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检索条件"主题词=software algorithms"

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Research and Design of AIS Reception Signal Processing System Based on GNU Radio

Research and Design of AIS Reception Signal Processing Syste...

引用

International Conference on Advanced Communication Technology (ICACT)

作者： Zijiao Zhou Peng Gong Bin Tang Piao He Xiuming Peng Guangwei Zhang National Key Laboratory of Mechatronic Engineering and Control School of Mechatronical Engineering Beijing Institute of Technology Beijing China

ISBN: (数字)9791188428137

ISBN: (纸本)9798331507602

The Automatic Identification System (AIS), as a standard communication and navigation device for ships, plays a significant role in ensuring the safety and efficiency of maritime traffic. The accuracy of the AIS receiver’s signal processing directly affects the bit error rate (BER) and packet error rate (PER) of the AIS system, drawing considerable attention to AIS signal reception and processing technologies. Current research on AIS reception signals mainly focuses on custom implementations using hardware platforms like FPGAs; however, the high cost of hardware implementation has become a limiting factor in the development of AIS signal processing technologies. Therefore, this paper designs an AIS reception signal processing system based on GNU Radio, developing demodulation algorithm and NRZI decoding modules, and testing them with typical demodulation algorithms. Experimental results demonstrate the feasibility and effectiveness of the designed reception signal processing system.

关键词： Costs software algorithms Bit error rate Signal processing algorithms Signal processing Hardware Decoding Artificial intelligence Standards Demodulation

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Development of a Model for Texture Analysis of Machined Parts on CNC Machines

Development of a Model for Texture Analysis of Machined Part...

引用

International Russian Smart Industry Conference (SmartIndustryCon)

作者： Ilya Kovalev David Malykh Alexander Kiselev department of Computer Control Systems MSUT “STANKIN” Moscow Russia department of Robotics and Mechatronics MSUT “STANKIN” Moscow Russia

ISBN: (数字)9798331511241

ISBN: (纸本)9798331511258

This work is devoted to the development of a software module for analyzing the textures of machined parts on CNC machines using computer vision methods. The main goal of the research is to create a tool capable of analyzing geometric parameters of products based on texture properties of materials, which is especially relevant in the conditions of high-volume production. The paper considers modern methods of texture analysis, as well as their robustness to various disturbances such as illumination changes, noise, blurring, rotation and image scaling. An analysis system that combines binocular and texture methods of image processing is proposed, which makes it possible to improve the accuracy of measuring distances to objects on the basis of binocular algorithm, by means of additional analysis of texture properties of surfaces of the processed part.

关键词： Computer vision Image analysis software algorithms Noise User interfaces software Robustness Classification algorithms Surface texture Surface treatment

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Analysis of Visual Information to Determine the Emotional State of People

Analysis of Visual Information to Determine the Emotional St...

引用

International Youth Conference on Radio Electronics, Electrical and Power Engineering (REEPE)

作者： Svetlana M. Kutsenko Elena A. Saltanaeva Tatiana V. Lapteva Nikolay S. Kiselev Information Technology and Information Systems Department Kazan State Power Engineering University Kazan Russian Federation

ISBN: (数字)9798331531836

ISBN: (纸本)9798331531843

The demand for emotion recognition software in various fields of human endeavour is undeniable. Research has focused on the application of various technologies and methods, including machine learning, neural networks and big data analytics. Available software in the field of emotion recognition is characterised by a number of drawbacks: high cost; not always transparent data privacy and ethics; dependence on data quality; and narrow specialisation of data processing. Thus, it is relevant to develop the software taking into account the minimisation of the above disadvantages. In implementing the application, data collection and preparation was carried out, a recognition model was developed using neural networks and machine learning, and the accuracy of the model was evaluated. The application implements user authorisation using encryption algorithms, file uploading, file analysis, saving and viewing the results. The developed software allows recognising six basic emotions: joy, sadness, anger, fear, surprise and neutral state.

