检索结果-内蒙古大学图书馆

18th IFIP WG 10.3 International Conference on Network and Parallel Computing, NPC 2021

作者： Zhang, Yingxue Fan, Guisheng Yu, Huiqun Chen, Xingpeng Department of Computer Science and Engineering East China University of Science and Technology Shanghai China Shanghai Key Laboratory of Computer Software Evaluating and Testing Shanghai China

ISBN: (纸本)9783030935702

Reliability requirement assurance is an important prerequisite for application execution in the cloud. Although copy management can improve the reliability of applications, it also brings a series of resource waste and overhead issues. Therefore, the efficiency-first fault-tolerant algorithm (EFFT) with minimum execution cost in the cloud application is proposed. This algorithm minimizes the execution cost of the application under the constraints of reliability, and solves the problem of excessive overhead caused by too many copies. The EFFT algorithm is divided into two stages: initial allocation and dynamic adjustment. On the initial allocation of EFFT algorithm, a sorting rule is defined to determine the priority of tasks and instances. During the adjustment phase, by defining an actual efficiency ratio indicator to measure the cost-effectiveness of an instance, the EFFT algorithm makes a good trade-off between cost and reliability in order to minimize execution costs. Run our algorithm on randomly generated parallel applications of different scales and compare the experimental results with four advanced algorithms. The experiments show that the performance of the algorithm we proposed is better than the other algorithms in terms of execution cost and fault tolerance. © 2022, IFIP International Federation for Information Processing.

关键词： Fault tolerance

来源：评论

学校读者我要写书评

暂无评论

Rice Leaves Disease Diagnose Empowered with Transfer Learning

引用

computer systems science & Engineering 2022年第9期42卷 1001-1014页

作者： Nouh Sabri Elmitwally Maria Tariq Muhammad Adnan Khan Munir Ahmad Sagheer Abbas Fahad Mazaed Alotaibi College of Computer and Information Sciences Jouf UniversitySakaka72341Saudi Arabia Department of Computer Science Faculty of Computers and Artificial IntelligenceCairo University12613Egypt School of Computer Science National College of Business Administration and EconomicsLahore54000Pakistan Department of Computer Science Lahore Garrison UniversityLahore54000Pakistan Pattern Recognition and Machine Learning Lab Department of SoftwareGachon UniversitySeongnam13557Korea Department of Information System Faculty of Computing and Information TechnologyKing Abdulaziz UniversityJeddah21589Saudi Arabia

In the agricultural industry,rice infections have resulted in significant productivity and economic *** infections must be recognized early on to regulate and mitigate the effects of the *** diagnosis of disease severity effects or incidence can preserve production from quantitative and qualitative losses,reduce pesticide use,and boost ta country’s *** the health of a rice plant through its leaves is usually done as a manual ocular *** this manuscript,three rice plant diseases:Bacterial leaf blight,Brown spot,and Leaf smut,were identified using the Alexnet *** research shows that any reduction in rice plants will have a significant beneficial impact on alleviating global food hunger by increasing supply,lowering prices,and reducing production's environmental impact that affects the economy of any *** would be able to get more exact and faster results with this technology,allowing them to administer the most acceptable treatment *** Using Alex Net,the proposed approach achieved a 99.0%accuracy rate for diagnosing rice leaves disease.

关键词： Rice bacterial leaf blight brown spot leaf smut machine learning alexnet

来源：评论

学校读者我要写书评

暂无评论

Domain-Invariant Similarity Activation Map Contrastive Learning for Retrieval-Based Long-Term Visual Localization

引用

IEEE/CAA Journal of Automatica Sinica 2022年第2期9卷 313-328页

作者： Hanjiang Hu Hesheng Wang Zhe Liu Weidong Chen Department of Automation Shanghai Jiao Tong UniversityShanghai 200240China IEEE Department of Automation Institute of Medical RoboticsKey Laboratory of System Control and Information Processing of Ministry of EducationKey Laboratory of Marine Intelligent Equipment and System of Ministry of EducationShanghai Jiao Tong UniversityShanghai 200240China Department of Computer Science and Technology University of CambridgeCambridge CB30FDUnited Kingdom

