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Integrated AI-Based Pipeline for Law Enforcement Application: FIR Assistance 5th

Integrated AI-Based Pipeline for Law Enforcement Application...

引用

5th international conference on computing and Network Communications, CoCoNet 2023

作者： Amruth, A. Ramanan, R. Paul, Rhea Pranav, R. Gupta, Deepa Vekkot, Susmitha Nair, Priyanka C. Department of Computer Science and Engineering Amrita School of Computing Amrita Vishwa Vidyapeetham Bengaluru India Department of Electronics and Communication Engineering Amrita School of Engineering Amrita Vishwa Vidyapeetham Bengaluru India

ISBN: (纸本)9789819747108

This paper presents an integrated AI-based pipeline for law enforcement applications, specifically targeting the creation of first information report (FIR) in the Kannada language. The pipeline comprises a speech processing block utilizing automatic speech recognition (ASR) models to convert spoken Kannada into text, and a natural language processing block employing advanced AI techniques for information extraction and generating concise FIR summaries. The research focuses on optimizing and streamlining the FIR creation process by leveraging AI technologies and overcoming data scarcity in the Kannada language through data augmentation techniques. OpenAI’s Whisper is used for ASR, resulting in two-word error rate in this use case. For information extraction, a Bi-LSTM neural network is employed for named entity recognition (NER) with a performance of 94%. The proposed NER model utilizes three tags, which can be expanded to accommodate additional tags as per FIR requirements. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.

关键词： FIR filters

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PITD3-based Autonomous Evasion Decision-making Method for Aircraft 43

PITD3-based Autonomous Evasion Decision-making Method for Ai...

引用

43rd Chinese control conference, CCC 2024

作者： Liu, Chang Dou, Liqian Zhang, Ruilong Tang, Yifan Ren, Mengyuan Zhang, Lun School of Electrical Engineering and Automation Tianjin300072 China Beijing Aerospace Automatic Control Institute China Tianjin Aerospace Institute of Computing Technology Tianjin300308 China

ISBN: (纸本)9789887581581

Outstanding autonomous evasion decision-making capability has an important significance for ensuring flight safety and enhancing the autonomy of the aircraft. In this paper, a prediction information-based TD3 (PITD3) evasion decision-making algorithm for aircraft is proposed, which can autonomously evade the interceptors' attack in an antagonistic environment. Firstly, an antagonistic environment is described according to environmental constraints and the dynamics of the aircraft and interceptor. Secondly, the autonomous decision-making process of the aircraft facing the threat target is modelled as a Markov decision process to describe the state information of the aircraft and interceptor. Finally, an autonomous evasion decision-making method based on the twin delayed deep deterministic policy gradient (TD3) is designed to find the optimal strategy, and the effectiveness of the proposed autonomous evasion decision-making method is demonstrated by simulation results and comparative experiments. © 2024 Technical Committee on control Theory, Chinese Association of Automation.

关键词： Markov processes

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IoT Based Smart Waste Monitoring System Envisioning a Sustainable Smart City

IoT Based Smart Waste Monitoring System Envisioning a Sustai...

引用

2024 IEEE international conference on computing, Applications and Systems, COMPAS 2024

作者： Aurko, Najmus Saquib Masum, S.M. Hossain, Md Sajid American International University Bangladesh Computer Science and Engineering Dhaka1229 Bangladesh American International University Bangladesh Electrical and Electronic Engineering Dhaka1229 Bangladesh

ISBN: (纸本)9798331529765

This paper introduces a smart approach to waste management through the integration of smart technologies. Our proposed system employs the ESP8266 Wi-Fi module to enable remote notification, ensuring efficient waste monitoring both indoors and outdoors. The core components include an Ultrasonic Sensor HC-SR04 for real-time monitoring of the waste bin's fill level, an IR sensor to facilitate automated lid opening upon user proximity, and a servo motor to control the lid mechanism. Upon detection of fullness of the waste bin, the system triggers a buzzer, providing an audible alert for the user and encouraging the user timely waste disposal. The innovation aimed for a more cost effective and economically beneficial system. The innovation extends beyond conventional waste monitoring because we are not only implementing it indoors but also outdoors to monitor waste disposal which will maintain a clean environment overall. The paper outlines the implementation of a client-server model, emphasizing its potential to foster a pollution-free society, good health, and a cleaner environment. © 2024 IEEE.

关键词： Ultrasonic sensors

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Design of the Improved electrical and Technological Modes control Algorithms for Various Classes of EAFs

Design of the Improved Electrical and Technological Modes Co...

