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检索条件"任意字段=Proceedings of the 6th International Conference on Algorithms, Computing and Systems"

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20th international conference on Hybrid Intelligent systems, HIS 2020 and 12th World Congress on Nature and Biologically Inspired computing, NaBIC 2020

20th International Conference on Hybrid Intelligent Systems,...

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20th international conference on Hybrid Intelligent systems, HIS 2020 and 12th World Congress on Nature and Biologically Inspired computing, NaBIC 2020

ISBN: (纸本)9783030730499

the proceedings contain 78 papers. the special focus in this conference is on Hybrid Intelligent systems. the topics include: Text Classification Using Convolution Neural Networks with FastText Embedding;deep Convolutional Neural Network Based on Wavelet Transform for Super Image Resolution;optimizing Instance Selection Strategies in Interactive Machine Learning: An Application to Fraud Detection;building IoT Analytics and Machine Learning with Open Source Software for Prediction of Environmental Data;ANFIS-Based Inverse Kinematics and Forward Dynamics of 3 DOF Serial Manipulator;design and Development of Intelligent Pesticide Spraying System for Agricultural Robot;solving Dynamic Bag-of-Tasks Scheduling Problem in Heterogeneous Multi-cloud Environment Using Hybrid Bi-Level Optimization Model;Caching Mechanisms Evolution in CCN Architectures;SentiLSTM: A Deep Learning Approach for Sentiment Analysis of Restaurant Reviews;auto-Encoder Based Wavelet and Extreme Learning Machine for Face Recognition;characterizing Antennas’ Radiation Pattern Using Bernoulli Lemniscates;analysis of Metaheuristics Feature Selection Algorithm for Classification;hybrid Genetic algorithms to Solve the Traveling Salesman Problem;hybridization of Adaboost with Random Forest for Real-Time Prediction of Online Shoppers’ Purchasing Intention;change Detection in Satellite Imagery: A Multi-label Approach Using Convolutional Neural Network;inverse Neural Control of a Magnetic Levitation System: Experimental Results;COVID-19 Detection Using Deep Learning;an Isolation Forest Learning Based Outlier Detection Approach for Effectively Classifying Cyber Anomalies;an Effective Heart Disease Prediction Model Based on Machine Learning Techniques;optimal Design of Fuzzy Controllers Using the Multiverse Optimizer;sparse Wavelet Auto-encoder for Covid-19 Cases Identification;a New Bi-objective Classic Transportation Model Considering Social Justice;emotion Recognition Using Multimodalities.

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proceedings of ITNT 2020 - 6th IEEE international conference on Information Technology and Nanotechnology

Proceedings of ITNT 2020 - 6th IEEE International Conference...

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6th IEEE international conference on Information Technology and Nanotechnology, ITNT 2020

ISBN: (纸本)9781728170411

the proceedings contain 194 papers. the topics discussed include: the efficiency of deep learning algorithms for detecting anatomical reference points on radiological images of the head profile;calculation of thermal processes during laser treatment of dual phase steel using computer-generated diffractive optical element;the two reflector design problem for forming flat wavefront from a point source;on possibility of using of spectral analysis for control the energy distribution of electromagnetic waves in radar channels;asymmetric resonances and field enhancement of hybrid plasmon-waveguide modes in CdTe structures;study of GAN-based image reconstruction for diffractive optical systems;spatio-temporal graph convolutional networks for short-term traffic forecasting;and interference shaper of polarization-inhomogeneous laser beams based on a spatial light modulator.

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proceedings of H2RC 2020: 6th international Workshop on Heterogeneous High-Performance Reconfigurable computing, Held in conjunction with SC 2020: the international conference for High Performance computing, Networking, Storage and Analysis

Proceedings of H2RC 2020: 6th International Workshop on Hete...

