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检索条件"主题词=software algorithms"

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Constructing Obstacle Maps for Highly Automated Vehicles Using the Extended Kalman Filter

Constructing Obstacle Maps for Highly Automated Vehicles Usi...

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International Russian Automation Conference (RusAutoCon)

作者： Imil Khairullin Faculty of Information Systems and Technologies Ulyanovsk State Technical University Ulyanovsk Russia

ISBN: (数字)9798350349818

ISBN: (纸本)9798350349825

The paper deals with the development of methods and tools for building obstacle maps for highly automated vehicles (HAV) based on the Extended Kalman Filter (EKF). Obstacle maps are used in the HAV control system for avoiding moving and stationary targets and for localization in conjunction with other positioning tools. The EKF module is used to estimate the position of landmarks and the vehicle itself based on the data received from the front cameras. The data processing involves converting the images into Birds-Eye-View (BEV) projections using an Inverted Perspective Map (IPM) to account for spatial information. The paper describes the methods and algorithms used for image processing, object recognition using a neural network with YOLOv8 architecture, and determination of free space for movement using semantic segmentation based on MobileNetV3 neural network architecture. The results of testing the developed methods and software in the Webots modeling environment are also presented, and the prospects for the development and improvement of the system are discussed. The software is implemented using the ROS2 software platform.

关键词： Location awareness Roads software algorithms Neural networks Urban areas Computer architecture Cameras Control systems Kalman filters Autonomous vehicles

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FairPipes: Data Mutation Pipelines for Machine Learning Fairness

FairPipes: Data Mutation Pipelines for Machine Learning Fair...

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International Workshop on Automation of software Test (AST)

作者： Camille Molinier Paul Temple Gilles Perrouin ESIR University of Rennes Rennes France University of Rennes CNRS Inria IRISA Rennes France PReCISE/NaDI University of Namur Namur Belgium

ISBN: (数字)9798400705885

ISBN: (纸本)9798350352184

Machine Learning (ML) models are ubiquitous in decision-making applications impacting citizens’ lives: credit attribution, crime recidivism, etc. In addition to seeking high performance and generalization abilities, ensuring that ML models do not discriminate against citizens regarding their age, gender, or race is essential. To this end, researchers developed various fairness assessment techniques, comprising fairness metrics and mitigation approaches, notably at the model level. However, the sensitivity of ML models to fairness data perturbations has been less explored. This paper presents mutation-based pipelines to emulate fairness variations in the data once the model is deployed. FairPipes implements mutation operators that shuffle sensitive attributes, add new values, or affect their distribution. We evaluated FairPipes on seven ML models over three datasets. Our results highlight different fairness sensitivity behaviors across models, from the most sensitive perceptrons to the insensitive support vector machines. We also consider the role of model optimization in fairness performance, being variable across models. FairPipes automates fairness testing at deployment time, informing researchers and practitioners on the fairness sensitivity evolution of their ML *** Concepts• software and its engineering → software testing and debugging; • Computing methodologies → Machine learning.

关键词： software testing Support vector machines Adaptation models Sensitivity Computational modeling Prevention and mitigation Pipelines software algorithms Data models software

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A Survey of Lifetime Extension Techniques for High-Reliability Power Electronics

A Survey of Lifetime Extension Techniques for High-Reliabili...

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International Conference on Electrical Machines and Systems (ICEMS)

作者： Min Zhang Yongxing Yang Yukai Wen Wei Jiang Dan Zhao Ke Shen School of Automation Northwestern Polytechnical University Xi'an Shaanxi China School of Electrical Engineering Xi'an University of Technology Xi'an Shaanxi China

ISBN: (数字)9784886864406

ISBN: (纸本)9798350379105

The lifetime of power converters is crucial for the reliability of power electronic systems. Long term exposure to severe thermal stress can lead to cumulative fatigue failure in semiconductor devices and DC-link capacitors. Active thermal control through software optimization of control algorithms has been extensively investigated to mitigate power loss and extend component life. This article aims to provide a comprehensive analysis of state-of-the-art lifetime extension control of power converters. A review of the current status of failure mechanisms and failure criteria will be provided, and technology surveys of lifetime estimation will be detailed. Also, a comparison of lifetime extension control strategies for different converters is carried out.