关键词： Training Emotion recognition Visualization Analytical models Accuracy Text recognition Neural networks software algorithms Data models software

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Training Neural Networks Based on PSO Algorithm and BP Algorithm

Training Neural Networks Based on PSO Algorithm and BP Algor...

引用

Power Electronics, Computer Applications (ICPECA), IEEE International Conference on

作者： Darong Gao The Electrical Engineering College Northwest Minzu University Lanzhou China

ISBN: (数字)9798331533694

ISBN: (纸本)9798331533700

Signal processing has made extensive use of neural networks. This study examines neural network training using the PSO and BP algorithms. To train the neural network, the PSO algorithm alone, the BP algorithm alone, and the PSO algorithm combined with BP algorithm are examined for the same signal. It is determined that the PSO algorithm in conjunction with the BP algorithm can enhance the network's learning efficiency and accelerate its convergence.

关键词： Training software algorithms Neural networks Signal processing algorithms Signal processing Approximation algorithms software Power electronics MATLAB Optimization

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IoT Based Monitoring System for Health During Menstruation

IoT Based Monitoring System for Health During Menstruation

引用

Sentiment Analysis and Deep Learning (ICSADL), International Conference on

作者： Chinmaya Khadse Shital Hajare Nishad Sheikh Roshni Dahule Priya Kate Department of Computer Science and Engineering Faculty of Engineering and Technology Datta Meghe Institute of Higher Education and Research Sawangi Wardha Maharashtra India Department of Artificial Intelligence and Machine Learning Faculty of Engineering and Technology Datta Meghe Institute of Higher Education and Research Sawangi Wardha Maharashtra India Department of Computer Science and Engineering Faculty of Engineering and Technology Datta Meghe Institute of Higher Education and Research Sawani Wardha Maharashtra India

ISBN: (数字)9798331523923

ISBN: (纸本)9798331523930

The integration of IoT and ML brought forth new prospective solutions in menstrual health management, pertaining to continuous monitoring of physiological signals and personalization of insights for women. This article discusses the usage of IoT, smartphones, and cloud-based systems for tracking vital signs, temperature, pulse rate, and flow of menstruation that will enable pro-active management of the cycle. The use of ML algorithms, including supervised models-like Random Forest and Logistic Regression-and complex techniques like RNNs and LSTM networks-offers added advantages for predicting menstrual cycles and ovulation. These technologies offer personalized health recommendations, early diagnosis of menstrual disorders, and help in communicating with healthcare providers in a very short span of time. While offering huge potential to improve women's health, concerns around data privacy, ethical considerations, and equitable access to these digital health solutions are highlighted. The existing systems showed improvements yet they encountered problems because of insufficient data diversity and health system integration as well as insufficient personalization and imprecise cycle predictions. Data privacy issues and security threats that stem from ML models along with constant bias concerns prevent broad acceptance of ML systems in general use. This research study analyzes IoT and ML applications in menstrual health today and introduces their advantages as well as the barriers that require resolution before mass acceptance can occur. The proposal introduces an approach to create menstrual tracking software through a combination of rule-based systems with ML algorithms that generates precise forecasts alongside tailored information for women who have PCOS or PCOD.

关键词： Data privacy Ethics software algorithms Prediction algorithms software Internet of Things Biomedical monitoring Wearable devices Smart phones Monitoring

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Identification Based on the Optimal Information Structure of Non-Stationary Objects

Identification Based on the Optimal Information Structure of...

引用

International Russian Smart Industry Conference (SmartIndustryCon)

作者： Isroil I. Jumanov Sunatillo M. Xolmonov Olimjon I. Djumanov Department of Artificial Intelligence and Information Systems Samarkand state university named after Sh. Rashidov Samarkand Uzbekistan

