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检索条件"任意字段=11th International Conference on Intelligent Data Engineering and Automated Learning"

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11th international Work-conference on Bioinformatics and Biomedical engineering, IWBBIO 2024

11th International Work-Conference on Bioinformatics and Bio...

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11th international Work-conference on Bioinformatics and Biomedical engineering, IWBBIO 2024

ISBN: (纸本)9783031646355

the proceedings contain 54 papers. the special focus in this conference is on Bioinformatics and Biomedical engineering. the topics include: GPACDA – circRNA-Disease Association Prediction with Generating Polynomials;Bioinformatics Analysis Provides Insight into the Identification of miRNAs as Transcriptional Regulators in Respiratory Syncytial Virus Infection;risk Factors of Recurrence and Metastasis of Breast Cancer Sub-types Based on Magnetic Resonance Imaging Techniques;Analysis of a Parallel and Distributed BPSO Algorithm for EEG Classification: Impact on Energy, Time and Accuracy;Naïve Bayes for Health-Status Predictive Monitoring in COVID-19: Leveraging Drugs and Diagnoses;speech Analysis for Autism Spectrum Disorder Detection for Children;SiMHOMer: Siamese Models for Health Ontologies Merging and Validation through Large Language Models;lossless Compression of Nanopore Sequencing Raw Signals;medical Equipment Real-Time Locating System in Hospitals Based on Bluetooth Low Energy;Validation of WHO Charts Mobile Applications for Body Length and Weight Assessment in Healthy Newborns;Predicting Atherosclerotic Plaque Onset and Growth in Carotid Arteries: A CFD-Driven Approach;hemispherical Directional Reflectance as a Screening Tool to Distinguish Effervescent Tablets with Acetylsalicylic Acid and Vitamin C Stored Under Stress Conditions from those Stored in Ambient Conditions;enhanced Ergonomics in Laryngoscopic Surgery. Exploring Innovative Solutions;maximal Deadlift Strength and Bone Mass in a Group of Healthy Elderly Men;multilayer Networks: A Survey on Models, Analysis of Algorithms and database;bone Mineral Density in Middle-Aged Former Sprinters and Middle-Aged Active Men;spectrum Filtering to Extract Pulse Rate Variability from Signals Recorded by Wearable Devices;machine learning Model for Anxiety Disorder Diagnosis Based on Sensory Time-Series data;analysis of the Relationship Between Electrodermal Activity and Blood Glucose Level in Diabetics.

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intelligent Code Review Assignment for Large Scale Open Source Software Stacks 7

Intelligent Code Review Assignment for Large Scale Open Sour...

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37th IEEE/ACM international conference on automated Software engineering (ASE)

作者： Aryendu, Ishan Wang, Ying Elkourdi, Farah AlOmar, Eman Stevens Inst Technol Hoboken NJ 07030 USA

ISBN: (纸本)9781450394758

In the process of developing software, code review is crucial. By identifying problems before they arise in production, it enhances the quality of the code. Finding the best reviewer for a code change, however, is extremely challenging especially in large scale, especially open source software stacks with cross functioning designs and collaborations among multiple developers and teams. Additionally, a review by someone who lacks knowledge and understanding of the code can result in high resource consumption and technical errors. the reviewers who have the specialty in both functioning (domain knowledge) and non-functioning areas of a commit are considered as the most qualified reviewer to look over any changes to the code. Quality attributes serve as the connection among the user requirements, delivered function description, software architecture and implementation through put the entire software stack cycle. In this study, we target on auto reviewer assignment in large scale software stacks and aim to build a self-learning, and self-correct platform for intelligently matching between a commit based on its quality attributes and the skills sets of reviewers. To achieve this, quality attributes are classified and abstracted from the commit messages and based on which, the commits are assigned to the reviewers with the capability in reviewing the target commits. We first designed machine learning schemes for abstracting quality attributes based on historical data from the OpenStack repository. Two models are built and trained for automating the classification of the commits based on their quality attributes using the manual labeling of commits and multi-class classifiers. We then positioned the reviewers based on their historical data and the quality attributes characteristics. Finally we selected the recommended reviewer based on the distance between a commit and candidate reviewers. In this paper, we demonstrate how the models can choose the best quality attributes

关键词： Large-scale Open-source Code Review Commit Classification Machine learning MPNet

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Road Surface Friction Estimation for Winter Conditions Utilising General Visual Features 27

Road Surface Friction Estimation for Winter Conditions Utili...

