检索结果-内蒙古大学图书馆

20th IFIP WG 10.3 international conference on Network and parallel Computing, NPC 2024

作者： Qin, Lisha Tan, Haoliang Zou, Xiangyu Ou, Wenhao Wei, Yan Huang, Rubing Xia, Wen Harbin Institute of Technology Shenzhen China Peng Cheng Laboratory Shenzhen China Zhongruan International Technology Service Co. Ltd. Shenzhen China Macau University of Science and Technology Macao China

ISBN: (纸本)9789819628292

Docker image storage systems, like Docker registry, often employ deduplication to reduce storage overhead. Existing deduplication methods for these systems detect redundancy at either layer or file level, each with its own advantages and limitations. Layer-level deduplication offers much faster restoration but lower deduplication ratio, as it eliminates duplicate layers while ignoring duplicate files across layers. Conversely, file-level deduplication offers a higher deduplication ratio but slower restoration, as removing duplicate files scatters the files of a layer, leading to multiple disk read I/O during restoration. Our analysis reveals that the slow restoration in file-level deduplication partly stems from ignoring file-layer relationships. In this paper, we propose MiDedup, a new Docker deduplication method. MiDedup detects redundancy at file-level and organizes files into a restore-friendly layout by considering file-layer relationships to enhance restore speed. Our studies also show that duplicated files of one layer are not uniformly distributed across different layers. MiDedup uses this insight to skip deduplicating scattered files to further optimize the file layout for faster restoration. Evaluations indicate that MiDedup achieves restore speeds that are 8–19× faster than file-level deduplication (slightly slower than layer-level one), while maintaining 9–47% higher deduplication ratios than layer-level deduplication. © IFIP international Federation for Information processing 2025.

关键词： Redundancy

来源：评论

学校读者我要写书评

暂无评论

FPGA-Based 3D EM/MPM Simulation Framework for Medical Image Segmentation Applications

FPGA-Based 3D EM/MPM Simulation Framework for Medical Image ...

引用

international conference on Electronics, Materials Engineering and Nano-Technology (IEMENTech)

作者： Samit Karmakar Arindam Chakraborty Saptarshi Banerjee Ayantika Mondal Satavisha Dutta Sayak Nandi Electronics & Communication Engineering Dept. Institute of Engineering & Management University of Engineering & Management Kolkata India

ISBN: (数字)9798331520762

ISBN: (纸本)9798331520779

Medical image segmentation is a critical process in identifying disease-infected regions for diagnostic and treatment purposes. this paper introduces an FPGA-based framework for implementing the Expectation Maximization/Markov Random Field (E M/MP M) algorithm in 3D medical image segmentation. FPGA platforms offer unparalleled advantages in terms of parallel processing, speed, and energy efficiency, making them a promising choice for real-time medical image analysis. this proposed framework enables rapid segmentation of 3D images, leveraging the FPGA's on-chip memory and custom logic for efficient pixel classification and data processing. the adaptive design also supports the integration of external RAM for larger datasets. Simulated using Verilog HDL and Quartus Prime, this work demonstrates accurate segmentation results through virtual testing, thus showcasing the system's robustness for medical applications.

关键词： Image segmentation three-dimensional displays Random access memory Medical services parallel processing Real-time systems Energy efficiency Hardware design languages Medical diagnostic imaging Field programmable gate arrays

来源：评论

学校读者我要写书评

暂无评论

An Effective Approach to Speech-Based Email Assistance for Visually Impaired People

An Effective Approach to Speech-Based Email Assistance for V...

引用

international conference on Trends in Electronics and Informatics (ICEI)

作者： Henwyn Shan Antony. S Sherin Eliyas Department of Computer Application Hindustan Institute of Technology and Science Chennai India

ISBN: (数字)9798331544607

ISBN: (纸本)9798331544614

the Speech-based Email Assistant aims to promote digital inclusivity for the blind by allowing email operations to be done hands-free via voice commands. the system is capable of uninterrupted use without any visual input, using the OpenAI Whisper model for converting speech to text and the Google Text-to-Speech (GTTS) package for providing auditory feedback. the application allows for creating, sending, retrieving, managing mailboxes, and summarizing email messages, thus providing basic Natural Language processing (NLP) functions. Voice input is in live mode through PyAudio, and emails are sent over secure channels using SMTP and IMAP for email operations. Voice authentication alongside SHA-256 hashing is applied to enhance security, providing protection against unauthorized access while ensuring user privacy. this research aims to develop a voice-based email assistant that is user-friendly, efficient, and secure, thus promoting the digitally inclusive training of visually impaired users.

