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检索条件"任意字段=International Conference on Pattern Analysis and Intelligence Robotics"

共 15865 条记录，以下是251-260 订阅

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GCN-LSTM: A Graph-Based Deep Learning Method for Metagenomic Virus Classification 4

GCN-LSTM: A Graph-Based Deep Learning Method for Metagenomic...

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4th international conference on Computer, Control and robotics (ICCCR)

作者： Zhou, Yiding Deng, Li Xiao, Lei Jin, Lu Shanghai Univ Sch Mech Engn & Automat Shanghai Peoples R China

ISBN: (纸本)9798350373141;9798350373158

Viruses, as the most common organisms in the natural world, have significant impacts on both the environment and human society. Metagenomic sequencing of the virome can provide comprehensive information about viral sequences within microbial communities. Therefore, it is crucial to classify viral and host sequences from metagenomic data. Currently, the analysis of viral sequences heavily relies on one-hot encoded text data, which poses challenges due to its large volume and difficulty in extracting deep features. In this study, we propose a graph-based deep learning approach called GCN-LSTM for the classification of viral sequences in metagenomic data. GCN-LSTM utilizes a graph encoding technique to represent viral and host sequences, and employs graph convolution to extract features. Furthermore, it employs an LSTM neural network with self-attention mechanism to achieve the classification of viral and host sequences. Experimental results demonstrate that the performance of the proposed model improves with increasing sequence length, and outperforms the commonly used DeepVirFinder method.

关键词： metagenomics virus deep learning LSTM gapped pattern graph

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Measurement of Self-regulated Learning: Strategies for Mapping Trace Data to Learning Processes and Downstream analysis Implications 24

Measurement of Self-regulated Learning: Strategies for Mappi...

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14th Annual international conference on Learning Analytics and Knowledge (LAK) - Learning Analytics in the Age of Artificial intelligence

作者： Osakwe, Ikenna Chen, Guanliang Fan, Yizhou Rakovic, Mladen Singh, Shaveen Molenaar, Inge Gasevic, Dragan Monash Univ Clayton Vic Australia Peking Univ Beijing Peoples R China Radboud Univ Nijmegen Nijmegen Netherlands

ISBN: (纸本)9798400716188

Trace data provides opportunities to study self-regulated learning (SRL) processes as they unfold. However, raw trace data must be translated into meaningful SRL constructs to enable analysis. This typically involves developing a pattern dictionary that maps trace sequences to SRL processes, and a trace parser to implement the mappings. While much attention focuses on the pattern dictionary, trace parsing methodology remains under-investigated. This study explores how trace parsers affect extracted processes and downstream analysis. Four methods were compared: Disconnected, Connected, Lookahead, and Synonym Matching. Statistical analysis of medians and process mining networks showed parsing choices significantly impacted SRL process identification and sequencing. Disconnected parsing isolated metacognitive processes while Connected approaches showed greater connectivity between meta-cognitive and cognitive events. Furthermore, Connected methods provided process maps more aligned with cyclical theoretical models of SRL. The results demonstrate trace parser design critically affects the validity of extracted SRL processes, with implications for SRL measurement in learning analytics.

关键词： learning analytics learning strategies self-regulated learning

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analysis of New Distribution Network Planning Using Artificial intelligence Semantic Recognition 2

Analysis of New Distribution Network Planning Using Artifici...

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2nd international conference on Innovations and Development of Information Technologies and robotics, IDITR 2023

作者： Liao, He Yang, Jing Li, Hao Tuo, Jianjun Ma, Yarong Feng, Yuxin Fei, Changshun State Grid Gansu Electric Power Company Enterprise Development Department Lanzhou China Accenture Information and Technology Center Co Development Department Beijing SGITG Ltd. Beijing China

ISBN: (纸本)9798350345575

Use artificial intelligence semantic extraction and knowledge calculation to create professional knowledge base, covering professional field standards, key indicators, and evaluation experience, and form a knowledge map and store it in the graph database, and the formed professional key knowledge base can be used as a standard library and algorithm library for professional applications. This paper extracts knowledge from the feasibility study documents in the power grid field to form a knowledge base of key points for grid feasibility study review: Use artificial intelligence OCR recognition technology to structure useful information from feasibility study documents, use artificial intelligence NLP components to extract knowledge from information, and use artificial intelligence knowledge graphs to store knowledge. © 2023 IEEE.

