检索结果-内蒙古大学图书馆

3rd International Conference on Intelligent Systems, Advanced Computing, and Communication, ISACC 2025

作者： Tripathi, Abhishek Gopi Reddy, Kasu V S Amarnath, K. Bavesh, C. Vardhan, Bestha Singh, Sumitra Kalasalingam Academy of Research and Education Department of Computer Science and Engineering Virudhunagar India Central Electronics Engineering Research Institute Semiconductor Devices Design Group Pilani India

ISBN: (纸本)9798331523893

This paper presents a cost-effective manual wheelchair system designed to enhance mobility and communication for deaf-mute, disabled, and elderly individuals. The system employs a gesture-based mechanism using a glove with embedded flex sensors to detect finger movements, translating them into actionable commands. These commands are processed by a microcontroller to provide real-time feedback through three channels: visual messages displayed on an LCD, wireless communication with a caretaker's device, and audio feedback via a speaker. Testing demonstrates reliable gesture detection and response generation, highlighting the system's effectiveness in meeting the diverse needs of users. The design emphasizes affordability, ease of use, and adaptability, offering a practical and inclusive solution for individuals with varying levels of mobility and communication challenges. © 2025 IEEE.

关键词： Signaling

来源：评论

学校读者我要写书评

暂无评论

GIRP: Energy-Efficient QoS-Oriented Microservice Resource Provisioning via Multi-Objective Multi-Task Reinforcement Learning

引用

IEEE Transactions on Mobile Computing 2025年第7期24卷 5793-5807页

作者： Yuan, Honggang Wang, Ting Fu, Min Shi, Yuanming East China Normal University MoE Engineering Research Center of Software/Hardware Co-design Technology and Application Shanghai Key Laboratory of Trustworthy Computing Shanghai200062 China National University of Singapore Department of Electrical and Computer Engineering 117583 Singapore ShanghaiTech University School of Information Science and Technology Shanghai201210 China

Microservice architecture has revolutionized web service development by facilitating loosely coupled and independently developable components distributed as containers or virtual machines. While existing studies emphasize end-to-end latency, this paper investigates energy-efficient quality-of-service (QoS)-oriented microservice provisioning, focusing on both QoS satisfaction and power consumption (PC) conservation. We propose the Green and Intelligent Resource Provision (GIRP) architecture, integrating a data-driven energy-latency-aware resource allocation and scheduling manager to balance latency and PC. To reconcile the trade-offs involved, a dual-objective optimization problem is formulated to minimize latency and energy use by selecting proper servers, allocating CPU cores, and determining service replicas. To address challenges with discrete variables, dual objectives, and implicit mappings, we leverage a model-free deep deterministic policy gradient-based reinforcement learning algorithm. Specifically, we develop a multi-task agent via the Multi-gate Mixture-of-Experts model to simultaneously make two separate actions regarding CPU core numbers and service replica numbers, followed by a single-task agent to determine service scheduling. Extensive experiments on the DeathStarBenchmark testbed validate GIRP's effectiveness, demonstrating approximately 52% resource savings and a 43% reduction in PC compared to leading methods like Sinan, Firm, and heuristic-based algorithms. These results highlight GIRP's capability to optimize microservice orchestration by balancing end-to-end latency and power efficiency. © 2025 IEEE. All rights reserved.

关键词： Quality of service

来源：评论

学校读者我要写书评

暂无评论

Drawing Order Diagrams Through Two-Dimension Extension

引用

Journal of Graph Algorithms and applications 2023年第9期27卷 783-802页

作者： Dürrschnabel, Dominik Hanika, Tom Stumme, Gerd Knowledge & Data Engineering Group Research Center for Information System Design & Department of Electrical Engineering and Computer Science University of Kassel Germany Institute of Computer Science University of Hildesheim Germany Berlin School of Library and Information Science Humboldt-Universität zu Berlin Germany

