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检索条件"丛书名=Lecture Notes in Networks and Systems"

共 9905 条记录，以下是2471-2480 订阅

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Evaluation of Point Cloud Data Augmentation for 3D-LiDAR Object Detection in Autonomous Driving 6th

Evaluation of Point Cloud Data Augmentation for 3D-LiDAR Obj...

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6th Iberian Robotics Conference (Robot)

作者： Martins, Marta Gomes, Iago P. Wolf, Denis Fernando Premebida, Cristiano Univ Coimbra Inst Syst & Robot Coimbra Portugal Univ Sao Paulo Inst Math & Comp Sci Sao Paulo Brazil

ISBN: (纸本)9783031586750;9783031586767

Obstacle detection is an essential component for autonomous vehicles to navigate safely. To address certain limitations of 2D object detection, numerous recent approaches have emerged, aiming to leverage LiDAR sensors for 3D object detection. LiDAR sensors, with their depth sensing capabilities, offer richer spatial and geometric data, enabling the accurate estimation of 3D bounding boxes and object orientations. However, the complexity of 3D annotation, in supervised object detection, imposes significant challenges for this task. To address the annotation problem, some studies have explored data augmentation techniques for 3D point clouds, but, not all augmentation methods yield positive impacts on model performance. Therefore, this paper presents an indepth evaluation of global data augmentation techniques, specifically focusing on geometric transformation and noise-based methods for 3D object detection. The results reported in this paper, achieved on the KITTI dataset, showed a relevant difference in some geometric operations, and the importance of noise-based methods.

关键词： 3D object detection autonomous driving deep learning data augmentation

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Ensemble Learning with Physics-Informed Neural networks for Harsh Time Series Analysis 1

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15th International Conference on Autonomous systems

作者： Kayisu, Antoine Kazadi Fasouli, Paraskevi Kambale, Witesyavwirwa Vianney Bokoro, Pitshou Kyamakya, Kyandoghere Univ Klagenfurt Inst Smart Syst Technol Univ Str 65-67 A-9020 Klagenfurt Austria Univ Kinshasa Fac Polytech Kinshasa DEM REP CONGO Univ Johannesburg Dept Elect & Elect Engn Technol Johannesburg South Africa

ISBN: (数字)9783031614187

ISBN: (纸本)9783031614170;9783031614187

In time series data analysis, particularly in dynamic environments like road traffic, the challenges posed by harsh conditions, nonlinearity, and stochasticity are formidable. This paper introduces a novel approach that synergizes Physics-Informed Neural networks (PINNs) and Ensemble Transfer Learning (ETL) to address these challenges, enhancing the accuracy and reliability of time series analysis and prediction. PINNs, by incorporating domain knowledge through partial differential equations (PDEs), enable the integration of underlying physics principles into neural network architectures. This fusion of data-driven insights with physical constraints provides a robust framework for capturing complex relationships in time series data. ETL complements PINNs by leveraging multiple models trained on related datasets, enhancing generalization across scenarios and improving forecasting accuracy. A case study focusing on road traffic data is expected to demonstrate the effectiveness of this concept, utilizing real-world traffic data and encoding basic traffic flow equations with PINNs. The anticipated results suggest that the ensemble of PINNs with transfer learning will surpass traditional methods, exhibiting superior predictive capabilities and adaptability to dynamic conditions, even in unobserved scenarios.

关键词： PINN Ensemble Learning traffic forecasting time-series analysis

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Designing a Water Level Measurement System to Monitor the Flow of Water from the Primary Catchment Source of Tulcan City Using LoRa Communication Technology 4th

Designing a Water Level Measurement System to Monitor the Fl...

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4th International Research and Innovation Congress - Smart Technologies and systems (CI3)

作者： Ramirez Ortega, Paul Maya-Olalla, Edgar Dominguez-Limaico, Hernan M. Zambrano, Marcelo Vasquez Ayala, Carlos Gordillo Pasquel, Marco Univ Tecn Norte Ave 17 Julio 5-21 & Gen Maria Cordoba Ibarra 100105 Ecuador Inst Super Tecnol Ruminahui Ave Atahualpa 1701 & 8 Febrero Sangolqui 171103 Ecuador

ISBN: (纸本)9783031634338;9783031634345

This study focuses on utilizing LoRa wireless communication technology to create a sensor network that measures the water level of a river. The collected data can help assess the current state of the river and detect any changes in its level. Alerts can be sent via email if any changes are detected. The system consists of various components. Firstly, sensor nodes are utilized that employ HC-SR04 sensors for level calculation. Secondly, the ESP32 microcontroller is connected to the LoRa RFM95 module for wireless transmission using LoRa. Finally, the microcontroller handles the processing tasks. The central node acts as a receiver for the data gathered by the sensor nodes. It consists of an Arduino Uno compatible with the LoRa RFM95 module. The central node is connected to a Raspberry PI 4 for processing and then sending the data using the MQTT protocol to the server. The information can then be viewed on the ThingSpeak platform. Tests have been conducted to verify the established communication between the nodes and the Gateway. The results have shown that the LoRa communication parameters are accurately established in the RFM95 modules. Additionally, the data sent from the nodes to the Gateway is visualized on ThingSpeak.