关键词： Surveys Reviews Semiconductor devices software algorithms Power electronics software software reliability Thermal stresses Stress Optimization

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A robust double-layer affinity based matting method

A robust double-layer affinity based matting method

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Big Data & Artificial Intelligence & software Engineering (ICBASE), International Conference on

作者： Guilin Yao Junjie Chang School of Computer and Information Engineering Harbin University of Commerce Herbin China

ISBN: (数字)9798331506612

ISBN: (纸本)9798331506629

In traditional matting algorithms, sampling and affine methods are the primary approaches. The sampling method provides initial alpha values for each pixel but often results in discontinuities and noise, necessitating affine methods for smoothing. Affine methods, which involve both short- and long-range searches, enhance alpha value continuity between neighboring pixels but have varying effects on different regions. To address this, we propose a dual-layer post-processing matting algorithm that combines robust priors with long-range and shortrange modeling. The robust prior step independently samples each unknown pixel, selecting optimal foreground and background samples to compute initial alpha values. Then, a dual-layer affine framework, utilizing the KNN method and a color linear model, further refines these alpha values. Experiments show that this dual-layer algorithm improves both the visual quality and the accuracy of alpha values for foreground, background, and mixed regions.

关键词： Visualization Solid modeling Smoothing methods Computational modeling software algorithms Color Nearest neighbor methods Solids Sampling methods software engineering

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Algorithm of Automatic Synthesis of Optimal Solutions for Power Systems based on the Method of Dynamic Programming

Algorithm of Automatic Synthesis of Optimal Solutions for Po...

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International Youth Scientific and Technical Conference on Relay Protection and Automation (RPA)

作者： A. A. Voloshin E. A. Voloshin A.I. Kovalenko D.P. Yakovlev E. S. Astakhov I.S. Polygalin D.A. Romanov Relay Protection and Automation of Power System Department National Research University«MPEI» Moscow Russia

ISBN: (数字)9798331501105

ISBN: (纸本)9798331501112

Determination of technically and economically feasible design solutions for power distribution networks remains an urgent task of the electric power industry. Existing design methods, both manual and software, do not allow to fully automate the process and do not take into account distributed energy sources. The article proposes an algorithm for the automatic synthesis of the optimal structure and parameters of the electrical network scheme. To implement the algorithm the method of dynamic programming with ‘collapsing’ of solutions was used, which allowed to significantly reduce the search space and increase the efficiency of calculations. The software implementation of the algorithm was performed in the Java programming language with visualization of the obtained solutions using the *** package. To verify the effectiveness of the proposed approach, computational experiments were carried out on a 13-node scheme of the distribution network. Two tasks were considered: design of a new electrical network and development of the existing electrical network using the algorithm of automatic synthesis of the optimal solution for the power system on the basis of dynamic programming. Various scenarios including different network configurations and substation nominal voltage levels were analyzed in the experiments. The results showed that the proposed algorithm allows to efficiently find optimal solutions, taking into account both technical and economic aspects.

关键词： Visualization Automation Heuristic algorithms Design methodology Power system dynamics software algorithms Distribution networks Voltage software Dynamic programming

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Enhancing Presentation Dynamics with Real-time Hand Gesture Recognition: A Review

Enhancing Presentation Dynamics with Real-time Hand Gesture ...