引用

6th IEEE/ACM international Workshop on Heterogeneous High-Performance Reconfigurable computing, H2RC 2020

ISBN: (纸本)9781665415927

the proceedings contain 6 papers. the topics discussed include: programming reconfigurable heterogeneous computing clusters using MPI with transpilation;evaluating FPGA accelerator performance with a parameterized OpenCL adaptation of selected benchmarks of the HPC-challenge benchmark suite;exploring the acceleration of nekbone on reconfigurable architectures;FPGA acceleration of fluid-flow kernels;FPGA-as-a-service toolkit (FaaST;and OpenCL-enabled parallel raytracing for astrophysical application on multiple FPGAs with optical links.

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Advanced Object Tracking in Self-Driving Cars: EKF and UKF Performance Evaluation 6

Advanced Object Tracking in Self-Driving Cars: EKF and UKF P...

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6th IEEE Novel Intelligent and Leading Emerging Sciences conference, NILES 2024

作者： Ragab, Hussam Khamis, Salah Napoleon, Sameh A. October 6 University Faculty of Engineering Department of Electronics and Electrical Communication 6th of October City Egypt Tanta University Faculty of Engineering Department of Electronics and Electrical Communication Tanta Egypt

ISBN: (纸本)9798350378511

Sensor fusion offers significant advantages over analyzing individual data sources separately, leveraging the complementary strengths of multiple sensors in various applications. the use of multiple sensors enhances the accuracy and reliability of tracking systems. this paper proposes a comparative study of multi-sensor fusion algorithms, focusing on the integration of radar and lidar data for tracking dynamic objects in the environment. the sensor data used by the fusion algorithms mainly consists of dynamic states (position, velocity, and additional parameters) of surrounding objects. this work specifically evaluates the accuracy and consistency of the Extended Kalman Filter (EKF) and the Unscented Kalman Filter (UKF). the study uses different models, incorporating angular velocity data from radar. Implemented in C++ and visualized using Python, the results demonstrate that the UKF outperforms the EKF across various state variables. the UKF demonstrates lower Root Mean Square Error (RMSE) values due to its superior handling of non-linearity. the consistency of both filters is confirmed using the Normalized Innovation Squared (NIS) statistic, which also addresses how to deal with faulty data. these results highlight the potential of the UKF to enhance the precision of object tracking in autonomous driving applications. © 2024 IEEE.

关键词： Extended Kalman filters

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A Proposed Multi Layer CNN Architecture for Detecting Bangla Traffic Sign 6

A Proposed Multi Layer CNN Architecture for Detecting Bangla...

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6th international conference on Electrical Engineering and Information and Communication Technology, ICEEICT 2024

作者： Tushar, Md. Jahan, Israt Sarker, Teerthanker Rukhsara, Lamia Rabeya, Tapasy Daffodill International University Dept. of Cse Bangladesh

ISBN: (纸本)9798350385779

Detecting Bangla traffic signs in Bangladesh is crucial for road safety as it ensures effective communication with drivers who primarily understand Bengali. Accurate recognition of these signs can significantly reduce accidents and enhance compliance with traffic regulations, ultimately saving lives on the country's roads. this study delves into the development of a multi-layer Convolutional Neural Network (CNN) architecture specifically designed for precise Bangla traffic sign detection. the dataset was collected from Dhaka by us and aims to accurately represent the road systems in *** used a range of powerful deep learning algorithms, such as DenseNet201, ResNet50, VGG19, Xception, CNN01, and CNN02, to tackle the traffic sign detection task. these algorithms were selected for their impressive track record in image classification tasksthe models were improved to increase reliability after being trained on a well-rounded dataset collected directly from *** a careful examination, DenseNet201 stood out as the best model, achieving an impressive accuracy of 99.65%. this impressive accomplishment highlights the ability of the DenseNet201 architecture to recognize complex features found in Bangla traffic *** there is not much research paper about bangla traffic sign *** it is hard to compare. there is one paper of Uddin, Md Mahatab et al about bangla traffic sign identification. His CNN model achieved 98% accuracy. Our study addresses a significant gap in the field of Bangla traffic sign detection, especially considering the lack of existing research papers on the subject. In addition, it highlights the significance of choosing CNN architectures that are customized for specific datasets and tasks, thus enhancing the accuracy and effectiveness of machine learning models in real-world scenarios. © 2024 IEEE.

