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Model-Free Unsupervised Anomaly Detection of a General Robotic System Using a Stacked LSTM and Its Application to a Fixed-Wing Unmanned Aerial Vehicle

Model-Free Unsupervised Anomaly Detection of a General Robot...

引用

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

作者： Park, Jae-Hyeon Shanbhag, Soham Chang, Dong Eui Korea Adv Inst Sci & Technol Sch Elect Engn Daejeon 34141 South Korea

ISBN: (数字)9781665479271

ISBN: (纸本)9781665479271

With the growing application of various robots in real life, the need for an automatic anomaly detection system for robots is necessary for safety. In this paper, we develop an anomaly detection method using a stacked LSTM that can be applied to any robot controlled by a feedback control. Our method does not need installation of additional sensors. Our method is model-free and unsupervised because it does not require the analytical model of the system and the training data does not require faulty operation conditions. We validate our method on real fixed-wing unmanned aerial vehicle flight data containing control surface failure scenarios. We demonstrate the superiority of the proposed algorithm over existing anomaly detection methods in the literature. Our code is available at https://***/superhumangod/Model-freeunsupervised-anomaly-detection.

关键词： Training Analytical models Current measurement Training data Robot sensing systems Autonomous aerial vehicles Sensors

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Analysis of Students Performance in Flipped Classroom-based Vocational Education Using data Mining Tools 11

Analysis of Students Performance in Flipped Classroom-based ...

引用

11th ieee international conference on intelligent computing and Information systems, ICICIS 2023

作者： Kamal Eldeen, Yousra O. Abdelraheem, Mohamed Soliman, Taysir Hassan A. Misr International Technological University IT Department Egyptian-German College of Technology Assiut Egypt Assiut University Electrical Engineering Department Assiut Egypt Assiut University Faculty of Computers and Information Information Science Department Assiut Egypt

ISBN: (纸本)9798350322101

This research investigates the impact of applying a Flipped Classroom Approach (FCA) in Vocational Education and proposes an improved approach that integrates Cognitive Theory of Multimedia Learning (CTML) with flipped learning based on Revised Bloom's taxonomy. Educational data mining (EDM) using statistics and data analysis was applied to transform large educational raw data into useful and meaningful information. This information can be applied to gain insights into students and their learning environments, enhance teaching support, and optimize decision-making in educational systems. EDM was performed on the student activities recorded on online learning management system (Moodle) including, pre-class activities, attendance, and after-class assignments. A correlation analysis was performed to explore the relationship between their activities in Moodle and academic performance. Results show that students who followed the flipped learning strategy outperformed those who did not, and the video designed according to CTML had a positive impact on student outcomes. The study also revealed that after-class assignments had a significant influence on students' results, and that the students' final results could be predicted through their assignment performance. © 2023 ieee.

关键词： Students

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Enhanced Angle of Arrival (AoA) Prediction through Neural Networks and Primary and Adjacent Antennas Representation Transformation (PAAR) 18

Enhanced Angle of Arrival (AoA) Prediction through Neural Ne...

引用

18th ieee international conference on advanced Networks and Telecommunications systems, ANTS 2024

作者： Selle, Patrick Sikora, Axel Amft, Oliver Offenburg University of Applied Sciences Offenburg Germany Hahn-Schickard Villingen-Schwenningen & Freiburg Germany University of Freiburg Intelligent Embedded Systems Lab Freiburg Germany

ISBN: (纸本)9798350391725

In this study, we present an enhanced Angle of Arrival (AoA) prediction method using neural networks and the Primary and Adjacent Antennas Representation (PAAR) transformation. PAAR leverages rotational symmetry in segmented antenna data, to transform the data into a rotation-invariant form. Thus, PAAR improves predictive accuracy and stability, especially with limited training data. We conducted experiments with two Digital Video Broadcasting - Terrestrial (DVB-T) datasets and evaluated four different neural network models, each varying in parameter size. Results demonstrate that the PAAR method clearly outperforms the traditional unprocessed approach, which we refer to as the plain approach, in data-limited scenarios, reducing the mean absolute angular error (MAAE) by up to {4 0 %}. However, with extensive training data, the plain approach can surpass PAAR due to error propagation. The study demonstrates that the PAAR method effectively enhances AoA prediction, especially with sparse training data. © 2024 ieee.

关键词： Digital video broadcasting (DVB)

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Design and Realization of intelligent Airborne Information Processing Concept Simulation System 24

Design and Realization of Intelligent Airborne Information P...