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Communication, Computer Sciences and Engineering (IC3SE), International Conference on

作者： Divya Upadhyay Pankaj Sati Naman Jain Computer Science and Engineering ABES Engineering College Ghaziabad Uttar Pradesh India

ISBN: (数字)9798350366846

ISBN: (纸本)9798350366853

Consider conducting talks where the presenter uses only hand gestures no buttons or mouse to interact with the audience and control the slides. An in-depth discussion of enhancing presentation dynamics through real-time hand gesture recognition will be covered in this research paper. A presentation's importance in the digital age is underscored by the need to make it more dynamic and engaging. The paper investigates how real-time hand gesture recognition technologies might significantly improve the quality of presentations. In this paper, the instruments and techniques that people are now using are examined closely. Consider cameras like the Microsoft Kinect that can detect hand movements. These enable presenters to transition between slides seamlessly, emphasise key points, and engage with images or videos without uncomfortable pauses. Furthermore, they examine wearable technology with unique sensors that enable presenters to control their presentations without bulky equipment. Presenters now have greater freedom to engage with their audience thanks to wearables that use tiny sensors to interpret hand movements and convert them into actions. Not only that, but this study will go even more deeply into the scientific aspect. This paper will focus on advanced artificial intelligence-based computer programs and devices that can detect hand movements in real time. Teaching a computer to recognize when a user points, swipes, or waves their hand to interact with an audience is analogous to teaching it to do the same. When users combine verbal and hand movements, it gets incredibly lively. This article explores the possibilities of integrating spoken words and hand gestures to provide highly interactive presentations. With the help of this fusion, presenters can more easily convey their message by using their hands to give instructions or add explanations.

关键词： Reviews Education software algorithms Gesture recognition Cameras Real-time systems software

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Enabling User Intent-based Network Path Adaptation for Live Volumetric Streaming

Enabling User Intent-based Network Path Adaptation for Live ...

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IFIP Networking Conference

作者： Peng Qian Ning Wang Foh Chuan Heng Carl Udora Rahim Tafazolli 5GIC&6GIC Institute for Communication Systems (ICS) University of Surrey Guildford Surrey U.K.

ISBN: (数字)9783903176638

ISBN: (纸本)9798350390605

Volumetric video is an emerging media application that enables the projection of people or objects into a virtual space in a real-time and immersive manner. Unlike traditional video, live volumetric video streaming in virtual space allows users to interact with teleported objects with a wide range of intentions. However, a significant technical challenge in this context is the need for real-time network adaptation driven by diverse user intents (e.g., user's movement in the virtual space), which may instantly change the streaming's network demand. To ensure a satisfactory perceived Quality of Experience (QoE) in the face of both intent and network condition uncertainty, we have developed a novel solution framework that allows offline user intent registration and online user intent capture with necessary path adaptation. This path adaptation module is empowered by a novel Multi-Arm Bandit (MAB) based path selection algorithm, with joint consideration of probed application delay and network congestion. Through real and extensive experiments, we have validated the effectiveness of our proposed framework in assuring user QoE under various network conditions and for different user intent scenarios.

关键词： Uncertainty Volume measurement Image edge detection software algorithms Streaming media Media Real-time systems

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Performance Analysis of Predicting LIC Stock Price using Lasso Regression Compared with Random Forest Regression

Performance Analysis of Predicting LIC Stock Price using Las...

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International Conference on Computational and Characterization Techniques in Engineering & Sciences (CCTES)

作者： Chennupati Charan Kumar V Parthipan Department of Computer Science and Engineering Saveetha School of Engineering Saveetha Institute of Medical and Technical Sciences Saveetha University Chennai Tamil Nadu India Department of Big Data and Network Security Saveetha School of Engineering Saveetha Institute of Medical and Technical Sciences Saveetha University Chennai Tamil Nadu India

ISBN: (数字)9798350364699

ISBN: (纸本)9798350364705

With regard to the objective of the entire study, the goal is to improve the accuracy of predicting stock price using Lasso Regression in comparison to Random Forest Regression. The Novel K-Nearest Neighbors and Support Vector Machine Algorithm are the two groups that are the emphasis of this research activity. Each of these groups is carried out ten times. For the purpose of calculating samples, the Clincal software was utilized. The alpha value was determined to be 0.05, and the confidence interval was set at 95%. We took into consideration the stock price prediction dataset that was available on *** and had a size of 12617. With a value of p=0.000 (Independent sample t-test p<0.05), the SPSS statistical analysis prediction of stock price demonstrates that there is a statistically significant difference between the Lasso regression algorithm and Random Forest Regression. This data indicates that the Lasso regression algorithm is superior to Random Forest Regression. For the Random Forest regression technique it obtained a percentage accuracy of 84%, while in the new improved Lasso regression approach it records a greater level of accuracy of 93%. The comparison of Random Forest Regressions and Lasso Regressions in the progress of predicting the stock price analysis shows that the latter was substantially more effective. This was revealed in the accomplishment of the current research development project.

