检索结果-内蒙古大学图书馆

Virtual-physical digital twin testbed for heterogeneous crowd operations

science China(Information sciences) 2025年第5期68卷 404-406页

作者： Mingliang XU Zheng WANG Yang MENG Wencan LUO Hua WANG Shuo HE Chaochao LI Yibo GUO Yafei LI Pei LV School of Computer Science and Artificial Intelligence Zhengzhou University Engineering Research Center of Intelligent Swarm Systems Ministry of Education National Supercomputing Center in Zhengzhou

Heterogeneous crowd operations involve complex procedural subtasks performed by dynamic teams with diverse agent behaviors,tailored to specific task *** of such operations include carrier aircraft support,airport ground handling,and logistics *** a hybrid virtual-physical digital twin testbed for scenario generation and plan verification in heterogeneous crowd operations addresses the issues of low credibility in virtual simulations and the high costs associated with real-world *** is becoming increasingly important in practical applications.

关键词：

来源：评论

学校读者我要写书评

暂无评论

Data-driven output regulation control for constrained linear systems

引用

science China(Information sciences) 2025年第3期68卷 338-353页

作者： Chaoyu XIA Yi DONG Chaoli WANG Shengyuan XU Shanghai Research Institute for Intelligent Autonomous Systems Tongji University College of Electronic and Information Engineering Shanghai Research Institute for Intelligent Autonomous SystemsTongji University Department of Control Science and Engineering School of Optical-Electrical and Computer EngineeringUniversity of Shanghai for Science and Technology Department of Automation Nanjing University of Science and Technology

This study introduces a data-driven approach for state and output feedback control addressing the constrained output regulation problem in unknown linear discrete-time systems. Our method ensures effective tracking performance while satisfying the state and input constraints, even when system matrices are not available. We first establish a sufficient condition necessary for the existence of a solution pair to the regulator equation and propose a data-based approach to obtain the feedforward and feedback control gains for state feedback control using linear programming. Furthermore, we design a refined Luenberger observer to accurately estimate the system state, while keeping the estimation error within a predefined set. By combining output regulation theory, we develop an output feedback control strategy. The stability of the closed-loop system is rigorously proved to be asymptotically stable by further leveraging the concept of λ-contractive sets.

关键词： output regulation constrained system data-driven.

来源：评论

学校读者我要写书评

暂无评论

Use that Pinky on the ‘A’ Key: A Finger-Key Identification Module for a Touch Typing Trainer 4th

Use that Pinky on the ‘A’ Key: A Finger-Key Identificati...

引用

4th International Conference on Advances in Computational science and Engineering, ICACSE 2023

作者： Valles, Oscar Vian L. Gom-os, Dhong Fhel K. Center for Research in Intelligent Systems Department of Computer Science University of the Philippines Cebu Cebu6000 Philippines

ISBN: (纸本)9789819729760

Typing tests list out words for the user to repeat. These tests measure metrics that quantify the user’s ability to type. However, conventional typing metrics do not measure correct finger placement. This aspect of typing may affect the user’s health. It is also a crucial aspect of keyboard typing education. As such, a method to identify which finger is used to press which key is beneficial. This paper introduces a new technique to achieve this by developing a finger-key identification module that utilizes computer vision algorithms to detect the keys in a keyboard, and a ready-made machine learning solution to track fingers while typing. This module was successful in finger-key identification with an accuracy of 99.58% in a dataset of 942 keypresses. It also had an average finger-key identification time of 0.083 s, which allows it to perform real-time finger-key identification for typing speeds up to 143.040 words per minute, well beyond the median typing speed of the population. Two metrics for correct finger placement were defined and were implemented in a proof-of-concept trainer: (1) finger placement accuracy and (2) historical finger placement accuracy. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2024.

关键词： Palmprint recognition

来源：评论

学校读者我要写书评

暂无评论

Naïve Bayesian Approach to Intruder Detection in Smart Homes Using Sensor Networks 4th

Naïve Bayesian Approach to Intruder Detection in Smart Ho...

引用

4th International Conference on Advances in Computational science and Engineering, ICACSE 2023

作者： Bolivar, Daisy Jane S. Gom-os, Dhong Fhel K. Department of Computer Science Center for Research in Intelligent Systems University of the Philippines Cebu Cebu6000 Philippines

ISBN: (纸本)9789819729760

We used camera, light, door, and window sensors, and day of the week, duration, and activation time parameters for a Naïve Bayesian approach to intruder detection in a smart home. A nine-week normal and a two-week intruder behavior data were extracted using sensor devices. SmartThings SmartApp was used to gather the sensor data which were published to Google Sheets, then exported to Excel and Python for pre-processing, providing a dataset size of 509, consisting of 284 normal and 225 intruder data. The data had an 80/20 train-test split and was fitted to the Naïve Bayes model. By identifying behavioral patterns and increasing parameters from the state-of-the-art, the model’s accuracy improved to 94.12% and achieved an F2-score of 93.18%. This study has shown that increasing sensor size could significantly improve intruder detection. Future work could include the analysis of the contribution of each sensor to provide informed decision to system designers. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2024.