关键词： Training Visualization Authentication Natural language processing Electronic mail Text to speech Security Speech processing Usability Speech to text

来源：评论

学校读者我要写书评

暂无评论

parallel processing and applied mathematics: 11th international conference, PPAM 2015 Krakow, Poland, september 6-9, 2015 revised selected papers, part I

Lecture Notes in Computer Science (including subseries Lectu...

引用

Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) 2016年 9573卷

作者： Wyrzykowski, Roman Deelman, Ewa Dongarra, Jack Karczewski, Konrad Kitowski, Jacek Wiatr, Kazimierz Czestochowa University of Technology Czestochowa Poland Department of Computer Science University of Southern California Marina Del ReyCA United States Electrical Engineering and Computer Science University of Tennessee KnoxvilleTN United States Institute of Computer and Information Science Czestochowa University of Technology Czestochowa Poland Department of Computer Science AGH University of Science and Technology Krakow Poland AGH University of Science and Technology Krakow Poland

来源：评论

学校读者我要写书评

暂无评论

Comparison of the Genetic Algorithm and the Particle Swarm Optimization for Minimizing Fuel Consumption for UAVs

Comparison of the Genetic Algorithm and the Particle Swarm O...

引用

Innovative Research in applied Science, Engineering and Technology (IRASET),conference on

作者： Vincent Roberge Mohammed Tarbouchi Gilles Labonté Department of Electrical and Computer Engineering Royal Military College of Canada Kingston Canada Department of Mathematics and Computer Science Royal Military College of Canada Kingston Canada

ISBN: (数字)9798331532970

ISBN: (纸本)9798331532987

this paper compares the efficiency of two metaheuristics, namely the Genetic Algorithm (GA) and the Particle Swarm Optimization (PSO), for the problem of fuel minimization for uncrewed aerial vehicles (UAVs). When flying search-and-rescue or surveillance missions, it is critical to minimize fuel consumption in order to increase the autonomy of the vehicles. the method proposed consists of using the metaheuristic to compute optimized power settings for the UAV along the trajectory. the approach involves path smoothing in 3D using circular arcs for fixed-wing UAVs. Equations of motion and Newton's equation are used to calculate fuel consumption based on power settings. the metaheuristics are used to compute optimized power settings while adhering to physical constraints. the method is parallelized on a multicore processor for faster computation and optimization in case of trajectory changes. Results show that both the GA and the PSO are efficient at minimizing fuel consumption for the UAV with the PSO being slightly superior. the proposed method can reduce fuel consumption by up to 15% and the parallel implementation is 13.8× faster than a sequential implementation on the CPU.

关键词： Smoothing methods Multicore processing Surveillance Metaheuristics Autonomous aerial vehicles Minimization Trajectory Fuels Particle swarm optimization Genetic algorithms

来源：评论

学校读者我要写书评

暂无评论

Towards Automatic, Predictable and High-Performance parallel Code Generation 30th

Towards Automatic, Predictable and High-Performance Paralle...

引用

30th international conference on parallel and Distributed processing Techniques, PDPTA 2024, held as part of the World Congress in Computer Science, Computer Engineering and applied Computing, CSCE 2024

作者： Mullin, Lenore Hains, Gaétan 1400 Washington Ave AlbanyNY12222 United States LACL Université Paris-Est Créteil94000 France