ISBN: (数字)9798331511241

ISBN: (纸本)9798331511258

Scientific and methodological foundations have been developed for optimizing the identification of non-stationary objects based on the optimal information structure with mechanisms for selecting an adequate model, reducing excess space, highlighting, dividing random time series, clustering, and forecasting, subject to a priori limitations and parametric uncertainty of processes. The effectiveness of using identifiers based on dynamic models combined with a neural network has been studied. algorithms for combined statistical and dynamic models and neural networks of various architectures have been implemented. Tools for modeling processes and presenting statistical, dynamic and specific characteristics were obtained. The computational schemes of network components with mechanisms for setting variables, optimization, and adaptive network training have been improved.v A cognitive analysis of variables has been implemented taking into account structural complexity, stochasticity of element connections based on a stochastic regression model, by tracking the ambiguity of dynamics. Optimization problems based on the probabilistic risk function and sliding control were solved. A generalized algorithm for identifying non-stationary objects is constructed based on tools for identifying boundaries, the general range of element values, selecting informative elements, and generating training sets. An identification software package was implemented in C++ in the parallel computing environment “CUDA”.

关键词： Training Adaptation models software packages Computational modeling Heuristic algorithms software algorithms Stochastic processes Data models Object recognition Optimization

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Anaheim: Architecture and algorithms for Processing Fully Homomorphic Encryption in Memory

Anaheim: Architecture and Algorithms for Processing Fully Ho...

引用

IEEE Symposium on High-Performance Computer Architecture

作者： Jongmin Kim Sungmin Yun Hyesung Ji Wonseok Choi Sangpyo Kim Jung Ho Ahn Seoul National University

ISBN: (数字)9798331506476

ISBN: (纸本)9798331506483

Fully homomorphic encryption (FHE) is a promising solution for privacy-preserving cloud computing as it enables computations on sensitive data without any risk of data leakage. Despite the significant attention FHE has received, substantial computation and memory demands make it hardly practical for real-world applications. We propose a readily available and practical hardware solution to tackle this problem by using GPUs. GPUs have adequate computational and memory resources to handle complex operations in FHE, including number-theoretic transform (NTT), on which most prior work has deeply focused. However, through detailed analyses, we discover that the performance bottleneck on GPUs is primarily due to simpler element-wise operations, which are limited by off-chip memory (DRAM) bandwidth. Motivated by these observations, we develop Anaheim, a processing-in-memory (PIM) architecture for FHE. We develop optimized FHE execution flows and an end-toend software framework for using PIM with GPUs. Also, we design a versatile PIM unit that handles various modular integer arithmetic PIM instructions, along with an efficient data mapping and associated PIM execution algorithms that minimize data access overhead by leveraging the internal structure of DRAM. Our concerted efforts substantially enhance the performance and energy efficiency of various FHE workloads on GPUs.

关键词： software algorithms Layout Random access memory Computer architecture Bandwidth Transforms software Energy efficiency Hardware Homomorphic encryption

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From Concepts to Applications: A Comprehensive Overview of ROS

From Concepts to Applications: A Comprehensive Overview of R...

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International Conference on Computational Cybernetics (ICCC)

作者： Esmeralda Kadena Marsidi Gupi Beatrix Fregan Aniko Horvath-Kiss Xhezmije Palushi Zoltan Rajnai Banki Donát Faculty of Mechanical and Safety Engineering Obuda University Budapest Hungary Faculty of Economics Governance and Law Barleti University Tirana Albania National University of Public Service Budapest Hungary Faculty of Information Technology Tirana Business University Tirana Albania

ISBN: (数字)9798331502461

ISBN: (纸本)9798331502478

This paper explores the Robot Operating System (ROS), a foundational open-source middleware designed to facilitate robotics development by integrating hardware and software. It provides essential tools and algorithms enabling efficient programming of complex robotic systems. This work delves into the core components of ROS, including its computational graph model, parameter servers, and messaging systems, while highlighting tools that enhance system capabilities. Additionally, the paper reviews navigation algorithms, from traditional ones to advanced path-planning techniques, emphasizing their applications in autonomous mobile robotics. Comparisons of robotics software platforms illustrate the diversity and adaptability required to meet the demands of modern robotics. In the end, this paper emphasizes its critical role in advancing academic research and industrial applications.