Ordinal real-world data such as concept hierarchies, ontologies, genealogies, or task dependencies in scheduling often has the property to not only contain pairwise comparable, but also incomparable elements. Order diagrams provide an important tool for understanding and thus discovering knowledge in such data. Easily readable drawings of such order diagrams are hard to come by, even for small ordered sets. Many attempts were made to transfer classical graph drawing approaches to order diagrams. Although these methods produce satisfying results for some ordered sets, they unfortunately perform poorly in general. In this work, we present the novel algorithm DimDraw to decompose an ordered set (e.g., a concept hierarchy) in linear orders and to produce a corresponding order diagram. This algorithm is based on a relation between the dimension of an ordered set and the bipartiteness of its transitive incompatibility graph. To evaluate the quality of the algorithm, a user study was conducted where generated drawings were compared with ones from state-of-the-art drawing algorithms. © 2023 Brown University. All rights reserved.

关键词： Set theory

来源：评论

学校读者我要写书评

暂无评论

Exploration of Thermoelectric Energy Harvesting for Secure, TLS-Based Industrial IoT Nodes 1

引用

7th International Conference on Internet of Things, ICIOT 2022 held as Part of the Services Conference Federation, SCF 2022

作者： Lauer, Frederik Schöffel, Maximilian Rheinländer, Carl C. Wehn, Norbert Department of Electrical and Computer Engineering Microelectronic Systems Design Research Group Technische Universität Kaiserslautern Kaiserslautern67663 Germany

ISBN: (数字)9783031235825

ISBN: (纸本)9783031235818

Security is one of the biggest challenges, particularly in the Industrial IoT and in critical infrastructures. Complex cryptographic computations are in contrast to the low energy budget of the devices, especially when independence from the power grid is required, as it is the case with retrofitted sensor nodes. Energy harvesting offers a promising alternative but tightens the energy constraints of the application further. In this work, we investigate how IoT edge devices can be powered by thermal energy harvesting and concurrently meet the stringent TLS-based security requirements. We analyze a thermoelectric generator system at its lowest power output region and evaluate different energy storage technologies in a representative IoT architecture. Our results show that temperature gradients as low as 1 K are sufficient to enable secure connections every 20 min in a representative IIoT application. © 2023, The Author(s), under exclusive license to Springer Nature Switzerland AG.

关键词： Energy harvesting

来源：评论

学校读者我要写书评

暂无评论

Joint Graph Convolutional Network and Convolutional Neural Network for Recommendation 3

Joint Graph Convolutional Network and Convolutional Neural N...

引用

3rd International Conference on Frontiers of Electronics, Information and Computation Technologies, ICFEICT 2023

作者： Wang, Hui Ding, Di Li, Zhiwen Li, Shengchang Zeng, Shuai Huaxin Consulting Design Research Institute Group Customer Department Hangzhou China China Ordnance Industry Computer Application Technology Institute Internet and Information Technology Department Beijing China

ISBN: (纸本)9798350302356

The recommendation algorithms based on graph convolutional network can extract the association relationship between users and items by interaction data, but most of these algorithms ignore the general preferences in the review data of users and items. The recommendation algorithms based on convolutional neural network with review can learn user behaviors and item properties. In order to combine the advantages of two kinds of algorithm and make use of both review text data and user-item interaction data fully, we proposed a new model called Joint Graph Convolutional Network and Convolutional Neural Network for Recommendation (JGCR) in this paper. This model used the graph convolutional network to extract association relations, and used convolutional neural network to extract the general preferences from review text, and carried out feature fusion to improve the recommendation effect. This paper conducted comparative experiments on four datasets of amazon dataset to verify the effectiveness of the proposed model. The evaluation metric is mean square error. Experiments results demonstrate that JGCR significantly outperforms all baseline recommendation algorithms. The feature from jointing graph convolutional network and convolutional neural network can improve the recommendation effect. © 2023 IEEE.

关键词： Convolution

来源：评论

学校读者我要写书评

暂无评论

Social Recommendation Algorithm Based on Fusion Graph Convolutional Neural Network and Gated Recurrent Unit Network 4

Social Recommendation Algorithm Based on Fusion Graph Convol...