关键词： Smart homes

来源：评论

学校读者我要写书评

暂无评论

5G Resource Allocation Using Feature Selection and Greylag Goose Optimization Algorithm

引用

computers, Materials & Continua 2024年第7期80卷 1179-1201页

作者： Amel Ali Alhussan S.K.Towfek Department of Computer Sciences College of Computer and Information SciencesPrincess Nourah bint Abdulrahman UniversityP.O.Box 84428Riyadh11671Saudi Arabia Computer Science and Intelligent Systems Research Center BlacksburgVA 24060USA

In the contemporary world of highly efficient technological development,fifth-generation technology(5G)is seen as a vital step forward with theoretical maximum download speeds of up to twenty gigabits per second(Gbps).As far as the current implementations are concerned,they are at the level of slightly below 1 Gbps,but this allowed a great leap forward from fourth generation technology(4G),as well as enabling significantly reduced latency,making 5G an absolute necessity for applications such as gaming,virtual conferencing,and other interactive electronic *** of this change are not limited to connectivity alone;it urges operators to refine their business strategies and offers users better and improved digital *** essential factor is optimization and the application of artificial intelligence throughout the general arrangement of intricate and detailed 5G *** Binary Greylag Goose Optimization(bGGO)to achieve a significant reduction in the feature set while maintaining or improving model performance,leading to more efficient and effective 5G network management,and Greylag Goose Optimization(GGO)increases the efficiency of the machine ***,the model performs and yields more accurate *** work proposes a new method to schedule the resources in the next generation,5G,based on a feature selection using GGO and a regression model that is an ensemble of K-Nearest Neighbors(KNN),Gradient Boosting,and Extra Trees *** ensemble model shows better prediction performance with the coefficient of determination R squared value equal *** proposed framework is supported by several Statistical analyses,such as theWilcoxon signed-rank *** of the benefits of this study are the introduction of new efficient optimization algorithms,the selection of features and more reliable ensemble models which improve the efficiency of 5G technology.

关键词： Optimization ensemble learning 5G technology artificial intelligence greylag goose optimization ANOVA test

来源：评论

学校读者我要写书评

暂无评论

GonioPi: Towards Developing a Scalable, Versatile, Reliable and Accurate Handheld-Wearable Digital Goniometer

引用

International Journal of Advanced computer science and Applications 2022年第6期13卷 321-330页

作者： Garcia, Thomas Jonathan R. Gom-os, Dhong Fhel K. Center for Research in Intelligent Systems Department of Computer Science University of the Philippines Cebu Cebu Philippines

Range of Motion (ROM) Testing is an important physical examination performed in physical therapy used in assessing the ROM of a patient’s joint. The most commonly used instrument for ROM Testing is the universal goniometer. The most common cause for unreliable and inaccurate joint angle ROM measurements is measurement errors. Multiple studies have been done to mitigate measurement errors in clinical goniometry by designing and developing wearable digital goniometers using sensor technology. This study aims to design and develop a handheld-wearable digital goniometer called the GonioPi that is versatile, scalable, reliable and accurate when using the MPU-6050 IMU sensor and Raspberry Pi Pico as the main components. The results showed that the GonioPi is versatile and scalable as it is able to support multiple ROM Tests using multiple different positions on people with varying heights, weights, and BMI categories. The results also showed that the GonioPi is reliable and accurate as it was able to record joint angle ROM measurements of less than 5 degrees and 10 degrees which are the accepted standard values for reliability and accuracy, respectively © 2022. International Journal of Advanced computer science and *** Rights Reserved.

关键词： Goniometers

来源：评论

学校读者我要写书评

暂无评论

A State-Migration Particle Swarm Optimizer for Adaptive Latent Factor Analysis of High-Dimensional and Incomplete Data

引用

IEEE/CAA Journal of Automatica Sinica 2024年第11期11卷 2220-2235页

作者： Jiufang Chen Kechen Liu Xin Luo Ye Yuan Khaled Sedraoui Yusuf Al-Turki MengChu Zhou IEEE the College of Computer Science and Technology Chongqing University of Posts and Telecommunications the Department of Computer Science Columbia University the College of Computer and Information Science Southwest University the Department of Electrical and Computer Engineering Faculty of Engineeringand also with K.A.CARE Energy Research and Innovation CenterKing Abdulaziz University the Center of Research Excellence in Renewable Energy and Power Systems the Department of Electrical and Computer EngineeringFaculty of Engineeringand also with K.A.CARE Energy Research and Innovation CenterKing Abdulaziz University the Department of Electrical and Computer Engineering New Jersey Institute of Technology

High-dimensional and incomplete(HDI) matrices are primarily generated in all kinds of big-data-related practical applications. A latent factor analysis(LFA) model is capable of conducting efficient representation learning to an HDI matrix,whose hyper-parameter adaptation can be implemented through a particle swarm optimizer(PSO) to meet scalable ***, conventional PSO is limited by its premature issues,which leads to the accuracy loss of a resultant LFA model. To address this thorny issue, this study merges the information of each particle's state migration into its evolution process following the principle of a generalized momentum method for improving its search ability, thereby building a state-migration particle swarm optimizer(SPSO), whose theoretical convergence is rigorously proved in this study. It is then incorporated into an LFA model for implementing efficient hyper-parameter adaptation without accuracy loss. Experiments on six HDI matrices indicate that an SPSO-incorporated LFA model outperforms state-of-the-art LFA models in terms of prediction accuracy for missing data of an HDI matrix with competitive computational ***, SPSO's use ensures efficient and reliable hyper-parameter adaptation in an LFA model, thus ensuring practicality and accurate representation learning for HDI matrices.

