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Real-Time Distributed Multi-Robot Target Tracking via Virtual Pheromones

Real-Time Distributed Multi-Robot Target Tracking via Virtua...

引用

ieee/RSJ international conference on intelligent Robots and systems (IROS)

作者： Mathew, Joseph Prince Nowzari, Cameron George Mason Univ Dept Elect & Comp Engn Fairfax VA 22030 USA

ISBN: (数字)9781665479271

ISBN: (纸本)9781665479271

Actively searching for targets using a multi-agent system in an unknown environment poses a two-pronged problem, where on the one hand we need agents to cover as much of the environment as possible and on the other have a higher density of agents where there are potential targets to maximize detection performance. This paper proposes a fully distributed solution for an ad hoc network of agents to cooperatively search an unknown environment and actively track found targets. The solution combines a distributed pheromone-based coverage control strategy with a distributed target selection mechanism.

关键词： Target tracking Uncertainty Heuristic algorithms Robot vision systems Distributed databases Cameras Real-time systems

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Design and Embedded Development of MathML Network Mathematical Formula Editor 6

Design and Embedded Development of MathML Network Mathematic...

引用

6th international conference on intelligent computing and Control systems, ICICCS 2022

作者： Xue, Lihong Yunnan Jiaotong College Kunming650500 China

ISBN: (纸本)9781665410359

This article describes the functional characteristics of the network math formula editor and the algorithm implementation of related functions. Users can edit mathematical formulas in GUI or using basic MathML representations, and save them in the form of MathML documents, so that mathematical formulas can be processed and transmitted on the Web in a method different from traditional communication, which solves the problem of the inability of image files to store mathematical information in the past. The disadvantages of being queried and reused, with great flexibility and scalability, the editor also provides formula template customization tools for users to develop personalized formula templates to meet the application needs of different user groups. © 2022 ieee.

关键词： Scalability Layout Control systems Encoding Information exchange Graphical user interfaces

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Robust Data-Driven Control Against Actuator FDI for Unknown Linear systems 18

Robust Data-Driven Control Against Actuator FDI for Unknown ...

引用

ieee 18th international conference on Control and Automation (ICCA)

作者： Liu, Wenjie Sun, Jian Deng, Fang Wang, Gang Chen, Jie Beijing Inst Technol Natl Key Lab Autonomous Intelligent Unmanned Syst Beijing 100081 Peoples R China Beijing Inst Technol Sch Automat Beijing 100081 Peoples R China Beijing Inst Technol Chongqing Innovat Ctr Chongqing 401120 Peoples R China Tongji Univ Dept Control Sci & Engn Shanghai 201804 Peoples R China

ISBN: (纸本)9798350354416;9798350354409

This paper designs a data-driven controller for unknown linear systems whose actuators suffer from false data injection (FDI) attacks, using only noisy input-state data. To achieve this objective, a general FDI attack model is introduced, which imposes constraints only on the switching frequency of attack channels and the magnitude of attack matrices. A time-varying state feedback control law is designed based on offline and online input-state data, which adapts to the channel switching of FDI attacks. This is achieved by solving a data-based semi-definite programs (SDPs) on-the-fly such that stabilizing the set of subsystems consistent with both offline clean data and online attack-corrupted data. It is shown that under mild conditions on the attack and the noise, the feasibility of the proposed SDP guarantees that the controller stabilizes the attack-corrupted system. A numerical example is presented to validate the effectiveness of the proposed method.

关键词： Linear systems

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Leveraging Artificial Intelligence to Secure Wireless Network: Exploring Threats, Existing Approaches, and Proposed Mitigation Strategies

Leveraging Artificial Intelligence to Secure Wireless Networ...

引用

2024 international conference on Innovation and Intelligence for Informatics, computing, and Technologies, 3ICT 2024

作者： Nan Xin, Alice Lee Ramly, Athirah Mohd Behjati, Mehran Sharif, Mhd Saeed Department of Computing and Information Systems Sunway University Selangor Malaysia School of Architecture Computing and Engineering UEL London United Kingdom Intelligent Technologies Research Group School of Architecture Computing and Engineering UEL London United Kingdom

ISBN: (纸本)9798331533137

The exponential growth of network has introduced new Internet-of-Things (IoT) use cases that has enabling us convenience and comfort. The surge of IoT devices due to the capabilities brought by fifth generation (5G) have given rise to security threats and attacks, particularly malware attacks IoT botnets have been an alarming issue, where smart devices can be manipulated by malicious actors to commence subsequent attacks such as Denial of Service (DoS). Traditional and complex security techniques may not be a viable solution towards these resource-constrained devices with limited processing power. Machine Learning techniques (ML) are the rising trend, and it is often used in Intrusion Detection systems and Network Anomaly Detection. This paper emphasizes on analyzing and comparing various ML models on the IoT-23 dataset. It aims to predict anomalies and conclude the model with optimal performance and least computational time cost that can be used for network anomaly detection systems with real-time data in future works. The ML models used in this paper are Decision Trees (DT), K-nearest neighbours (KNN), Random Forest (RF), Naïve Bayes (NB) and Histogram Gradient Boosting (HGB). DT displayed the best performance with an accuracy score of 73% and F1 score of 0.49 with a time cost of 28.22 seconds. ©2024 ieee.