关键词： Semantics

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Raspberry Pi-powered door lock with facial recognition

Raspberry Pi-powered door lock with facial recognition

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2024 IEEE international Students' conference on Electrical, Electronics and Computer Science, SCEECS 2024

作者： Jha, Anjali Bulbule, Rajesh Nagrale, Nilesh Belambe, Tanavi Dit E&tc Dept. Pune India

ISBN: (纸本)9798350348460

Facial recognition is a widely-used process that aims to detect and verify an individual's identity. This technique is employed in various applications, such as image and video analysis, surveillance, and security systems. OpenCV is a computer vision technique that enables users to comprehend the storage, modification and feature extraction of images and videos. The advancement of artificial intelligence is heavily reliant on computer vision techniques, particularly in self-driving cars, robotics, and image-editing software. The OpenCV Library is a valuable tool for processing and displaying camera images. This research utilizes the Haar Cascade Classifier, a machine learning-based algorithm, to process a user's face image and detect faces accurately. © 2024 IEEE.

关键词： computer vision Facial recognition Haar Cascade Classifier image processing machine learning OpenCV robotics security systems self-driving cars

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Theoretical principles and simulation analysis of an intelligent corrosion sensor based on fiber Bragg grating 11

Theoretical principles and simulation analysis of an intelli...

引用

11th IEEE international conference on Cybernetics and Intelligent Systems (CIS) / 11th IEEE international conference on robotics, Automation and Mechatronics (RAM)

作者： Gong, Yongjian Guo, Yongxing Xiong, Li Wuhan Univ Sci & Technol Key Lab Met Equipment & Control Technol Minist Educ Wuhan Peoples R China Wuhan Univ Sci & Technol Hubei Key Lab Mech Transmiss & Mfg Engn Wuhan Peoples R China

ISBN: (纸本)9798350364200;9798350364194

Corrosion of reinforcing bars is a major factor affecting the durability of reinforced concrete structures. The volume of corroded reinforcement expands and the protective layer gradually cracks, which in turn reduces the serviceability of the structure. In this study, a fibre optic intelligent corrosion monitoring device based on magnetic sensing is investigated. A new type of magnetic probe is designed for sensing the corrosion of steel reinforcement, and strain sensing is carried out by utilizing high elasticity diaphragm and fibre optic grating structure. A finite element method is utilized to simulate the sensitivity and linearity of the device under different magnetic forces. The experimental results show that the sensor has good mechanical response effect and the fibre optic diaphragm stress sensing structure has good linearity, which can achieve longterm high-precision non-destructive monitoring of rebar corrosion.

关键词： Reinforcement corrosion FBG Sensor Monitoring

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Exploring educational transformation and innovation pathways in the era of artificial intelligence 24

Exploring educational transformation and innovation pathways...

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2024 international conference on Artificial intelligence and Future Education, AIFE 2024

作者： Sun, Weiwei Qin, Minwu Yin, Zhenyao Guangzhou Institute of Science and Technology Guangzhou Guangdong China Guangdong Baiyun University Guangzhou Guangdong China

ISBN: (纸本)9798400710650

This study analyzes the profound impact of artificial intelligence (AI) on education, exploring the applications of educational reform theory, technological innovation theory, and the theory of equal educational opportunities in the context of AI-driven educational transformation. The rapid advancement of AI technologies-particularly deep learning, intelligent image recognition, big data, and educational robotics-is driving education from traditional models toward personalization, lifelong learning, and intelligent approaches. Technological innovation not only revamps teaching tools and resources but also enables differentiated instruction through intelligent data analysis, promoting educational equity and enhancing students' self-learning abilities. AI demonstrates immense potential in supporting lifelong learning, optimizing educational processes, and enriching the educational ecosystem;however, it also raises ethical challenges, including privacy concerns and risks of educational alienation. Consequently, educators should focus on the responsible application of AI technologies, leveraging the intrinsic strengths of education, to improve teaching quality and foster harmonious development between humans and machines. © 2024 Copyright held by the owner/author(s).

关键词： Adversarial machine learning

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A Bibliometric analysis of Sleep pattern Prediction of Breast Cancer Survivors Using VOSviewer 1

A Bibliometric Analysis of Sleep Pattern Prediction of Breas...

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1st international conference on Computational intelligence, Communication Technology and Networking, CICTN 2023

作者： Singh, Swati Sharma, Sonal Uttaranchal School of Computing Sciences Dehradun India

ISBN: (纸本)9798350338027

Breast cancer and its treatment have aroused great concern over the past decade due to the growing number of incidences reported in women worldwide. 12%- 95% of breast cancer patients were found to have disturbed sleep patterns. Statistics showed a significant increase over the period in reporting of sleep disorders by breast cancer patients. The purpose of this study is to determine the scope of research of sleep pattern prediction of breast cancer survivors. Total 2,992 publications from Scopus database were taken for bibliometric analysis. This study retrieved the information of subject keywords, countries, journals, organizations, and authors working majorly in this field. Findings suggested that USA holds a dominant position in sleep research in breast cancer patients. As per our research this is the first bibliometric study conducted using Scopus database to do bibliometric analysis of sleep pattern of breast cancer survivors in India with the help of VosViewer (version 1.6.18). © 2023 IEEE.