关键词： Data science generalized momentum high-dimensional and incomplete(HDI)data hyper-parameter adaptation latent factor analysis(LFA) particle swarm optimization(PSO)

来源：评论

学校读者我要写书评

暂无评论

Worst-Case Integrity Attacks and Resilient State Estimation With Partially Secured Measurements

引用

IEEE Transactions on Control of Network systems 2025年第2期12卷 1769-1779页

作者： Zhou, Jing Shang, Jun Chen, Tongwen University of Alberta Department of Electrical and Computer Engineering EdmontonABT6G 1H9 Canada Tongji University Department of Control Science and Engineering Shanghai Institute of Intelligent Science and Technology National Key Laboratory of Autonomous Intelligent Unmanned Systems Frontiers Science Center for Intelligent Autonomous Systems Shanghai200092 China

This paper examines the problem of optimal deception attacks against state estimation with partially secured measurements, where smart sensors transmit innovation sequences to the remote end for information fusion. Due to resource limitations or defensive countermeasures, the adversary can only modify data packets transmitted through unreliable channels. Meanwhile, the attack should be synthesized with sophistication to deceive an anomaly detector. To investigate the vulnerabilities of such estimation systems without feedback links and enhance security performance, the optimal attack policy is derived by formulating and explicitly solving a convex optimization problem, with the goal of maximizing the sum of estimation errors. Subsequently, a novel attack detection and resilient state estimation algorithm is proposed to ensure an acceptable level of estimation accuracy. The theoretical performance metrics, including false alarm rates for the proposed detector, are provided. Finally, the effectiveness of the results is confirmed through numerical examples. © 2014 IEEE.

关键词： Optimal detection

来源：评论

学校读者我要写书评

暂无评论

Methods for class-imbalanced learning with support vector machines: a review and an empirical evaluation

引用

Soft Computing 2024年第20期28卷 11873-11894页

作者： Rezvani, Salim Pourpanah, Farhad Lim, Chee Peng Wu, Q. M. Jonathan Department of Computer Science Ryerson University TorontoON Canada Department of Electrical and Computer Engineering University of Windsor WindsorON Canada Institute for Intelligent Systems Research and Innovation Deakin University GeelongVIC Australia

This paper presents a review on methods for class-imbalanced learning with the Support Vector Machine (SVM) and its variants. We first explain the structure of SVM and its variants and discuss their inefficiency in learning with class-imbalanced data sets. We introduce a hierarchical categorization of SVM-based models with respect to class-imbalanced learning. Specifically, we categorize SVM-based models into re-sampling, algorithmic, and fusion methods, and discuss the principles of the representative models in each category. In addition, we conduct a series of empirical evaluations to compare the performances of various representative SVM-based models in each category using benchmark imbalanced data sets, ranging from low to high imbalanced ratios. Our findings reveal that while algorithmic methods are less time-consuming owing to no data pre-processing requirements, fusion methods, which combine both re-sampling and algorithmic approaches, generally perform the best, but with a higher computational load. A discussion on research gaps and future research directions is provided. © The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature 2024.

关键词： Support vector machines

来源：评论

学校读者我要写书评

暂无评论

A Privacy-Aware Provably Secure Smart Card Authentication Protocol Based on Physically Unclonable Functions

引用

IEEE Transactions on Dependable and Secure Computing 2024年第4期21卷 2766-2778页

作者： Fan, Chun-I Karati, Arijit Wu, Shou-Li National Sun Yat-sen University Department of Computer Science and Engineering Information Security Research Center The Intelligent Electronic Commerce Research Center Kaohsiung804 Taiwan National Sun Yat-sen University Department of Computer Science and Engineering Kaohsiung804 Taiwan

For many industrial applications, the smart card is a necessary safety component in user authentication. Smart cards provided to the users are used in open and public places, making them susceptible to physical and cloning attacks. Thus, the opponent can break the authentication process without the smart card if the information is exposed. In addition, many existing authentication systems employ challenge-response pairs (CRPs) to identify users by creating large numbers of data on the server and spending much time looking for and comparing responses. To address these concerns, we propose a lightweight privacy-preserving authentication protocol in which the physically unclonable function is considered a necessary tool. The suggested technique avoids creating a significant number of CRPs on the server to identify users uniquely. Under formal security models, the proposed protocol is resistant to user impersonation attacks and session key disclosure attacks and achieves robust mutual authentication. Nonetheless, it is immune to other essential security vulnerabilities. Empirical performance analysis demonstrates its viability in comparison to prior works. © 2023 IEEE.

关键词： Authentication

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：