Visual localization is a crucial component in the application of mobile robot and autonomous *** retrieval is an efficient and effective technique in image-based localization *** to the drastic variability of environmental conditions,e.g.,illumination changes,retrievalbased visual localization is severely affected and becomes a challenging *** this work,a general architecture is first formulated probabilistically to extract domain-invariant features through multi-domain image ***,a novel gradientweighted similarity activation mapping loss(Grad-SAM)is incorporated for finer localization with high *** also propose a new adaptive triplet loss to boost the contrastive learning of the embedding in a self-supervised *** final coarse-to-fine image retrieval pipeline is implemented as the sequential combination of models with and without Grad-SAM *** experiments have been conducted to validate the effectiveness of the proposed approach on the CMU-Seasons *** strong generalization ability of our approach is verified with the RobotCar dataset using models pre-trained on urban parts of the CMU-Seasons *** performance is on par with or even outperforms the state-of-the-art image-based localization baselines in medium or high precision,especially under challenging environments with illumination variance,vegetation,and night-time ***,real-site experiments have been conducted to validate the efficiency and effectiveness of the coarse-to-fine strategy for localization.

关键词： Deep representation learning place recognition visual localization

来源：评论

学校读者我要写书评

暂无评论

A Stimulus Analysis for Sustaining Attention of Video Lecture Learners 15th

A Stimulus Analysis for Sustaining Attention of Video Lectur...

引用

15th International Conference on computer science and its Applications, CSA 2023 and 17th KIPS International Conference on Ubiquitous Information Technologies and Applications, CUTE 2023

作者： Roh, Kyoungeui Park, Ji Su Kang, Jungho Shon, Jin Gon Advanced Convergence Technology Laboratory Korea National Open University Seoul Korea Republic of Department of Computer Science and Engineering Jeonju University Jeonju-si Korea Republic of Department of Software Engineering Baewha Woman University Seoul Korea Republic of Department of Computer Science Graduate School Korea National Open University Seoul Korea Republic of

ISBN: (纸本)9789819724468

There is a concern about the learner effectiveness in video lecture. The ability of learners to effectively engage is influenced by the time they can sustain their attention. However, learners watching video lectures often struggle to maintain their attention after a certain period of time. This is primarily because video lectures are created without taking into consideration the time learners can sustain their attention. This study aims to investigate what kind of stimuli could be presented to learners during video lectures to help them sustain their attention. This study designs five experimental stimuli to be presented during video lectures playback and measures the time learners sustain attention for each stimulus. The experimental results show that when video lecture learners are received simultaneous visual stimulus in the form of dynamic text and auditory stimulus in the form of voiceover, the time they sustain attention in video lectures is the longest. This suggests that presenting dynamic text and voiceover simultaneously during video lectures can be the most effective strategy to sustain learners’ attention. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2024.

关键词： Contrastive Learning

来源：评论

学校读者我要写书评

暂无评论

PriSTI: A Conditional Diffusion Framework for Spatiotemporal Imputation 39

PriSTI: A Conditional Diffusion Framework for Spatiotemporal...

引用

39th IEEE International Conference on Data Engineering, ICDE 2023

作者： Liu, Mingzhe Huang, Han Feng, Hao Sun, Leilei Du, Bowen Fu, Yanjie Beihang University State Key Laboratory of Software Development Environment Beijing100191 China University of Central Florida Department of Computer Science FL32816 United States

ISBN: (纸本)9798350322279

Spatiotemporal data mining plays an important role in air quality monitoring, crowd flow modeling, and climate forecasting. However, the originally collected spatiotemporal data in real-world scenarios is usually incomplete due to sensor failures or transmission loss. Spatiotemporal imputation aims to fill the missing values according to the observed values and the underlying spatiotemporal dependence of them. The previous dominant models impute missing values autoregressively and suffer from the problem of error accumulation. As emerging powerful generative models, the diffusion probabilistic models can be adopted to impute missing values conditioned by observations and avoid inferring missing values from inaccurate historical imputation. However, the construction and utilization of conditional information are inevitable challenges when applying diffusion models to spatiotemporal imputation. To address above issues, we propose a conditional diffusion framework for spatiotemporal imputation with enhanced prior modeling, named PriSTI. Our proposed framework provides a conditional feature extraction module first to extract the coarse yet effective spatiotemporal dependencies from conditional information as the global context prior. Then, a noise estimation module transforms random noise to realistic values, with the spatiotemporal attention weights calculated by the conditional feature, as well as the consideration of geographic relationships. PriSTI outperforms existing imputation methods in various missing patterns of different real-world spatiotemporal data, and effectively handles scenarios such as high missing rates and sensor failure. The implementation code is available at https://***/LMZZML/PriSTI. © 2023 IEEE.