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24th ieee international conference on High Performance computing and Communications, 8th ieee international conference on data Science and systems, 20th ieee international conference on Smart City and 8th ieee international conference on Dependability in Sensor, Cloud and Big data systems and Application, HPCC/DSS/SmartCity/DependSys 2022

作者： Xie, Jianchun Bai, Linting Luo, Qing Aviation Key Laboratory of Science and Technology on Airborne and Missile-borne Computer Avic Xi'an Aeronautics Computing Technique Research Institute Xi'an China College of Aerospace Engineering Nanjing University of Aeronautics and Astronautics Nanning China Shenyang Aircraft Design and Reserch Institute Shenyang China

ISBN: (纸本)9798350319934

Facing the development trend of future distributed cloud operations, intelligent operations, and the technical requirements of multi-machine collaborative operations in the aviation field, this paper further studies the unified data transmission and management of multiple platforms based on the research of the unified cloud intelligent combat system architecture. Distributed data storage and management, multi-platform open information processing resource management and other key technologies, on the basis of the principle prototype designed and implemented by ourselves, a set of conceptual simulation platforms have been constructed for the simulation and technical verification of the entire airborne information processing system. © 2022 ieee.

关键词： Distributed cloud

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A Complete Piping Identification Solution for Piping and Instrumentation Diagrams 25

A Complete Piping Identification Solution for Piping and Ins...

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25th ieee international conferences on High Performance computing and Communications, 9th international conference on data Science and systems, 21st ieee international conference on Smart City and 9th ieee international conference on Dependability in Sensor, Cloud and Big data systems and Applications, HPCC/DSS/SmartCity/DependSys 2023

作者： Liu, Shengyong Li, Zhongtao Zhao, Shuai Yang, Lei Zhao, Fu Ge, Chuan University of Jinan School of Information Science and Engineering University of Jinan Shandong Provincial Key Laboratory of Network Based Intelligent Computing Jinan China Jinan Housing and Urban-Rural Development Bureau Jinan China The Shandong Cyberspace Affairs Commission Jinan China Shandong Xiaoya Holding Group Co. Ltd Jinan China Shandong University Jinan China

ISBN: (纸本)9798350330014

This study proposes a pipeline identification method for identifying pipelines in Piping and Instrumentation Diagrams (P&IDs) in image format. Automating this process is an important issue for the process plant industry, as image P &IDs are currently identified manually by humans. As part of research on technology for automatic conversion of image-format piping and instrumentation diagram (P&ID) into digital P&ID, this study proposes a method combining deep learning and traditional image detection to identify various types of pipelines in image format P&ID. The proposed method includes image pipeline extraction, pipeline simulation data augmentation, pipeline identification and fusion. For multiple test P &IDs, using yolov8 based on split coordinate spatial attention and augmented with simulated data, the average precision and recall are 90.5 % and 88.5 %, respectively. Combined with LSD line detection, it takes an average of 100 seconds to recognize a complete image, and the overall pipeline recognition rate can reach 95.5 %. © 2023 ieee.

关键词： Object recognition

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SECURE - MEDSHARE: Decentralized Patient data Sharing for Improved Healthcare

SECURE - MEDSHARE: Decentralized Patient Data Sharing for Im...

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2024 international conference on Advances in data Engineering and intelligent computing systems, ADICS 2024

作者： Kapoor, Vansh Vadagasiya, Dhara Revathy, S. Hindustan Institute Of Technology And Science Department Of Computer Science And Engineering Tamil Nadu Chennai India

ISBN: (纸本)9798350364828

Blockchain provides a decentralized framework for peer-to-peer networks' data and transaction management. The basic approach to the proposed system is to create a trustworthy and secure platform that enables doctors to safely store, access, and manage patients' private medical information while abiding by stringent privacy laws to protect patient confidentiality. data that has been separated into blocks can be distributed because of to the decentralized system. Then, every block is shielded against hackers trying to change the data. All of the network's peers, or miners, or users, must validate each modification to the data using modern cryptography techniques. The SECURE - MEDSHARE system uses blockchain technology to store patient data from different hospitals in a decentralized and secure way, overcoming the limitations of local servers. In an era where data privacy and security are paramount, this Proposed System presents a pioneering solution leveraging blockchain technology for secure medical data sharing. The system's foundation relies on the decentralized nature of blockchain, implemented through Ethereum and Hardhat for robust smart contract deployment and management. Interactions occur via a user-friendly React frontend, integrating seamlessly with MetaMask for secure blockchain transactions. The Proposed System utilizes IPFS for decentralized file storage, ensuring data integrity and accessibility. Smart contracts play a pivotal role, orchestrating access controls and establishing a transparent framework for healthcare data sharing. This innovative approach promises heightened security, privacy, and efficiency in managing sensitive medical information, catering to the evolving needs of modern health care systems. The system's architecture and functionality align with the growing demand for reliable, decentralized solutions in data-sensitive domains, positioning it as a potential cornerstone in revolutionizing healthcare data management © 2024 ieee.

关键词： Blockchain

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A Discrete Missing data Imputation Method Based on Improved Multi-layer Perceptron 11

A Discrete Missing Data Imputation Method Based on Improved ...