关键词： LoRa LoRa Gateway ThingSpeak catchment source

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The Modified Genetic Algorithm for Solving the Traveling Salesman Problem 28th

The Modified Genetic Algorithm for Solving the Traveling Sal...

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2024 International Conference Automation

作者： Solohubov, Illia Moroz, Artur Oliinyk, Andrii Subbotin, Sergey Skrupsky, Stepan Natl Univ Zaporizhzhya Politech Zaporizhzhya Ukraine

ISBN: (纸本)9783031782657;9783031782664

The Traveling Salesman Problem is one of the most relevant challenges today, as the need to solve it arises in various fields. However, there is no clear algorithm for its solution. It falls within the realm of NP-complete problems and is optimization-oriented. While it is assumed that the solution to these problems involves exhaustive search, in practice, various algorithms and approaches are often used to reduce the volume of analyzed solutions, aiming to find a way to solve the problem without exhaustive search. This includes methods like branch and bound to expedite the search or artificial intelligence approaches such as the ant colony algorithm and genetic algorithms to accelerate the process while achieving the closest possible solution. Genetic methods are one of the most powerful tools for solving such tasks. These algorithms model evolutionary processes, which, thanks to the basic principles of evolution, allow finding better solutions. This approach allows representing the task as a certain evolutionary process. It is based on the fact that from the very beginning, a certain set of solutions is chosen, and they start competing with each other. Each solution represents an individual, and a set of its solutions represents a "gene". Each of these genes during the algorithm's operation can evolve, adapt, or mutate according to the rules of the environment. In the end, only the strongest genes should remain, which will be the approximate optimal solution. A characteristic of these algorithms is that each implementation can be unique. An important task in building algorithms is precisely the optimization of their parameters, as well as choosing the right approach to some of its stages, where only the best of them will remain in the end. This methodology not only allows finding approximately optimal solutions but also provides flexibility and adaptability for various requirements and constraints.

关键词： Algorithmic Modification Genetic algorithm Graph algorithms Mutation Coefficient Optimization TSP Traveling Salesman Problem

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Robust Attitude Control of a Disturbed Multi-rotor Aircraft: Experimental Comparisons 4th

Robust Attitude Control of a Disturbed Multi-rotor Aircraft:...

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4th International Conference on Digital Technologies and Applications (ICDTA)

作者： Hassani, Hamid Mansouri, Anass Ahaitouf, Ali Sidi Mohamed Ben Abdellah Univ Fac Sci Dhar El Mahraz Dept Phys LISAC Lab Fes Morocco Sidi Mohammed Ben Abdellah Univ Fac Sci & Technol SIGER Lab Fes Morocco Sidi Mohammed Ben Abdellah Univ Sch Appl Sci SIGER Lab Fes Morocco

ISBN: (纸本)9783031686528;9783031686535

In this work, a robust nonlinear attitude control is developed for a perturbed quadrotor aircraft. The proposed control scheme combines a finite-time sliding mode control with a smooth-reaching law to achieve the stability of the closed-loop system. The suggested method can provide precise tracking of the predefined trajectories while compensating for the impact of wind disturbances. Experimental comparisons with other recent controllers are conducted to highlight the outperformance of the suggested method in terms of trajectory tracking, robustness, and chattering alleviation.

关键词： Quadrotor smooth reaching law wind disturbances experimental comparisons

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Insights into Age-Related Macular Degeneration Detection: A Comprehensive Review of OCT Image Analysis 1

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4th Congress on Intelligent systems (CIS)

作者： Nejkar, Rahul Sukumar Sayyad, Shabnam Farook Savitribai Phule Pune Univ AISSMS Coll Engn Dept Comp Engn Pune 411001 Maharashtra India Sanjeevan Engn & Technol Inst Panhala 416201 Maharashtra India

ISBN: (数字)9789819990436

ISBN: (纸本)9789819990429;9789819990436

Age-related macular degeneration (AMD) and diabetic retinopathy (DR) are eye disorders that affect the macula, the center of the retina, and can harm an elderly person's vision. The severity of these conditions can require immediate eye care, and each case requires a different treatment. Optical coherence tomography (OCT) is a method for evaluating AMD diagnosis. The early treatment depends on the correct finding of wet and dry AMD. This paper deliberates state-of-the-art methods for automatic and faster classification of wet and dry AMD with deep convolutional neural networks, evaluating their performance results for AMD diagnosis and grading. The main objective of this research is to investigate and evaluate computer-aided diagnostic (CAD) methods for diagnosing and rating AMDs.

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Augmented Nonlinear PID Controller for Human-Robot Collaboration with Uncertainties 7th

Augmented Nonlinear PID Controller for Human-Robot Collabora...