关键词： 5G mobile communication systems

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InCOpt: Incremental Constrained Optimization using the Bayes Tree

InCOpt: Incremental Constrained Optimization using the Bayes...

引用

ieee/RSJ international conference on intelligent Robots and systems (IROS)

作者： Qadri, Mohamad Sodhi, Palonla Mangelson, Joshua G. Dellaert, Frank Kaess, Michael Carnegie Mellon Univ Robot Inst Pittsburgh PA 15213 USA Georgia Inst Technol Sch Interact Comp Atlanta GA 30332 USA Brigham Young Univ Elect & Comp Engn Dept Provo UT 84602 USA

ISBN: (数字)9781665479271

ISBN: (纸本)9781665479271

In this work, we investigate the problem of incrementally solving constrained non-linear optimization problems formulated as factor graphs. Prior incremental solvers were either restricted to the unconstrained case or required periodic batch relinearizations of the objective and constraints which are expensive and detract from the online nature of the algorithm. We present InCOpt, an Augmented Lagrangian-based incremental constrained optimizer that views matrix operations as message passing over the Bayes tree. We first show how the linear system, resulting from linearizing the constrained objective, can be represented as a Bayes tree. We then propose an algorithm that views forward and back substitutions, which naturally arise from solving the Lagrangian, as upward and downward passes on the tree. Using this formulation, InCOpt can exploit properties such as fluid/online relinearization leading to increased accuracy without a sacrifice in runtime. We evaluate our solver on different applications (navigation and manipulation) and provide an extensive evaluation against existing constrained and unconstrained solvers.

关键词： Linear systems Runtime Navigation Message passing Matrices Optimization intelligent robots

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Vec2T5: A Chatbot Integrating Word2Vec and T5 for Improved Performance 5

Vec2T5: A Chatbot Integrating Word2Vec and T5 for Improved P...

引用

5th international conference on IoT Based Control Networks and intelligent systems, ICICNIS 2024

作者： Sallove, R. Inisha Mahalakshmi, T. Sre, V. Renuka Santhi, S. Anitha, V. National Engineering College Department of IT Kovilpatti India

ISBN: (纸本)9798331518097

Chatbots are now vital tools for improving user engagement and offering immediate assistance on a variety of platforms. However, traditional chatbot systems often struggle with balancing computational efficiency and contextual accuracy. This paper introduces Vec2T5, a hybrid chatbot model that combines Word2Vec for intent recognition with T5 (Text-to-Text Transfer Transformer) for dynamic response generation. Combining the best features of both models, Vec2T5 provides real-time, accurate query interpretation and contextually relevant responses to users while making efficient use of available resources. The streamlined architecture enables the system to offer high performance with minimal memory requirements. With a user-friendly interface and the ability to continuously learn from user interactions, Vec2T5 delivers a seamless, intelligent, and responsive chatbot experience, making it an ideal solution for organizations aiming to enhance communication and support. © 2024 ieee.

关键词： Natural language processing systems

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Active SLAM in 3D deformable environments

Active SLAM in 3D deformable environments

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ieee/RSJ international conference on intelligent Robots and systems (IROS)

作者： Xu, Mengya Zhao, Liang Huang, Shoudong Hao, Qi Southern Univ Sci & Technol Dept Comp Sci & Engn Shenzhen Peoples R China Univ Technol Sydney Robot Inst Sydney NSW 2008 Australia Southern Univ Sci & Technol Res Inst Trustworthy Autonomous Syst Shenzhen Guangdong Peoples R China

ISBN: (数字)9781665479271

ISBN: (纸本)9781665479271

This paper considers active SLAM problem for 3D deformable environments where the trajectory of the robot is planned to optimize the SLAM results. A planning strategy combining an efficient global planner with an accurate local planner is proposed to solve the problem. Simulation results under different scenarios have shown that the proposed active SLAM algorithm provides a good balance between accuracy and efficiency as compared to the local planner and the global planner. The MATLAB code of this first active SLAM algorithm for 3D deformable environments is made publicly available.