ISBN: (纸本)9783031856372

High-performance architectures have complex features so that reliable production of parallel software is beyond the reach of many Computer Science graduates. Compilers alone cannot guarantee the highest performance and multiple APIs with complex performance features are difficult to master. As a first step towards more comprehensive solutions we are building key elements of a pre-compiler system that will automatically produce predictable, scalable and high-performance code from declarative tensor expressions. In this paper we summarize and analyze a large set of timing experiments of matrix multiplication variants that are mapped to vectorized and multithread code. the analysis covers two high-end target architectures and exhaust a whole space of code, compiler, pragma and parallelism parameters. Our analysis shows how the best choice of parameters is produced from a small set of tests that can converge in a matter of seconds and then predict performance of larger instances to within 25% or much less. Inefficient choices of parameters is also shown to be reliably predicted from small tests, so that our design for a precompiler is guaranteed to be a realistic and portable tool. the generality of our mathematics of Arrays tensor algebra, and very broad applicability of tensor operations (signal processing, scientific computing, AI, etc.) supports our claim that these experiments and design can be generalized to a general purpose parallel programming tool. © the Author(s), under exclusive license to Springer Nature Switzerland AG 2025.

关键词： Tensors

来源：评论

学校读者我要写书评

暂无评论

Wind Power Forecasting Model Based on Feature processing and Deep Hybrid Kernel Extreme Learning Machine 8th

Wind Power Forecasting Model Based on Feature Processing and...

引用

8th international conference on Life System Modeling and Simulation, LSMS 2024 and 8th international conference on Intelligent Computing for Sustainable Energy and Environment, ICSEE 2024

作者： Wei, Xiongfei Wang, Jing Ruan, Yi Fang, Yuanjie College of Electrical Engineering Anhui Polytechnic University Anhui Wuhu241000 China School of Electronic Engineering Chaohu University Anhui Chaohu238024 China

ISBN: (纸本)9789819602315

To improve the forecasting accuracy of wind power, a wind power forecasting (WPF) model based on feature cleaning combined with deep hybrid kernel extreme learning machine (DHKELM) is proposed. the Pearson correlation coefficient (PCC) method is used to optimize the features, eliminate irrelevant features, and the isolated forest (IF) algorithm is used to clean the anomalous data in the retained features, which enhances the correlation between the selected features and wind power, and then combines the DHKELM to predict the wind power. Finally, the proposed model is applied to predict the wind power of a 1MW wind turbine, and the results of the progressive forecasting of the proposed method and the forecasting results of different models are compared. the results show that the PCC-IF-DHKELM forecasting model has a root-mean-square error of 0.01928 MW, an average absolute error of 0.015254 MW, and a correlation coefficient of 0.99435, which is significantly better than the other forecasting models, proving the effectiveness of the PCC-IF-DHKELM forecasting method. © the Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.

关键词： Wind forecasting

来源：评论

学校读者我要写书评

暂无评论

Design of Cloud-Edge-End Collaborative Framework for Power Supply Intelligent Inspection Operation Scenario Based on Unmanned Aerial Vehicle

Design of Cloud-Edge-End Collaborative Framework for Power S...

引用

IEEE Information Technology and Mechatronics Engineering conference (ITOEC)

作者： Wei Wang Ping Qiu State Grid Zhejiang Electric Power Co. Ltd. Hangzhou China Zhejiang International Studies University Hangzhou China

ISBN: (数字)9798331529482

ISBN: (纸本)9798331529499

As a new type of tool with powerful perception, monitoring, and emergency response capabilities, unmanned aerial vehicles (UAVs) have the characteristics of flexibility, maneuverability, and high-altitude inspection. UAVs can greatly improve the efficiency of power facility maintenance and repairing, reduce personnel risks, and have gradually become an important auxiliary means for power supply operation and management. Currently, research on cloud-edge collaborative computing using UAVs has been applied to power systems, especially in their daily maintenance. However, there is not much discussion on building a systematic UAV-based cloud-edge collaboration system, especially to meet the requirements of power supply companies. Aiming at the problems such as the limited distance of image transmission, the lack of timeliness and visualization of image data processing in the application process of UAVs, in this paper, a "cloud-edge-end" collaborative framework has been proposed to achieve fast data return over the distance under signal coverage, and use the characteristics of local edge computing to quickly solve image preprocessing.

关键词： Power supplies Clouds Collaboration Inspection Autonomous aerial vehicles Cameras Electricity supply industry Real-time systems Maintenance Edge computing

来源：评论

学校读者我要写书评

暂无评论

DV Emotion Net: A Sub-Study on Emotion Detection Model Performance Across P100, T4, and TPU VM V3-8

DV Emotion Net: A Sub-Study on Emotion Detection Model Perfo...