引用

4th International Conference on computer, Big Data and Artificial Intelligence, ICCBD+AI 2023

作者： Ding, Di Wang, Hui Li, Zhiwen Huaxin Consulting Design & Research Institute Group Customer Department Hangzhou China China Ordnance Industry Computer Application Technology Institute Internet and Information Technology Department Beijing China

ISBN: (纸本)9798350373233

This paper proposes a fusion model named FGCN-GRU (Fusion Graph Convolutional Neural network and Gated Recurrent Unit network) to predict users' ratings on items. Firstly, FGCN-GRU constructs a new graph convolutional neural network by regarding users' ratings on items as relative ratings and introduces the GRU network by considering the fact that the user's interest in items will change over time. Then the improved graph convolutional neural network, GRU network and users' social network are used to model users, items, and social relations respectively. The experimental results on the datasets of Ciao and Epinions show that the recommendation performance of the proposed model is better. © 2023 IEEE.

关键词： Convolutional neural networks

来源：评论

学校读者我要写书评

暂无评论

Energy-Efficient Shop Scheduling Using Space-Cooperation Multi-Objective Optimization

IEEE Transactions on Sustainable Computing

引用

IEEE Transactions on Sustainable Computing 2024年第3期10卷 601-615页

作者： Ding, Jiepin Xia, Jun Yang, Yaning Zhou, Junlong Chen, Mingsong Li, Keqin East China Normal University MoE Engineering Research Center of Software/Hardware Co-Design Technology and Application Shanghai200062 China Ningxia Normal University School of Physics and Electronic Information Engineering Guyuan756500 China Nanjing University of Science and Technology School of Computer Science and Engineering Nanjing210094 China State University of New York Department of Computer Science New PaltzNY12561 United States

Since Industry 5.0 emphasizes that manufacturing enterprises should raise awareness of social contribution to achieve sustainable development, more and more meta-heuristic algorithms are investigated to save energy in manufacturing systems. Although non-dominated sorting-based meta-heuristics have been recognized as promising multi-objective optimization methods for solving the energy-efficient flexible job shop scheduling problem (EFJSP), it is hard to guarantee the quality of the Pareto front (e.g., total energy consumption, makespan) due to the lack of population diversity. This is mainly because an improper individual comparison inevitably reduces population diversity, thus limiting exploration and exploitation abilities during population updates. To achieve efficient population evolution, this paper introduces a novel space-cooperation multi-objective optimization (SCMO) method that can effectively solve EFJSP to obtain scheduling schemes with better trade-offs. By cooperatively evaluating the similarity among individuals in both the decision space and objective space, we propose a space-cooperation population update method based on a three-vector representation that can accurately eliminate repetitive individuals to derive higher-quality Pareto solutions. To further improve search efficiency, we propose a difference-driven local search, which selectively changes the positions of operations with higher differences to search for neighbors effectively. Based on the Taguchi method, we conduct experiments to obtain a suitable parameter combination of SCMO. Comprehensive experimental results show that, compared to state-of-the-art methods, our SCMO method achieves the highest HV and NR and the lowest IGD, with an average of 0.990, 0.952, and 0.001, respectively. Meanwhile, compared to traditional local search approaches, our difference-driven local search obtains twice the HV on instance Mk12 and reduces the solving time from 1521s to 475s. © 2016 IEEE.

关键词： Job shop scheduling

来源：评论

学校读者我要写书评

暂无评论

IBB Traffic Graph Data: Benchmarking and Road Traffic Prediction Model 29

IBB Traffic Graph Data: Benchmarking and Road Traffic Predic...

引用

29th IEEE International Workshop on computer Aided Modeling and design of Communication Links and Networks, CAMAD 2024

作者： Olug, Eren Kaya, Kiymet Tugay, Resul Oguducu, Sule Gunduz Istanbul Technical University Department of Artificial Intelligence and Data Engineering Istanbul Turkey Itu Ai Research and Application Center Istanbul Turkey Bts Group Istanbul Turkey Istanbul Technical University Department of Computer Engineering Istanbul Turkey Gazi University Department of Computer Engineering Ankara Turkey

