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共 15864 条记录，以下是371-380 订阅

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Dielectric Resonator-based MIMO Antenna with pattern Diversity for 5G Millimeter-wave Application 5

Dielectric Resonator-based MIMO Antenna with Pattern Diversi...

引用

5th international conference on Smart Sensors and Application, ICSSA 2024

作者： Sahu, Jayant Kumar Gupta, Anshul Department of Electronics and Communication Engineering National Institute of Technology Raipur India

ISBN: (纸本)9798350354294

This study presents a quad-port, box-shaped multiple-input-multiple-output cylindrical dielectric resonator antenna (CDRA) that exhibits quad-directional pattern diversity for new radio frequency bands named n260 under the 5G millimeter-wave communication. The antenna operates between 36.30 GHz to 40.60 GHz frequency range. The primary structure consists of a CDRA excited with the help of a rectangular aperture and a modified microstrip feed line. This structure is replicated and arranged in a box configuration, resulting in a quad-port MIMO antenna system. The DRA elements are placed so that their adjacent broad-side radiation patterns are 90 degrees apart from each other in an azimuthal direction, providing a spatially decoupled radiation pattern and resulting in enhanced isolation. The proposed MIMO antenna achieves over 30 dB of isolation between antenna ports without additional decoupling structures. This structure is suitable for 5G new radio frequency bands n260 under millimeter-wave communication, forthcoming communication and IoT applications. © 2024 IEEE.

关键词： Millimeter waves

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Monte Carlo Tree Search Algorithms for Strategic Planning in Humanoid robotics 1

Monte Carlo Tree Search Algorithms for Strategic Planning in...

引用

1st IEEE international conference on Cognitive robotics and Intelligent Systems, ICC - ROBINS 2024

作者： Gundla, Praveen Gummadi, Annapurna Changala, Ravindra Vuyyuru, VeeraAnkalu Hemantha Kumar, A. Kiranbala, B. Nri Institute of Technology Andhra Pradesh Guntur India Hyderabad India Guru Nanak Institutions Technical Campus Department of Information Technology Hyderabad India KoneruLakshmaiah Education Foundation Department of Computer Science and Engineering A.P Vaddeswaram522502 India MED Annamacharya Institute of Technology and Sciences AP Rajampet India K.Ramakrishnan College of Engineering Department of Artificial Intelligence and Data Science Trichy India

ISBN: (纸本)9798350372748

With the increasing complexity and versatility of humanoid robots, there is a growing imperative for efficient and adaptable planning methodologies. This evolution marks a crucial step towards enhancing the overall capabilities and practicality of humanoid robotic systems. This research delves into the application of Monte Carlo Tree Search (MCTS) algorithms for enhancing strategic planning in the context of humanoid robotics. The study explores the integration of MCTS into humanoid robotics to enable effective decision-making processes that account for uncertainties, sensor noise, and real-time adaptability. By simulating future scenarios and evaluating potential actions through iterative sampling, MCTS facilitates the creation of robust and context-aware strategies. The research considers various aspects of strategic planning, including path finding, task allocation, and goal achievement. This investigation contributes to the burgeoning field of robotics by providing a comprehensive analysis of the benefits and challenges associated with implementing MCTS in humanoid robotic systems. The proposed MCTSA model shows better efficiency in Resource Allocation 88%, SuccessRate (Navigation) 85%, Average Planning Time 2.5 seconds and Success Rate (Object Manipulation) 92% which is higher when compared to the existing methods. The findings aim to inform the development of intelligent and autonomous robots capable of making strategic decisions in dynamic and uncertain environments, thereby advancing the capabilities of humanoid robotics in various practical applications. © 2024 IEEE.

关键词： Decision making

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Research on Unsupervised Fault Diagnosis based on Sparse Autoencoder and Locally Linear Embedding 2

Research on Unsupervised Fault Diagnosis based on Sparse Aut...

引用

2nd international conference on robotics, Artificial intelligence and Intelligent Control, RAIIC 2023

作者： Li, Yichen Liu, Guangye Zeng, Wei Jiang, Lei China Tobacco Hubei Industrial Co. Ltd. Hubei Xinye Reconstituted Tobacco Development Co. Ltd. Wuhan China Huazhong University of Science and Technology School of Artificial Intelligence and Automation Wuhan China

ISBN: (纸本)9798350328004

In this paper, we address the shortcomings of traditional unsupervised fault diagnosis methods in handling high-dimensional, nonlinear, and highly complex fault diagnosis problems, and propose an unsupervised fault diagnosis method based on sparse autoencoder and local linear embedding. This method combines the characteristics of sparse autoencoder and manifold learning methods to reduce dimensionality and extract features from high-dimensional data while preserving the local linear relationships within the data. The proposed model was experimentally validated on a three-phase flow equipment dataset, demonstrating the effectiveness of the model. © 2023 IEEE.