关键词： Service robots Navigation Reviews Operating systems software algorithms Hardware Servers Middleware Robots Robot programming

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Research on System Integration Development and Experiment for a Tomato Harvesting Robot

Research on System Integration Development and Experiment fo...

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IEEE International Conference on Industrial Technology (ICIT)

作者： Bingyuan Zhang Xinyu Lu Lingli Zhou Meina Zhang Ni Ren Jizhan Liu Key Laboratory of Modern Agricultural Equipment and Technology Jiangsu University Zhenjiang China Institute of Agricultural Information Jiangsu Academy of Agricultural Sciences Zhenjiang China

ISBN: (数字)9798331521950

ISBN: (纸本)9798331521967

Selective harvesting of fresh-market tomatoes is a labor-intensive task and one of the most cost-intensive stages in tomato production. Therefore, “machine substitution” is being an effective way to achieve automated harvesting for urgent need. To address the harvesting requirements of tomatoes grown on overhead suspension systems in greenhouse facilities, an automated tomato harvesting robot was developed by integrating RGB-D cameras, LiDAR sensor, a four-wheel-drive and four-wheel-steering(4WID4WIS) mobile chassis, a 6DOF collaborative robotic arm, and an integrated picking-recovery mechanism. A software system was developed based on the ROS framework to enable an autonomous “move-observe-harvest” workflow. Tomato detection and localization were implemented by using the YOLOv5 algorithm framework, while motion trajectory control of the robotic arm was achieved through a combination of hand-eye calibration, the RRT-Connect algorithm, and key waypoint strategies. Field tests of the harvesting robot were conducted in a greenhouse production environment. The results showed that the average harvesting cycle was 12.48 seconds per tomato, the harvesting success rate was 84%. These findings provide valuable insights for the development and industrial application of intelligent harvesting equipment tailored to tomatoes cultivated on overhead suspension systems in greenhouse facilities.

关键词： Location awareness Service robots Trajectory planning Robot kinematics Green products software algorithms Robot vision systems Production Manipulators Trajectory

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TidalMesh: Topology-Driven AllReduce Collective Communication for Mesh Topology

TidalMesh: Topology-Driven AllReduce Collective Communicatio...

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IEEE Symposium on High-Performance Computer Architecture

作者： Dongkyun Lim John Kim KAIST

ISBN: (数字)9798331506476

ISBN: (纸本)9798331506483

In deep learning workloads, collective communication across multiple nodes is a critical component in determining overall performance. AllReduce (as well as ReduceScatter and AllGather) is a commonly used collective communication for not only training but also inference. The performance of AllReduce depends on the algorithm utilized (or the “logical” topology) as well as the physical topology of the system that interconnects the nodes together. There has been many work on improving AllReduce performance but prior work have often been topologyaware approach where existing AllReduce algorithms were optimized for a given physical topology. In this work, we propose a topology-driven approach where the topology characteristics are exploited to propose a novel AllReduce collective communication algorithm; thus, the logical topology of the algorithm maps well to the physical topology. In particular, as 2D mesh topology is widely used in various scale-out systems, we propose TidalMesh AllReduce algorithm - a novel approach that exploits the inherent characteristics of the physical 2D mesh topology by pushing flows between the endpoint nodes, similar to a tidal wave, to achieve near-optimal performance for AllReduce. We propose how Sparse TidalMesh AllReduce minimizes bandwidth overhead of TidalMesh with no loss in performance. In addition, we demonstrate how collective communication unrolling can be exploited to enable “software pipelining” of collective communication while exploiting the unique opportunity of superimposing different phases of AllReduce. As a result, TidalMesh results in up to $\mathbf{2 4 \%}$ improvement in AllReduce performance across various deep learning models on a 64 -node $8 \times 8$ 2D mesh, compared to the state-of-the-art while maintaining the simplicity of a logical ring algorithm.

关键词： Deep learning Training software algorithms Computer architecture Bandwidth software Inference algorithms Topology Pipeline processing

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