引用

Sentiment Analysis and Deep Learning (ICSADL), international conference on

作者： Dhiren Dommeti Siva Ramakrishna Nallapati Rand Alfaris School of Professional Studies (SPS) Clark University Worcester Massachusetts USA

ISBN: (数字)9798331523923

ISBN: (纸本)9798331523930

this study evaluates the performance of different hardware configurations-GPU P100, GPU T4, and TPU VM v3-8-in the context of emotion detection using the DV EmotionNet framework. Building on prior research that integrates audio and video modalities for emotion recognition, the analysis explores how each hardware setup influences model efficiency and accuracy. Audio features were extracted using techniques such as energy, zero crossing rate, and Mel-Frequency Cepstral Coefficients (MFCC), while video features were obtained through spatial-temporal Gaussian kernels and Gaussian-weighted functions applied to the second momentum matrix. the Multimodal Feature Aggregation (MFA) method was employed to fuse the audio and video features, creating a comprehensive dataset. the evaluation utilized the Fusion of Emotion Recognition Convolutional Neural Network (FERCNN) model, focusing on the impact of accelerators on performance metrics. Recent advancements often face challenges like high computational costs, scalability issues, and sensitivity to noisy data. this study addresses these challenges by systematically evaluating the computational efficiency and accuracy trade-offs across different hardware accelerators. Results from the RAVDESS and CREMAD datasets revealed notable differences in accuracy, with the P100 demonstrating superior performance on simpler tasks, while TPU VM v3-8 excelled in more complex scenarios. these findings highlight the significance of hardware choice in optimizing multimodal emotion recognition systems, reinforcing the critical role of effective computational resources in enhancing applications across various domains, including human-computer interaction, healthcare, and entertainment.

关键词： Training Emotion recognition Accuracy Fluctuations Computational modeling Graphics processing units parallel processing Hardware Computational efficiency Testing

来源：评论

学校读者我要写书评

暂无评论

Development of a Machine Learning-Based Robotic System for Medical-Targeted Drug Delivery System 8th

Development of a Machine Learning-Based Robotic System for M...

引用

8th National conference on New Trends in Information and Communications Technology Applications, NTICT 2024

作者： Simango, Doubt Manyanye, Trish Aldhaibani, Jaafar A. Yahya, Abid Mushiri, Tawanda Ndaimani, Augustine Department of Mechatronic Engineering School of Engineering Sciences and Technology Private Bag Off-Chirundu Road Chinhoyi7724 Zimbabwe College of Engineering University of Information Technology and Communication Baghdad Iraq Botswana International University of Science and Technology Private Bag 16 Palapye Botswana Department of Industrial and Mechatronics Engineering Faculty of Engineering and the Built Environment University of Zimbabwe 630 Churchill Avenue Mt Pleasant Harare Zimbabwe Department of Biomedical Informatics and Biomedical Engineering University of Zimbabwe 630 Churchill Avenue Mt Pleasant Harare Zimbabwe

ISBN: (纸本)9783031870750

Medical robotics is a field that combines engineering and artificial intelligence to create robotic systems used in healthcare. this study aims to delve into the exciting field of developing medical-targeted drug delivery systems, which hold immense potential for revolutionizing how we administer therapeutic substances. By precisely delivering drugs to specific sites within the body, these innovative systems offer improved treatment outcomes, reduced side effects, and enhanced patient compliance. therefore, an image processing algorithm for visible target detection was designed, a system to determine the coordinates of the exact location of identified regions of the target was developed, and a trajectory plan for the robotic arm end effector for precise drug delivery was also designed. the integration of robotic systems into MRI scanners, the development of image processing algorithms, and also real-time feedback control systems are mechatronics-based processes. Medical image navigation technology has many uses in minimally invasive robots, mainly image acquisition techniques such as Magnetic Resonance Imaging (MRI) to acquire equivalent image data;however, medical imaging techniques have inefficient visibility in robotic-assisted surgeries of small and confined incisions. therefore, image processing methods are applied to precisely regulate the operation’s location and visibility and improve the procedure’s efficacy, accuracy, and safety. To develop an advanced medical-targeted drug delivery system. © the Author(s), under exclusive license to Springer Nature Switzerland AG 2025.

关键词： End effectors

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：