关键词： Simultaneous localization and mapping Three-dimensional displays Codes Simulation Trajectory Planning intelligent robots

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IPDD: intelligent Parkinson Disease Detection System 4th

IPDD: Intelligent Parkinson Disease Detection System

引用

4th international conference on Smart IoT systems: Innovations and computing, SSIC 2023

作者： Singhal, Manish Tiwari, Vinita Sharma, Ashish Electronic and Communication Indian Institute of Information Technology Rajasthan Kota325003 India Computer Science and Engineering Manipal University Rajasthan Jaipur303007 India

ISBN: (纸本)9789819751990

Worldwide, millions of peoples are affected by complex neuro degenerative disorder, that is known as PD (Parkinson Disease). In recent years, it is very critical for accurate diagnosis of PD at early stage for implementing timely interventions and improving patient life. There have been growing interest in developing intelligent systems for Parkinson’s disease detection, harnessing the potential of cutting-edge technologies such as artificial intelligence, machine l earning, and sensor-based data analysis. This research paper presents an in-depth exploration of an intelligent Parkinson Disease Detection System (IPDDS) designed for early diagnosis and quality level monitoring of PD using two most accurate machine learning techniques—SVM and Random Forest. The presented work relates the use of various performance metrices like Accuracy, Confusion Matrix, Precision, etc. Standard Dataset having voice samples of human’s having Parkinson Disease and not having PD is used to validate the various performance parameters and predict the PD or non-PD. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.

关键词： Neurodegenerative diseases

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Pediatric Vascular Anomalies Recognition with a Swin Transformer Framework 9

Pediatric Vascular Anomalies Recognition with a Swin Transfo...

引用

9th international conference on Image, Vision and computing, ICIVC 2024

作者： Zhang, Xieyang Zhang, Zhao Chen, Siyu Lang, Xun He, Bingbing Zhang, Yufeng School of Information Science and Engineering Yunnan University Kunming China Department of Dermatology Kunming Children’s Hospital Kunming Children’s Hospital Kunming China Yunnan Key Laboratory of Intelligent Systems and Computing Yunnan University Kunming China

ISBN: (纸本)9798350385991

Vascular anomalies primarily manifest in the head and neck area, impacting roughly one in every 22 children. Early and accurate diagnosis of these anomalies holds the potential to significantly improve physical functioning impairments in children. While computer-aided diagnosis (CAD) system can enhance diagnostic accuracy and address the scarcity of medical resources, existing systems for vascular anomalies identification are limited and mainly focus on binary classification tasks like infantile hemangiomas. Motivated by the above problem, this work develops a classification framework using clinical imaging data from Kunming Children’s Hospital, targeting six common vascular anomalies. Specifically, Swin Transformer was chosen as the backbone network for classification due to its ability to capture long-range dependencies of lesions. In addition, Modified RandAugment was employed to enrich the diversity of lesion data and enhance the robustness of the constructed Swin Transformer. Our experimental results demonstrate that the proposed framework can achieve good overall performance and excel in certain disease recognition tasks. This achievement may promote the development of high-quality CAD systems for diagnosing vascular anomalies in children. © 2024 ieee.

关键词： Pediatrics

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Location-aware Collaborative Filtering and Feature Interaction Learning for QoS Prediction

Location-aware Collaborative Filtering and Feature Interacti...

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ieee international conference on Web Services (ieee ICWS)

作者： Wang, Qinjing Yan, Cairui Wang, Jinyu Zheng, Wenguang Xiao, Yingyuan Tianjin Univ Technol Engn Res Ctr LearningBased Intelligent Syst Minist Educ Tianjin 300384 Peoples R China

ISBN: (纸本)9798350368567;9798350368550

With the development of the Internet and the application of cloud computing, the number of Web Services with similar functions is increasing. How to recommend high-quality services that satisfy their needs to users based on the quality of service (QoS) prediction results of Web Services is becoming increasingly important. Using the non-functional attributes of Web Services for QoS prediction has become a major research issue. Among the existing researches, methods based on collaborative filtering (CF) are firstly used in the field of QoS prediction. However, due to the sparsity of the call records of Web Services in the real world, traditional CF methods are greatly limited. In addition, the feature interaction of different dimensions and the importance of different feature combinations between the geographical location of users and services are rarely considered at the same time. In order to address the above, this paper proposes a new QoS prediction model that combines CF and feature interaction learning. The model innovatively uses similarity adaptive corrector to correct QoS, employs an attention factorization machine to model low-order feature interaction, and uses deep neural network to model high-order feature interaction. We conducted a comprehensive experiment with real-world datasets and achieved better QoS prediction accuracy.

关键词： QoS Prediction Collaborative Filtering Feature Interaction Learning Location Feature Similarity Adaptive Corrector

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