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7th International Conference on Green Technology and Sustainable Development

作者： Van-Truong Nguyen Minh-Tri Phan Gia-Duc Pham Manh-Ha Bui Van-Anh Nguyen Hanoi Univ Ind SMAE Fac Mechatron Hanoi Vietnam Univ Sci & Technol Hanoi Appl Engn Technol Dept Hanoi Vietnam Hanoi Univ Sci & Technol Sch Mech Engn Dept Mechatron Hanoi Vietnam Cranfield Univ Sch Aerosp Transport & Mfg Bedford England

ISBN: (纸本)9783031762314;9783031762321

This paper suggests an augmented nonlinear PID (ANPID) controller for Human-Robot Collaboration with uncertainties. To be more precise, the encouraged controller is constructed based on the design of a Nonlinear PID controller combined with the optimization of controller parameters by the PSO algorithm. Lyapunov's method is utilized to prove the stability of the controller. The ANPID exhibits enhanced performance in addressing instability, increased adaptability, and a more rapid response time. This controller improves precision and safety while dealing with uncertainties. Based on the outcome of the simulation of a robot arm's dynamic model, the ANPID demonstrates better performance compared to conventional PD and PID controllers.

关键词： Human-Robot Collaboration Augmented nonlinear PID PSO algorithm Uncertainties

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Data Science Analysis Curricula: Academy Offers vs Professionals Learning Needs in Costa Rica 1

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11st World Conference on Information systems and Technologies (WorldCIST)

作者： Guzman Benavides, Julio C. Chacon Paez, Andrea Lopez Herrera, Gustavo Univ Costa Rica San Jose Costa Rica State Distance Univ San Jose Costa Rica

ISBN: (数字)9783031456459

ISBN: (纸本)9783031456442;9783031456459

The analysis of large volumes of information has become necessary for decision-making in companies, creating new roles and capacities that must be covered. To meet this demand, institutes and universities have created curricular programs that satisfy this need;however, the coverage of these programs is nonstandard and leaves important topics uncovered. This paper compares a set of academic curricula inside and outside of CostaRica based on the report Computing Competencies for Undergraduate Data Science Curricula - ACM Data Science Task Force. Likewise, the results of a survey with professionals from different industries to identify the topics related to data science that they learned in formal education, work or that they would need to know, providing an overview of the issues that should strengthen or add within the academic curricula analyzed.

关键词： Education Data Science Curricula ACM Data Science

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Control Barrier Functions in Multirotors: A Safety Filter for Obstacle Avoidance 6th

Control Barrier Functions in Multirotors: A Safety Filter fo...

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6th Iberian Robotics Conference (Robot)

作者： Gonzalez-Morgado, Antonio Ollero, Anibal Heredia, Guillermo Univ Seville GRVC Robot Lab Seville Seville Spain

ISBN: (纸本)9783031591662;9783031591679

Similar to the Control Lyapunov Functions (CLFs), whose objective is to achieve the stability of a system, Control Barrier Functions (CBFs) aim to achieve the safety of a system. They serve as a safety filter that guarantees that the system remains in a defined safety region. This article aims at presenting an introductory overview of the theoretical framework of CBFs and of their application. For doing this, we apply the CBFs framework as a safety filter for obstacle avoidance in the XY movement of a multirotor. The safety filter is designed using two different multirotor models, a single integrator model without considering the inertia of the system and a first-order model that captures the dynamics of a velocity control loop. The proposed safety framework is validated with simulations in Matlab and experiments with indoor flights. The results show the importance of correctly modeling the system.

关键词： UAV Control Barrier Function Multirotors Obstacle Avoidance

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An AI and IoT Based Smart Green Home Sustainability 1

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8th Smart Trends in Computing and Communications (SmartCom)

作者： Sharma, Aniva Kulshrestha, Peeyush Poornima Inst Engn & Technol Dept Elect Engn Jaipur India Poornima Inst Engn & Technol Dept Comp Sci Engn Jaipur India

ISBN: (数字)9789819713202

ISBN: (纸本)9789819713196;9789819713202

Indoor air quality (IAQ) also known as the quality of the natural air inside, homes, building and other enclosed spaces where people live or work. It is essential to maintain good indoor air quality because poor (IAQ) can have adverse effects on human well-being. The Research paper described proposed a smart plantation system that uses AI and IoT technologies to monitor and optimize indoor plant growth. With the help of simulation tools, it is possible to analyze and optimize indoor air quality to create healthier and more comfortable indoor environments. In this paper, simulation work is carried out, and the implementation task is considered for extension of work. The simulation proteus software environment is used, which allows microcontroller board and other sensors to make the entire schematic very similar to practical implementation. The smart plantation system utilizes advanced AI algorithms, sensor networks, and automated irrigation systems to create optimal growing conditions for indoor plants. The system is designed to continuously monitor plant health and environmental conditions, making real-time adjustments to the cultivation process. The system will comprise a network of sensors to monitor different quantities such as humidity, temperature, light, and atmospheric and soil moisture. These sensors will transmit the collected data to a central processing unit, where AI algorithms will analyze the information to determine the optimal growing conditions for different plant species.

关键词： Artificial intelligence Internet of Things Indoor pollution Air pollution

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