引用

2023 international Ural conference on electrical Power engineering, UralCon 2023

作者： Nikolaev, A.A. Ivekeev, V.S. Tulupov, P.G. Efremov, V.A. Nosov Magnitogorsk State Technical Universiti Magnitogorsk Russia

ISBN: (纸本)9798350303391

The article presents the results of theoretical and experimental research on the development and improved algorithms and automatic control systems implementation for existing metallurgical furnaces, such as electric arc furnaces (EAFs) and ladle furnaces (LF) electrical modes, which are based on the use of information about higher harmonics of voltages and currents of electric arcs. The use of these algorithms and control systems provides an improvement in the time, energy and technological performance of the EAF and LF. It became possible due to the units electrical modes dynamic adaptation, determined by the on-load tap-changer stage of the furnace transformer and additional reactor (if any), as well as the number of the operating curve in the process of melting the metal charge in Chipboard or out-of-furnace processing of liquid steel in LF. Also, the paper presents the results of the usage of improved control system algorithms implemented in the existing EAF and LF of various classes and capacities operating at metallurgical enterprises. © 2023 IEEE.

关键词： Slags

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Mobile robot perception system in ROS 2 on embedded computing platforms 18

Mobile robot perception system in ROS 2 on embedded computin...

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18th IFAC conference on Programmable Devices and Embedded Systems (PDES)

作者： Zemcik, Tomas Kratochvila, Lukas Brno Univ Technol Brno Czech Republic

In this paper a perception system of a mobile robot is proposed and implemented combining a LiDAR sensor with a colour camera. Localisation of unknown objects in an a priori known environment and their classification is required in order for the robot to safely and reliably navigate the working area. To this end, a pipeline is proposed to process and fuse the LiDAR 3D point-cloud data with a monocular colour camera image classifications yielding precisely localised 3D detections with class designations. The proposed pipeline is designed to run on limited computational power embedded platforms in the ROS 2 environment, and has been tested on a robotic testbench. Copyright (c) 2024 The Authors. This is an open access article under the CC BY-NC-ND license (https://***/licenses/by-nc-nd/4.0/)

关键词： Mobile robot known environment ROS 2 sensor fusion object detection 3D object localisation

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Optimal Energy Management based on Dynamic Programming

Optimal Energy Management based on Dynamic Programming

引用

2024 international conference on Sustainable computing and Integrated Communication in Changing Landscape of AI, ICSCAI 2024

作者： Haripriya, D. Dahiwade, Mandakini Kotiyal, Arnav Al-Farouni, Mohammed Yadav, Kanchan Francis Raj, J. Relin Department of CSE Veltech Ranagarajan Dr.Saguntala R&D Institute of Science and Technology Avadi Tamilnadu Chennai India Department of Basic Engineering Indira College of Engineering and Management Pune India Department of Computer Science & Engineering Graphic Era Deemed to be University Dehradun India Department of computers Techniques engineering College of technical engineering The Islamic university Najaf Iraq Department of Electrical Engineering GLA University Mathura India Department of Electronics and Communication Engineering Saveetha School of Engineering Saveetha Institute of Medical and Technical Sciences Chennai India

ISBN: (纸本)9798350355338

The strategy based on reinforced learning will be able to present a solution that is close to the optimal solution achieved by using Dynamic Programming (DP), and the power distribution for hybrid vehicles also seems promising with DP. It addresses nonlinear dynamical systems' optimal control issues. However, DP cannot be applied to the majority of problems of practical interest due to its high complexity in terms of computation and dimensionality. In various energy policies, variability has not been addressed, and it is based on fixed driving profiles, which affect vehicle operation. The proposed study's goal is to create an optimal hybrid energy management system that generates more power at the lowest possible cost. The control strategy has been formed based on DP through the rule extraction process, and the fuel consumption must be minimized for the drive cycles. It has simple mathematical foundations, ensures the optimal solution for a given tolerance, and can be easily implemented in a short computer program. The strategy is evaluated in terms of real and predicted values, which makes the performance indices, and this comparison is done on different levels of time. © 2024 IEEE.

关键词： Hybrid power

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A Model for Segmentation and Classification of Skin Diseases using YOLO Algorithm 4

A Model for Segmentation and Classification of Skin Diseases...