关键词： Support vector machines Accuracy Statistical analysis software algorithms Prediction algorithms software Performance analysis Stock markets Random forests Overfitting

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2D Indoor Localization Using Multipath Triangles in MIMO Networks

2D Indoor Localization Using Multipath Triangles in MIMO Net...

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IEEE Conference on Global Communications (GLOBECOM)

作者： Xuesha Shi Zengshan Tian Ze Li Jian Zou School of Communications and Information Engineering Chongqing University of Posts and Telecommunications China Key Laboratory of Industrial Internet of Things & Networked Control Ministry of Education Chongqing University of Posts and Telecommunications China

ISBN: (数字)9798350351255

ISBN: (纸本)9798350351262

In response to the drawbacks of indoor multi-station joint localization, this paper proposes a high-precision indoor single-station localization technique based on the multipath shape factor (SF). A geometric localization model was constructed using the reflection and direct path. The localization equation was constructed using time of flight (ToF) and angle of arrival (AoA), and the Cramér-Rao lower bound (CRLB) of localization error was derived. Through CRLB, this paper introduced multipath SFs and derived the calculation expression of SFs. However, localization accuracy is affected by observation errors and other factors, and no effective method has been proposed yet. To improve localization accuracy and reduce algorithm complexity, this paper first proposes a compressive sensing multidimensional parameter estimation algorithm based on particle swarm optimization (PSO). Then, this paper proposes a multipath selection algorithm based on the SF. Finally, we conduct the simulation using commercial-grade wireless ray propagation modeling software. The experimental results show that the median location error is around 0.18 m by combining the two algorithms proposed in this paper.

关键词： Location awareness Accuracy Parameter estimation Filtering software algorithms Reflection Mathematical models Complexity theory Particle swarm optimization Compressed sensing

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OmniNxt: A Fully Open-source and Compact Aerial Robot with Omnidirectional Visual Perception

OmniNxt: A Fully Open-source and Compact Aerial Robot with O...

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IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)

作者： Peize Liu Chen Feng Yang Xu Yan Ning Hao Xu Shaojie Shen Department of Electronic and Computer Engineering The Hong Kong University of Science and Technology Hong Kong China Division of Emerging Interdisciplinary Areas The Hong Kong University of Science and Technology Hong Kong China

ISBN: (数字)9798350377705

ISBN: (纸本)9798350377712

Adopting omnidirectional Field of View (FoV) cameras in aerial robots vastly improves perception ability, significantly advancing aerial robotics’s capabilities in inspection, reconstruction, and rescue tasks. However, such sensors also elevate system complexity, e.g., hardware design, and corresponding algorithm, which limits researchers from utilizing aerial robots with omnidirectional FoV in their research. To bridge this gap, we propose OmniNxt, a fully open-source aerial robotics platform with omnidirectional perception. We design a high-performance flight controller Nxt-FC and a multi-fisheye camera set for OmniNxt. Meanwhile, the compatible software is carefully devised, which empowers OmniNxt to achieve accurate localization and real-time dense mapping with limited computation resource occupancy. We conducted extensive real-world experiments to validate the superior performance of OmniNxt in practical applications. All the hardware and software are open-access at 3 , and we provide docker images of each crucial module in the proposed system. Project page: https://***/OmniNxt.

关键词： Robot vision systems software algorithms Autonomous aerial vehicles Cameras software Hardware Sensor systems Real-time systems Sensors Visual perception

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