关键词： Failure analysis

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analysis of Duplicating the Human Mind Suspicions in AI in Various Divisions

Analysis of Duplicating the Human Mind Suspicions in AI in V...

引用

2025 international conference on Multi-Agent Systems for Collaborative intelligence, ICMSCI 2025

作者： Santhoshkumar, S.P. Karthika, R. Vijayakumar, N. Gajalakshmi, S. Jayanthi, K. Hariharasudhan, S. School of Computing Vel Tech Rangarajan Dr. Sagunthala R&d Institute of Science and Technology Department of Computer Science and Engineering Avadi Chennai India School of Computing Department of Information Technology Rathinam Technical Campus Coimbatore India Pollachi Institute of Engineering and Technology Pollachi Coimbatore India

ISBN: (纸本)9798331509828

Uncertainty in AI refers to the degree of confidence or probability associated with the accuracy or effectiveness of an AI system's output. It is a measure of how much the AI system is unsure about the correctness of its output or decision-making. Uncertainty can arise in AI systems due to a variety of factors, including the quality of input data, variations in data formats, variations in context or environment, and the complexity of the underlying algorithms. Different AI applications can have specific types of uncertainty associated with them, as we discussed in previous questions about uncertainty in AI image recognition, natural language processing, data extraction, expert systems, planning and optimization, and robotics. To mitigate uncertainty in AI systems, researchers and developers use various methods, such as incorporating more data and diverse inputs, improving the quality of input data, enhancing the algorithms, and using feedback mechanisms to learn from errors and improve the system over time. However, complete elimination of uncertainty is often challenging or impossible, and users should always be aware of the potential for errors or unexpected behaviour in AI systems. In this paper, analysis of artificial intelligence uncertainty in various fields. © 2025 IEEE.

关键词： Expert systems

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Research on Time Series Data Prediction Based on STP-GAN Algorithm 5

Research on Time Series Data Prediction Based on STP-GAN Alg...

引用

5th international conference on robotics, Intelligent Control and Artificial intelligence, RICAI 2023

作者： Zhang, Rui Mariano, Vladimir Y. College of Computing and Information Technologies National University Manila Philippines School of Big Data and Artificial Intelligence AnHui XinHua University Hefei China

ISBN: (纸本)9798350357950

In this paper, we utilize the Sentiment analysis technique in NLP field to provide the opinion influence factors for the algorithmic model by performing sentiment analysis on the text of the research report, introduce the GAN algorithm which is more compatible with the logic of the temporal data operation, and on the basis of which we add the Text Pathway, and put forward the text-assisted Generative Adversarial Network Prediction Model, STP-GAN. The model combines temporal data prediction with sentiment analysis to reduce the error of model training, and introduces the Transformer structure to improve the learning ability of temporal data features. In addition, STP-GAN utilizes BERT for fine-tuning and incorporates a lexicon to increase model adaptability. And on the basis of the proposed STP-GAN, the optimizer RMSPropW, which is more suitable for this research, is proposed, which uses the exponentially weighted moving average as the decay coefficient and utilizes weight decay to improve the training stability and training speed of the prediction model. © 2023 IEEE.

关键词： BERT generative adversarial model optimizer sentiment propensity analysis temporal data

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Design and analysis of Flexible Joints for Robots Based on Module Cells 5

Design and Analysis of Flexible Joints for Robots Based on M...

引用

5th international conference on robotics, Intelligent Control and Artificial intelligence, RICAI 2023

作者： Ma, Xiangyu Liang, Shuang Li, Yang Cui, Tingqiong Luo, Tianhong School of Intelligent Manufacturing Engineering Chongqing University of Arts and Sciences Chongqing China

ISBN: (纸本)9798350357950

In this paper, we propose a flexible robotic arm for robot structures. The robotic arm consists of an array of modular elements and is articulated by rods. Moreover, the module element is structured by double-layer hexagon, which is offsetted part of the distance from a hexagon. Furthermore, the working space and motion characteristics of the flexible robotic arm were analyzed. The analysis results show that the flexible manipulator based on the modular element has better flexibility and can realize different working spaces according to the different hinges of the modular units. It is worth noting that the design strategy based on the modular unit flexible manipulator expands the design ideas of the flexible robot mechanism, especially in the application fields with high requirements for robot flexibility, such as detection in narrow and long spaces and unstructured environments. © 2023 IEEE.

关键词： component Configuration analysis Flexible arm Modular cell Working space

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Formal Ontology in Information Systems - Proceedings of the 14th international conference, FOIS 2024

Formal Ontology in Information Systems - Proceedings of the ...

