** paper presents a system called Cacheap which automatically and efficiently manages the available memory to maximize the speed of grapli processing,minimize the amount of disk access,and maximize the utilization of memory for graph *** has a simple interface that can be easily adopted by existing graph *** paper describes the new system,uses it in recent graph engines,and demonstrates its integer factor improvements in the speed of large-scale grapli processing.

关键词： out-of-core graph processing system I/O optimization memory cache graph analytics locality

来源：评论

学校读者我要写书评

暂无评论

Non-Convex Potential Games for Finding Global Solutions to Sensor Network Localization

Non-Convex Potential Games for Finding Global Solutions to S...

引用

European Control Conference (ECC)

作者： Gehui Xu Guanpu Chen Yiguang Hong Baris Fidan Thomas Parisini Karl H. Johansson Key Laboratory of Systems and Control Academy of Mathematics and Systems Science Beijing China Division of Decision and Control Systems School of Electrical Engineering and Computer Science KTH Royal Institute of Technology Stockholm Sweden Department of Control Science and Engineering Tongji University Shanghai China Shanghai Research Institute for Intelligent Autonomous Systems Shanghai China Department of Mechanical and Mechatronics Engineering University of Waterloo Waterloo ON Canada Department of Electrical and Electronic Engineering Imperial College London London UK Department of Engineering and Architecture University of Trieste Trieste Italy

ISBN: (数字)9783907144107

ISBN: (纸本)9798331540920

Sensor network localization (SNL) problems require determining the physical coordinates of all sensors in a network. This process relies on the global coordinates of anchors and the available measurements between non-anchor and anchor nodes. Attributed to the intrinsic non-convexity, obtaining a globally optimal solution to SNL is challenging, as well as implementing corresponding algorithms. In this paper, we formulate a non-convex multi-player potential game for a generic SNL problem to investigate the identification condition of the global Nash equilibrium (NE) therein, where the global NE represents the global solution of SNL. We employ canonical duality theory to transform the non-convex game into a complementary dual problem. Then we develop a conjugation-based algorithm to compute the stationary points of the complementary dual problem. On this basis, we show an identification condition of the global NE: the stationary point of the proposed algorithm satisfies a duality relation. Finally, simulation results are provided to validate the effectiveness of the theoretical results.

关键词： Location awareness Coordinate measuring machines Simulation Current measurement Noise Europe Games

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：