关键词： Diffusion

来源：评论

学校读者我要写书评

暂无评论

Image Computation for Quantum Transition systems

Image Computation for Quantum Transition Systems

引用

Design, Automation and Test in Europe Conference and Exhibition

作者： Xin Hong Dingchao Gao Sanjiang Li Shenggang Ying Mingsheng Ying Key Laboratory of System Software (Chinese Academy of Sciences) and State Key Laboratory of Computer Science Institute of Software Chinese Academy of Sciences Beijing China Centre for Quantum Software and Information University of Technology Sydney Sydney Australia

ISBN: (数字)9783982674100

ISBN: (纸本)9798331534646

With the rapid progress in quantum hardware and software, the need for verification of quantum systems becomes increasingly crucial. While model checking is a dominant and very successful technique for verifying classical systems, its application to quantum systems is still an underdeveloped research area. This paper advances the development of model checking quantum systems by providing efficient image computation algorithms for quantum transition systems, which play a fundamental role in model checking. In our approach, we represent quantum circuits as tensor networks and design algorithms by leveraging the properties of tensor networks and tensor decision diagrams. Our experiments demonstrate that our contraction partition-based algorithm can greatly improve the efficiency of image computation for quantum transition systems.

关键词： Quantum system Tensors Europe Model checking software Hardware Partitioning algorithms Computational efficiency Quantum circuit

来源：评论

学校读者我要写书评

暂无评论

Measurement-based Verification of Quantum Markov Chains

arXiv

引用

arXiv 2024年

作者： Guan, Ji Feng, Yuan Turrini, Andrea Ying, Mingsheng Key Laboratory of System Software Chinese Academy of Sciences State Key Laboratory of Computer Science Institute of Software Beijing100190 China Department of Computer Science and Technology Tsinghua University Beijing100084 China Institute of Intelligent Software Guangzhou511458 China The Centre for Quantum Software and Information University of Technology SydneyNSW2007 Australia

Model-checking techniques have been extended to analyze quantum programs and communication protocols represented as quantum Markov chains, an extension of classical Markov chains. To specify qualitative temporal properties, a subspace-based quantum temporal logic is used, which is built on Birkhoff–von Neumann atomic propositions. These propositions determine whether a quantum state is within a subspace of the entire state space. In this paper, we propose the measurement-based linear-time temporal logic MLTL to check quantitative properties. MLTL builds upon classical linear-time temporal logic (LTL) but introduces quantum atomic propositions that reason about the probability distribution after measuring a quantum state. To facilitate verification, we extend the symbolic dynamics-based techniques for stochastic matrices described by Agrawal et al. (JACM 2015) to handle more general quantum linear operators (super-operators) through eigenvalue analysis. This extension enables the development of an efficient algorithm for approximately model checking a quantum Markov chain against an MLTL formula. To demonstrate the utility of our model-checking algorithm, we use it to simultaneously verify linear-time properties of both quantum and classical random walks. Through this verification, we confirm the previously established advantages discovered by Ambainis et al. (STOC 2001) of quantum walks over classical random walks and discover new phenomena unique to quantum walks. © 2024, CC BY.

关键词： Eigenvalues and eigenfunctions

来源：评论

学校读者我要写书评

暂无评论

Glowworm Swarm Optimization Algorithm for Retrieval of High Utility Itemsets

Glowworm Swarm Optimization Algorithm for Retrieval of High ...