ISBN: (纸本)9798350377644

Road traffic congestion prediction is a crucial component of intelligent transportation systems, since it enables proactive traffic management, enhances suburban experience, reduces environmental impact, and improves overall safety and efficiency. Although there are several public datasets, especially for metropolitan areas, these datasets may not be applicable to practical scenarios due to insufficiency in the scale of data (i.e. number of sensors and road links) and several external factors like different characteristics of the target area such as urban, highways and the data collection location. To address this, this paper introduces a novel IBB Traffic graph dataset as an alternative benchmark dataset to mitigate these limitations and enrich the literature with new geographical characteristics. IBB Traffic graph dataset covers the sensor data collected at 2451 distinct locations. Moreover, we propose a novel Road Traffic Prediction Model that strengthens temporal links through feature engineering, node embedding with GLEE to represent interrelated relationships within the traffic network, and traffic prediction with ExtraTrees. The results indicate that the proposed model consistently outperforms the baseline models, demonstrating an average accuracy improvement of 4%. © 2024 IEEE.

关键词： Traffic congestion

来源：评论

学校读者我要写书评

暂无评论

A NOVEL MODEL FOR THE MATERIAL SELECTION OF SMART OBJECTS FOR HAND-REHABILITATION: A CASE STUDY 24

A NOVEL MODEL FOR THE MATERIAL SELECTION OF SMART OBJECTS FO...

引用

24th International Conference on engineering design, ICED 2023

作者： Bos, Mikaël Ivar Karahanoǧlu, Armaǧan Haarman, Juliet Nizamis, Kostas Chair of Systems Engineering and Multidisciplinary Design Department of Design Production and Management Faculty of Engineering Technology University of Twente Enschede Netherlands Interaction Design Research Group Department of Design Production and Management Faculty of Engineering Technology University of Twente Enschede Netherlands Human Media Interaction Group Faculty of Electrical Engineering Mathematics and Computer Science University of Twente Enschede Netherlands

Home hand rehabilitation for stroke is becoming increasingly important due to logistic and financial challenges. Developing Daily-life Integrated Hand-rehabilitation Products (DIHP) aims to enable the application of at-home rehabilitation. The materials of these products are essential for their success, however, selecting materials for DIHP has not been investigated yet. Previous research on material selection showed that it is done strictly on material properties or based on a human-centered approach. Hence, in this study, we propose a hybrid model for choosing materials for DIHP. To achieve this, we first combined the findings of previous material selection processes into a comprehensive material selection model. We applied this model in a case study, in which we first selected three materials based on their properties. Following, we 3d printed a DIHP out of the chosen materials and tested the feeling of the materials with multiple expert groups. Our findings suggest that the proposed material selection method is promising and highlights that our comprehensive model provides more insights when compared to a strict material property-based selection. © The Author(s), 2023. Published by Cambridge University Press.

关键词： 3D printing

来源：评论

学校读者我要写书评

暂无评论

Cash Flow Forecasting Based on Wavelet Transform and Neural Networks 8

Cash Flow Forecasting Based on Wavelet Transform and Neural ...

引用

8th International Conference on computer Science and engineering, UBMK 2023

作者： Soylen, Zumra Mammadova, Farida Fasounaki, Mandana Ozmen, Ayse Irem Ince, Gokhan Istanbul Technical University Department of Computer Engineering İstanbul Turkey Mdp Group R&d Department İstanbul Turkey Istanbul Technical University Department of Computer Engineering & Ai and Data Science Application and Research Center İstanbul Turkey

ISBN: (纸本)9798350340815

Cash flow forecasting is a critical task for businesses and financial institutions to ensure effective financial planning and decision-making. However, limited data availability poses a significant challenge when developing accurate and robust cash flow prediction models. In this paper, we investigate the performance of various forecasting methods and propose an approach based on wavelet transform for improving the forecasting accuracy. We demonstrate the effectiveness of the proposed approach with the best combination of wavelet functions and methods for forecasting future values in a univariate time series. We investigate the impact of wavelet transform on forecasting techniques based on open-source datasets. Our methodology includes data collection, preprocessing, feature engineering, model selection, and experimentation using different performance evaluation metrics. © 2023 IEEE.

关键词： Forecasting

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：