关键词： Roads and streets

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Application Research of Graph Embedding Method Based on Heterogeneous Graph 6

Application Research of Graph Embedding Method Based on Hete...

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6th IEEE international conference on Power, Intelligent computing and systems, ICPICS 2024

作者： Yang, Shaohua Zhou, Qi China Electronics Technology Group Corporation 20th Research Institute Xi'an China

ISBN: (纸本)9798350374315

In this paper, we propose an innovative graph embedding method-HGAEN2V, which aims to solve the problem of node representation learning in heterogeneous graphs. Traditional graph embedding techniques face challenges when dealing with heterogeneous graphs containing multiple node and edge types, because they often ignore the complex and diverse relationship patterns between nodes. To overcome this constraint, we integrate the effective structural information capture of Node2Vec with the multi-level attention mechanism of HAN to create a hybrid model capable of thoroughly exploring the structural and semantic features of heterogeneous graphs. Initially, we enhance Node2Vec by refining the random walk strategy to achieve a balanced exploration and exploitation across various node and edge types. this adjustment enables the generation of initial embeddings that accurately portray the local neighborhood structure of nodes. then, two layers of attention mechanisms are introduced. the first layer focuses on the node level, and emphasizes the context that has the greatest impact on the current node by adaptively assigning the weights of neighbor nodes. the other layer focuses on the meta-path level, and the composite relations represented by different meta-paths are assigned different attention weights to distinguish the contributions of different types of connection patterns to node embedding. through experimental evaluation, the superior performance of the proposed model on benchmark datasets is verified. © 2024 IEEE.

关键词： Graph embeddings

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An in-Depth Analysis for Machine-Vision-Based Mango Leaf Diseases Recognition 6

An in-Depth Analysis for Machine-Vision-Based Mango Leaf Dis...

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6th international conference on Mobile computing and Sustainable Informatics, ICMCSI 2025

作者： Das, Prothoy Rahman, Md. Ataur Habib, Md. Tarek Khan, Md. Abbas Ali Islam, Mohammad Monirul Department of Computer Science and Engineering Daffodil International University Dhaka Bangladesh Department of Computer Science and Engineering Independent University Bangladesh Dhaka Bangladesh

ISBN: (纸本)9798331522667

Many leaf diseases that affect crop health cause severe mango farming concerns. this study employed deep learning techniques to analyze mango leaf disease categorization comprehensively. this study looks at the classification of five different mango leaf diseases using convolutional neural networks (CNNs): powdery mildew, dieback, gall midge, anthracnose, and healthy leaves. A dataset of 661 raw images was first gathered, and these raw images were augmented to create a final dataset of 2678 images. the study examines how preprocessing methods affect classification accuracy using five CNN models before and after data preprocessing. the outcomes show notable gains in accuracy following preprocessing, highlighting its critical function in improving model performance. Additionally, a new custom model is proposed and evaluated, demonstrating its effectiveness in reaching an impressive accuracy of 98.50%. this comparative study shows that the proposed model outperforms current CNN architectures, indicating that it has the potential to classify mango leaf diseases accurately. Our research aims to highlight the importance of preprocessing techniques and creating customized deep-learning models by presenting an effective method for automated mango leaf disease identification. © 2025 IEEE.

关键词： Fruits

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6th international conference on Industrial Engineering, ICIE 2020

6th International Conference on Industrial Engineering, ICIE...

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6th international conference on Industrial Engineering, ICIE 2020