引用

Smart systems for Electrical, Electronics, Communication and computer Engineering (ICSSEECC), International Conference on

作者： C. Sivamathi G.S. Karthick S. Vijayarani Department of Computer Science PSG College of Arts & Science Coimbatore India Department of Software System PSG College of Arts & Science Coimbatore India Department of Computer Science Bharathiar University Coimbatore India

ISBN: (数字)9798350378177

ISBN: (纸本)9798350378184

Utility mining is a recent mounting field in data mining. It has many research directions like Negative profit, On-shelf utility mining, rare utility itemset mining, utility based Association rule mining, Utility Sequence mining etc. All such research areas focus on single level transaction database. A very little attention was paid towards multi-level utility mining. In this work, high utility itemsets are generated from Multi level database, using Glowworm Swarm Optimization algorithm. This algorithm consists of four phases: Initialization, Fitness function, Luciferin-update phase and Movement phase. These phases are made to handle transaction database and are implemented to retrieve high utility itemsets. In experimental results the proposed algorithm was compared with existing PSO, GA, ACO optimization algorithms. Execution time, Memory space occupied and number of high utility itemsets retrieved are considered as performance measures.

关键词： Itemsets Insects Semantics Glowworm swarm optimization Extraterrestrial measurements Time measurement Association rule learning

来源：评论

学校读者我要写书评

暂无评论

UltraEdit: Instruction-based Fine-Grained Image Editing at Scale 38

UltraEdit: Instruction-based Fine-Grained Image Editing at S...

引用

38th Conference on Neural Information Processing systems, NeurIPS 2024

作者： Zhao, Haozhe Ma, Xiaojian Chen, Liang Si, Shuzheng Wu, Rujie An, Kaikai Yu, Peiyu Zhang, Minjia Li, Qing Chang, Baobao National Key Laboratory for Multimedia Information Processing Peking University China State Key Laboratory of General Artificial Intelligence BIGAI China School of Software and Microelectronics Peking University China Department of Computer Science and Technology Tsinghua University China School of Computer Science Peking University China UCLA United States UIUC United States

This paper presents ULTRAEDIT, a large-scale (~4M editing samples), automatically generated dataset for instruction-based image editing. Our key idea is to address the drawbacks in existing image editing datasets like InstructPix2Pix [10] and MagicBrush [71], and provide a systematic approach to producing massive and high-quality image editing samples. ULTRAEDIT offers several distinct advantages: 1) It features a broader range of editing instructions by leveraging the creativity of large language models (LLMs) alongside in-context editing examples from human raters;2) Its data sources are based on real images, including photographs and artworks, which provide greater diversity and reduced bias compared to datasets solely generated by text-to-image models;3) It also supports region-based editing, enhanced by high-quality, automatically produced region annotations. Our experiments show that canonical diffusion-based editing baselines trained on ULTRAEDIT set new records on MagicBrush and Emu-Edit benchmarks. Our analysis further confirms the crucial role of real image anchors and region-based editing data. The dataset, code, and models are available in ***/pkunlp-icler/UltraEdit. © 2024 Neural information processing systems foundation. All rights reserved.

关键词：

来源：评论

学校读者我要写书评

暂无评论

AI-Based Child Care Parental Control system 4

AI-Based Child Care Parental Control System

引用

4th International Conference on Advancements in Computing, ICAC 2022

作者： Jayasekara, Udara Maniyangama, Hansindu Vithana, Kalhan Weerasinghe, Tharana Wijekoon, Janaka Panchendrarajan, Rrubaa Department of Computer Science and Software Engineering Sri Lanka Institute of Information Technology Sri Lanka Department of Computer System Engineering Sri Lanka Institute of Information Technology Sri Lanka

ISBN: (纸本)9798350398090

Due to the prevalence of the COVID-19 epidemic around the globe, children were compelled to engage in remote learning through online platforms, hence mobile phone has become one of their predominant devices. Mobile device with Internet access offers a major outlet for education, entertainment, and social connection, but this combination can lead to several significant bad sequences such as online exploitation, harmful addictions, and other negative impacts of online social networking. To address harmful effects, parental controls are becoming more crucial, yet Sri Lankan parents are less aware of this. Consequently, this study proposes a parental control system to monitor their child's activities. Android, Microsoft Azure, Java, Python, OpenCV, MySQL, and FastAPI are among the most prominent technologies utilized in the proposed application's development. The suggested approach focuses primarily on the Sri Lankan context and aims to enhance parental digital literacy while safeguarding children from cyber threats. Yielded results showed the proposed mobile application for the identification of toxic words, drugs & alcohol content, game character images, and Instagram Sinhala comments severity as 94%, 95%, 97%, and 55% respectively in controlled experiments. © 2022 IEEE.

关键词： Control systems

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：