引用

14th international conference on Formal Ontology in Information Systems, FOIS 2024

ISBN: (纸本)9781643685618

The proceedings contain 19 papers. The topics discussed include: hanging around: cognitive inspired reasoning for reactive robotics;Core-O: a competence reference ontology for professional and learning ecosystems;OnNER: an ontology for semantic representation of named entities in scholarly publications;large language models and foundational ontologies;ontology as structure, domain and definition;interpreting texts and their characters;ontological analysis of money;ontological analysis of malfunctions: some formal considerations;unpacking the semantics of risk in climate change discourses;and towards semantic interoperability among heterogeneous cancer data models using a layered modular hyper-ontology.

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Identification of air compressor faults based on ViT and Mel spectrogram 2

Identification of air compressor faults based on ViT and Mel...

引用

2nd international conference on robotics, Artificial intelligence and Intelligent Control, RAIIC 2023

作者： Guo, Depeng Ge, Weili Li, Boyuan Gao, Jinfeng Zhengzhou University School of Computer and Artificial Intelligence Zhengzhou China Zhengzhou Windbell Machinery Co. Ltd Zhengzhou China

ISBN: (纸本)9798350328004

Air compressors are used as a power source in many industries, but they are likely to malfunction during use. However, traditional methods such as fault analysis and judgment on the working sound of air compressors are inefficient and have not fully applied artificial intelligence related technologies in this field. Therefore, we propose a machine working sound recognition method based on Vision Transformer(ViT), which extracts the features of the working sound of the air compressor and converts it into the Mel spectrogram, and use the method of image classification in deep learning to determine whether the air compressor is in a faulty state, thus avoiding more losses and improving work efficiency. The experimental results show that the deep learning method can determine the working status of the air compressor very well, and the ViT shows better classification performance than ResNet, VGG and other models. © 2023 IEEE.

关键词： Image enhancement

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Classification and Featurization of Motherboard Components Using YOLO Through Machine Learning

Classification and Featurization of Motherboard Components U...

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

作者： Rahman Fahim, Md. Imadur Mahazabin Senthia, Sabrina Ferdows, Rubayea Ahmed, Fuad IUBAT-International University of Business Agriculture and Technology Dept of Computer Science and Engineering Bangladesh Dept of Computer Science and Engineering Bangladesh

ISBN: (纸本)9798331529765

The role of technology is vital and can be observed through the 5th industrial revolution. As a matter of fact, the impact is so severe, it can be felt almost everywhere. As technology advances, one of the most promising frontiers lies in the realm of Artificial intelligence (AI), with machine learning at its forefront. Object detection is a crucial such part with applications in robotics and image analysis. This paper presents a comprehensive study on vision AI, focusing on the detection of motherboard components utilizing the YOLOv8 object detection framework. The results demonstrate the effectiveness and real time effectiveness of YOLOv8 in terms of motherboard object detection. Simultaneously, this work validates the feasibility of employing YOLOv8 for in-depth analysis and object detection on various circuit boards. This will allow many automated devices to repair circuit boards with the help of artificial intelligence. Consequently, allowing robots to detect flaws and repair integrated hardware components in situations considered difficult for humans. © 2024 IEEE.

关键词： Robot vision

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Research on ECO-HC Target Tracking Algorithm Based on Adaptive Template Update and Multi-Feature Fusion 6

Research on ECO-HC Target Tracking Algorithm Based on Adapti...

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6th international conference on robotics and Computer Vision, ICRCV 2024

作者： Zhao, Yongsheng Yang, Luyang Liu, Ting Gao, Yuxing School of Marine Electrical Engineering Dalian Maritime University Dalian China

ISBN: (纸本)9798331527426

Aiming at the problem that it is difficult to fully and effectively utilize features for complete representation of target information during target tracking in complex scenes, this paper proposes an ECO-HC target tracking algorithm based on adaptive template updating and multi-feature fusion. In terms of template updating, an adaptive template mechanism is introduced, which dynamically determines whether the target is occluded or deformed by fusing color correlation and hash correlation, thus adjusting the template updating strategy to avoid template contamination. In terms of feature extraction, average filtered local binary pattern (AVLBP) features are proposed and fused with HOG features to enhance the algorithm's ability to capture the detailed texture of the target. Experiments on the OTB-100 tracking datasets show that the accuracy and success rate of this paper's algorithm on the datasets are 86.7% and 79.7%, respectively, which are improved by 2.9% and 2.7%, respectively, compared to the baseline method. The effectiveness of the algorithm is verified through qualitative and quantitative analysis, which demonstrates that the adaptive template updating and multi-feature fusion strategies can significantly improve the robustness and accuracy of target tracking. © 2024 IEEE.

关键词： Local binary pattern

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