ISBN: (纸本)9783030548131

the proceedings contain 146 papers. the special focus in this conference is on Industrial Engineering. the topics include: Restoration of the Resource of Aviation Equipment Parts by Re-Hardening;method of Energy Efficiency Evaluation for Airplane Active Fuel System Pumping Groups;modification of Two-Stage Coaxial Gearbox;principles of Designing a Mobile Wind Turbine for the Arctic and the Far North;variable Speed Mechanisms of the Pipeline Valve Drive;new Mechanism for Composite Materials Compaction;research into Geometry of Direct-Flow Duct of Hydraulic Generator;improvement of Technical Means for Running-in and Testing Small-Sized Tractor Engines;theoretical Investigations of Journal Bearings with Micro-Dimples;research to Determine the Installation of Additional Stabilizer Bars for the Modernization of Trucks;diagnosing Continuous Dynamic systems Using Parametric Functions Sensitivity;performance Assessment in Design of High-Speed Automatic Machines Based on Analysis of their Dynamics;dynamic Analysis of Irregular Motion Stirrer with Elliptical Gear;the Program for Calculating the Critical Speed of Shaft Rotation;braking Energy Recuperation Management System of Device with Flywheel Storage;dynamics of Hydraulic Drive Equipped with Discrete Return Flow Controller;to Issue of Semiotic Component Visible for Pilot of Space Model Beyond Cabin of Aircraft Simulator;investigation of Wear Mechanisms in Heat-Resistant Coated Steels due to Frictional Heating in the Course of Sliding Friction with Resource Lubrication;to Issue of Dynamics of Solid Body in Gravitational Field of the Earth;Prospects of Increase of Small Micro Turbine—CHP systems Efficiency by Perfection of the thermodynamically Cycles;technology for Creating Compacted Bulk Layer of Catalysts or Adsorbents.

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ICCDE 2020 - 2020 the 6th international conference on computing and Data Engineering;AIEE 2020 - 2020 international conference on Artificial Intelligence in Electronics Engineering

ICCDE 2020 - 2020 the 6th International Conference on Comput...

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6th international conference on computing and Data Engineering, ICCDE 2020 and 2020 international conference on Artificial Intelligence in Electronics Engineering, AIEE 2020

ISBN: (纸本)9781450376730

the proceedings contain 51 papers. the topics discussed include: refining the round robin algorithm using a recomputed time quantum: a comparison;integrating user-defined priority tasks in a shortest job first round robin (SJFRR) scheduling algorithm;utilizing dynamic mean quantum time round robin to optimize the shortest job first scheduling algorithm;knowledge-based multimodal intention active perception algorithm research;SASGBC: improving sequence labeling performance for joint learning of slot filling and intent detection;a comparative study of decision tree and naive bayes machine learning model for crime category prediction in Chicago;graph based analytics enhanced by deep learning;application of hidden Markov chain and artificial neural networks in music recognition and classification;a weight initialization method associated with samples for deep feedforward neural network;approximate optimal control of nonlinear systems with mismatched perturbations based on asymptotically stable critic neural network;comparing SVM and KNN algorithms for Myanmar news sentiment analysis system;an improved Lanczos algorithm for principal component analysis;and evaluation of dimensionality reduction techniques -principal feature analysis in case of text classification problems.

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A SYSTEMATIC REVIEW OF thE NEW PMI® PROJECT MANAGEMENT BEST PRACTICES GUIDE (PMBOK® 7th EDITION) AGAINST thE PREVIOUS ONE (PMBOK® 6th EDITION): USING INFORMETRIC ON thEIR ORGANIZATION AND CHAPTER STRUCTURE 16

A SYSTEMATIC REVIEW OF THE NEW PMI® PROJECT MANAGEMENT BEST...

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16th IADIS international conference on Information systems 2023, IS 2023

作者： Boyadjian, João Carlos Petrin, Nilo Sergio Maziero SENAC University Center Brazil

ISBN: (纸本)9789898704481

this article evaluates the change made by the PMI® - Project Management Institute, in its most recent guide of best practices and project management standards, a substantial change in the organization and structure of its content compared to the previous guide. A quantitative analysis was carried out on the volume of citations of terms related to five evaluation perspectives: 1) project management approaches;2) areas of knowledge;3) process groups;4) management principles;5) performance domains, between the two most recent publications of PMI® project management standards and best practices guides (the 6th and 7th editions of the PMBOK® guide). the result showed us that the predictive, adaptive and hybrid approach, with some variations in their individual percentages in each version of the guides, maintained, in general, a similar proportion between them, without significant changes. On the other hand, it is important to note the emphasis placed on team and stakeholder management in the latest edition of the PMBOK® Guide. © 2023 proceedings of the 16th IADIS international conference on Information systems 2023, IS 2023. All rights reserved.

关键词： Project management

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