引用

11th ieee international conference on intelligent data acquisition and advanced computing systems - Technology and Applications (IDAACS)

作者： Yan, Chunyan Yuan, Jianyu Ye, Zhiwei Yang, Zhiyong Hubei Univ Technol Sch Comp Sci Wuhan Peoples R China Hubei Publ Secur Bur Sci & Technol Informat Dept Wuhan Peoples R China

ISBN: (纸本)9781665426053

data have become an important factor of production in various fields. While there are many missing values due to some irresistible reasons, which may lead to incorrect results and conclusions. A set of imputation methods have been proposed for filling continuous data, while only a few works focus on discrete missing data. In this paper, we propose an improved multi-layer perceptron (IMLP) imputation method based on the momentum gradient descent (MGD) algorithm to impute the discrete missing data via the one-hot encoding technique. To verify the performance of this method, comparisons have been made of mode, K-nearest neighbor, and auto-encoder imputation methods on different missing patterns and missing rates. The simulation result shows that the IMLP has a good imputation performance on discrete data with a high missing rate.

关键词： discrete missing data one-hot technique Multi-layer Perceptron momentum gradient descent algorithm

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Design of a Real-Time Crime Monitoring System using Machine Learning 3

Design of a Real-Time Crime Monitoring System using Machine ...

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3rd international conference on intelligent data Communication Technologies and Internet of Things, IDCIoT 2025

作者： Krishnaveni, A. Manikandan, C. Department ofComputer Science Karpagam Academy of Higher Education Coimbatore India

ISBN: (纸本)9798331527549

Crime in public areas poses risks to individuals and society at large. Traditional crime prevention methods face significant hurdles in detecting and tracking crime. Furthermore, the influx of large volumes of data overwhelms security systems and personnel making security enforcement harder. However, technological innovations have positively influenced different fields, including public safety and crime prevention. This study introduces an innovative system for crime prediction and analysis using machine learning, designed to assist law enforcement in identifying criminals in public spaces. The system enables authorities to input detailed information about criminals, including facial data, which is used to train an advanced recognition model. The system’s ability to provide accurate and timely alerts enhances the efficiency of law enforcement operations. This framework leverages state-of-the-art face recognition technology to offer a scalable and robust solution for crime prevention. By integrating machine learning algorithms with intelligent surveillance systems, the proposed approach addresses the growing need for proactive measures to ensure public safety. Further, this system also highlights the potential of technology to transform traditional crime detection methods, paving the way for smarter and more responsive law enforcement practices. Finally, the proposed system attained a 92% face detection accuracy score which was higher than existing approaches. © 2025 ieee.

关键词： Crime prediction exact location facial data machine learning public surveillance recognition model

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Review on Advancements in Coal Mine Safety and Comprehensive Overview of IoT-based Monitoring systems 3

Review on Advancements in Coal Mine Safety and Comprehensive...

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3rd international conference on Electronics and Renewable systems, ICEARS 2025

作者： Manonmani, A. Nalina, A. Seethaladevi, S. Yashika, S. Sri Saveetha Engineering College Department of Electronics and Instrumentation Engineering Tamil Nadu Chennai India

ISBN: (纸本)9798331509675

Ensuring the safety of miners is a critical priority due to the inherently hazardous conditions in underground mining environments. This research presents a Zigbee-based wireless data acquisition system designed to enhance real-time monitoring of essential environmental parameters such as air quality, temperature, humidity, and toxic gases. Moving beyond conventional methods, the system incorporates an adaptive sensor deployment strategy tailored to the complex and dynamic underground landscape, greatly enhancing data reliability and network resilience. advanced RSSI modeling techniques were applied to validate packet delivery and optimize network performance under changing environmental conditions. Field trials demonstrated that this system achieves exceptional accuracy and efficiency in detecting hazardous conditions, providing a proactive approach to hazard mitigation. The findings highlight the system's ability to transform safety protocols and operational practices in mining with a scalable, robust, and innovative wireless monitoring solution. © 2025 ieee.

关键词： Zigbee

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System Identification and Analysis of Temperature Control System 1

System Identification and Analysis of Temperature Control Sy...

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1st ieee international conference on Advances in Electronics, Communication, computing and intelligent Information systems, ICAECIS 2023

作者： Anitha, M. Prusty, Sankata Bhanjan REVA University School of Electronics and Communication Engineering Bengaluru560064 India

ISBN: (纸本)9798350348057

In real world, most of the phenomenons occur based on some physical, chemical and biological laws. The study of phenomena becomes much easier through the use of mathematical models with various approaches. In many controls engineering, it is often very important to automate the control process and ensure the optimum performance of the system. Many methods are developed to convert the real time data into the mathematical model. The process of obtaining the mathematical relationship of dynamic behavior of the system is known as system identification. The system identification using empirical method is carried based on the datasets imported into the MATLAB for temperature control system Heat exchanger system. The proportional integral derivative PID controller is used to uplift the substantial optimum performance of the system. The best fit transfer function is identified and the states space model and transfer function model are compared in system identification SI tool box in MATLAB. © 2023 ieee.

关键词： Three term control systems

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