引用

4th IEEE international conference on Smart Technologies in computing, electrical and Electronics, ICSTCEE 2023

作者： Vishal, D. Venkatesh Manikandaprabhu, M. Vishnuvardhan, B. Yuvaraj, S. Subha, R. Sri Eshwar College Of Engineering DepartmentofComputer Science And Engineering Coimbatore India

ISBN: (纸本)9798350384628

The difficulties people encounter in their daily lives are often caused by skin problems. Nonetheless, a large number of people are unaware of how serious skin diseases are. Many things can lead to skin conditions. In the past, identifying skin illnesses was a tedious, time-consuming process that called for specialist knowledge. It needed visual inspection and the assimilation of clinical data. But as technology advanced, more machine learning (ML) algorithms for picture recognition and prediction were created. As a result, large number of effective and automated classification methods for multiclass skin diseases has been made available. This paper compares and contrasts the performance of two different variants of the YOLO (You Look Only Once) algorithm (YOLOv7 and YOLOv7-x) for the automatic segmentation and classification of specific skin disorders. © 2023 IEEE.

关键词： Image recognition

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The separation theorem for mean-field linear quadratic optimal control problem with partial information 5

The separation theorem for mean-field linear quadratic optim...

引用

2024 5th international conference on electrical Technology and automatic control, ICETAC 2024

作者： Song, Hairong School of Control Science and Engineering Shandong University Shandong Jinan250061 China

We investigate the separation principle for a class of mean-field stochastic optimal control problems with partial information, where the linear stochastic dynamic system is observed through a linear noisy channel. In our model, the time inconsistency caused by the mean-field terms makes the dynamic programming principle (DPP) inapplicable, which immediately leads to difficulties in deriving the separation principle. Utilizing the optimal filtering equations in several dimensions, we can transform the stochastic optimal control problem with partial information into one with complete details. Subsequently, the Hamilton-Jacobi-Bellman (HJB) equation that can solve the optimal control is obtained with the support of the dynamic programming principle. The separation principle for solving the optimal control of the original problem is derived. © Published under licence by IOP Publishing Ltd.

关键词： Dynamic programming

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Comparative Study of Perturb and Observe Incremental Conductance and Particle Swarm Optimisation for Maximum Power Point Tracking Under Changing Irradiance 2

Comparative Study of Perturb and Observe Incremental Conduct...

引用

2nd international conference on Electronics, Energy and Measurement, IC2EM 2023

作者： Bouguerra, Assala Badoud, Abd Essalam Mekheilef, Saad Chouder, Aissa University of Setif 1 Automatic Laboratory of Setif Department of Electrical Engineering Setif Algeria School of Science Computing and Engineering Technologies Swinburne University of Technology HawthornVIC3122 Australia University of m'Sila Electrical Engineering Laboratory Departement of Electrical Engineering M'sila Algeria

ISBN: (纸本)9798350314243

Increasing the power output of photovoltaic (PV) systems is critical for efficient energy harvesting. This work gives a comprehensive comparison of three frequently used Maximum Power Point Tracking (MPPT) algorithms: Perturb and Observe (P&O), Incremental Conductance (Inc-Cond), and Particle Swarm Optimisation (PSO). The research looks at the performance of these algorithms under constant and variable irradiance settings with a constant temperature. The simulation findings highlight the merits and weaknesses of each method in terms of tracking efficiency, convergence speed, and robustness. The findings provide useful insights for determining the best MPPT algorithm for PV systems depending on unique environmental circumstances. © 2023 IEEE.

关键词： Energy harvesting

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Magnetic Levitation control Using Deep Reinforcement Learning and Prioritized Experience Replay with Action Noise Variations 4

Magnetic Levitation Control Using Deep Reinforcement Learnin...

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4th international conference on Power, control and computing Technologies, ICPC2T 2025

作者： Pare, Gopala Shil, Manas Pillai, G.N. Dey, Arnab Department of Electrical Engineering Indian Institute of Technology Roorkee India Mehta Family School of Data Science and Artificial Intelligence Indian Institute of Technology Roorkee India

ISBN: (纸本)9798331530402

In recent years, Reinforcement Learning (RL) has emerged as a promising approach for addressing control problems in complex, nonlinear environments. The ability of RL algorithms to autonomously learn optimal control policies without requiring an explicit system model makes them particularly suited for real-time applications in fields like robotics and industrial automation. This paper investigates the application of RL algorithms for controlling a magnetic levitation (maglev) system, which presents significant challenges due to its nonlinear dynamics. The Twin Delayed Deep Deterministic Policy Gradient (TD3) algorithm and the integration of Prioritized Experience Replay (PER) are employed to enhance learning efficiency. The impact of varying action noise (random perturbations added to actions) for exploration and system performance is explored;results demonstrate that TD3 with PER achieves superior stability, faster convergence, and reduced rise and settling times without overshoot. These findings emphasize the importance of tailored exploration strategies in optimizing control policies for complex environments, highlighting the potential of advanced RL techniques for real-time control applications. © 2025 IEEE.

关键词： Reinforcement learning

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