关键词： Sleep research

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Verification Method of Intelligent Prosthetic Algorithm Based on Anthropomorphic Walking Robot 3

Verification Method of Intelligent Prosthetic Algorithm Base...

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3rd international conference on robotics, Automation and Artificial intelligence (RAAI)

作者： An, Honglei Sun, Lei Ma, Hongxu Wei, Qing Natl Univ Def Technol Coll Intelligence Sci & Technol Changsha Peoples R China

ISBN: (纸本)9798350307573;9798350307566

A key issue in the research of intelligent prosthetics is the verification and analysis of the proposed prosthetic motion planning and control methods. In this paper, it is proposed that using a humanoid walking robot as the subject can effectively test the interaction dynamics between the prosthesis and the human body. This method also avoids the risk of injury to amputee patients when participating in the test before the control method is mature. Specifically, the anthropomorphic walking of bipedal walking robots is first realized, and a testbed that fully simulates the straight leg walking is obtained. The right leg (below the thigh) of the bipedal robot is then replaced with an intelligent prosthesis. When testing the planning and control methods of intelligent prosthetics, prosthetic controllers run independently. The bipedal walking robot, except for the part below the right thigh, normally performs the "humanoid motion controller". Effective intelligent prosthetic control methods will make the prosthesis-"human" coupling system produce smooth walking movements, while ineffective intelligent prosthetic control will cause the coupling system to fall due to strong interference.

关键词： verification intelligent prosthesis anthropomorphic walking virtual constraint

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Temporal Alignment of Multi-Dimensional Asynchronous Data for Digital Twin Evolutionary analysis 6

Temporal Alignment of Multi-Dimensional Asynchronous Data fo...

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6th international conference on robotics, Intelligent Control and Artificial intelligence, RICAI 2024

作者： Fang, Chenglong Sun, Jinlong Liu, Gaohe Zhang, Jiaji Gui, Shuqiang Wang, Qiankun School of Communications and Information Engineering Nanjing University of Posts and Telecommunications Nanjing China State Grid Dingxi Power Supply Company Nanjing China School of Civil Engineering and Architecture Wuhan University of Technology Wuhan China MCC Wukan Engineering Technology Co. Ltd Wuhan China

ISBN: (纸本)9798331541699

Digital twin technology is widely used in smart industries and other fields. However, analyzing its evolution in complex scenarios faces challenges in collecting and merging data, particularly in achieving precise data time alignment. Existing methods often struggle with diverse data types and frequencies. This paper introduces a new method for aligning multi-dimensional asynchronous data in digital twin evolution analysis. This approach ensures time alignment and frequency consistency through techniques such as filling null values, intelligent interpolation, and resampling. Key contributions include BiLSTM-based interpolation and flexible adjustment of data granularity. These advancements effectively address the challenge of data time alignment in digital twin evolution analysis, thereby improving data quality and alignment accuracy. The proposed method supports reliable data processing for tasks such as anomaly detection, accelerated evolution, and decision-making. Experimental results demonstrate its capability to recover data with severely damaged features, thereby advancing digital twin evolution analysis in complex scenarios. © 2024 IEEE.

关键词： Spatio-temporal data

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Design and motion performance analysis of a soft-bodied robot with dual motion modes 3

Design and motion performance analysis of a soft-bodied robo...

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3rd international conference on Control and Intelligent robotics, ICCIR 2023

作者： Li, Jiabao Qi, Yangjie Wang, Chengjun School of Artificial Intelligence Anhui University of Science and Technology Huainan232001 China School of Mechanical Engineering Anhui University of Science and Technology Huainan232001 China

ISBN: (纸本)9781510671867

In this study, a soft robot with dual movement modes was designed to address the problem of pneumatic soft robots having a "tail," limited movement, and a single movement mode. Inspired by the movement pattern of the catapult and the crawling gait of the tortoise, the design of the soft robot with dual movement modes was completed, including the crawling mechanism, jumping mechanism, and overall mechanism. For the crawling mechanism, a mathematical model of the deformation of the crawling drive was established using the Yeoh model and the principle of virtual work, and the factors affecting the deformation of the crawling drive were analyzed. The deformation of the crawling drive was simulated and analyzed using ABAQUS, and the relationship between air pressure, size of the drive, and deformation of the drive was investigated. For the jumping mechanism, the energy storage mechanism was analyzed in terms of energy storage and drive air pressure, and ADAMS was used to explore the jumping performance of the soft robot under different energy storage conditions for simulation analysis. The results revealed that the proposed design allows the robot to crawl and jump at the same time and removes the "tail" of the pneumatic soft robot, thereby improving its range of motion. © 2023 SPIE.

关键词： Energy storage

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