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27th IEEE international conference on intelligent Transportation Systems, ITSC 2024

作者： Ojala, Risto Alamikkotervo, Eerik Aalto University Department of Mechanical Engineering Aalto00076 Finland

ISBN: (纸本)9798331505929

In below freezing winter conditions, road surface friction can greatly vary based on the mixture of snow, ice, and water on the road. Friction between the road and vehicle tyres is a critical parameter defining vehicle dynamics, and therefore road surface friction information is essential to acquire for several intelligent transportation applications, such as safe control of automated vehicles or alerting drivers of slippery road conditions. this paper explores computer vision-based evaluation of road surface friction from roadside cameras. Previous studies have extensively investigated the application of convolutional neural networks for the task of evaluating the road surface condition from images. Here, we propose a hybrid deep learning architecture, WCamNet, consisting of a pretrained visual transformer model and convolutional blocks. the motivation of the architecture is to combine general visual features provided by the transformer model, as well as fine-tuned feature extraction properties of the convolutional blocks. To benchmark the approach, an extensive dataset was gathered from national Finnish road infrastructure network of roadside cameras and optical road surface friction sensors. Acquired results highlight that the proposed WCamNet outperforms previous approaches in the task of predicting the road surface friction from the roadside camera images. © 2024 IEEE.

关键词： Convolutional neural networks

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Design and Development of 'Virtual AI Teacher' System Based on NLP 11

Design and Development of 'Virtual AI Teacher' System Based ...

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11th international conference on Information and Education Technology, ICIET 2023

作者： Zhang, Yi Zhao, Shuying Tian, Xiangzhang Sun, Hao Northeastern University College of Information Science and Engineering Shenyang China Jiangxi Fufang Technology Co. Ltd Shenyang China

ISBN: (纸本)9781665465489

As one of the main research directions of artificial intelligence (AI), natural language processing (NLP) contributes to the development of the education industry in the fields of educational application development, teaching text processing, and teaching question and answer. Based on the machine reading comprehension (MRC) technology in NLP, this research has designed and developed a knowledge question-answering system for teaching material content, and combined the 'Pagebook' knowledge index function, teaching content voice interaction mode, etc., to form a 'virtual AI teacher' to assist students in learning. this study mainly introduces MRC model building and training, AIQA data set building, 'Pagebook' and voice interaction interface development. the main application object of this study is primary and secondary school students. It is applied to the in-class and out-of-class scenes of AI popularization education. the system scheme of 'virtual AI teacher' also supports the customization and expansion of teaching in other subjects. © 2023 IEEE.

关键词： Natural language processing systems

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Research on intelligent Vulnerability Identification Method for Power Information System 11

Research on Intelligent Vulnerability Identification Method ...

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11th Joint international Information Technology and Artificial Intelligence conference, ITAIC 2023

作者： Sheng, Liu Ze, Yuan Yang, Lin Yongxin, Fan Dandan, Li Xinyue, Shi Yilei, Song Zhanquan, Yun Electric Power Research Institute of State Grid Heilongjiang Electric Power Co. Ltd. Harbin China

ISBN: (纸本)9798350333664

With the rapid development of informatization in power systems, the network security threats are increasing day by day. Manual penetration testing is inefficient, while vulnerability scanning tools lack targeting. therefore, an intelligent, automatic method is urgently needed to identify vulnerabilities. In this paper, an intelligent vulnerability identification method for power information system is proposed. Aiming at the characteristics of power systems, this paper constructs a dedicated vulnerability knowledge database. An end-to-end solution is proposed, extracting features from heterogeneous vulnerability data and modeling them via convolutional and recurrent neural networks to classify Web, system, protocol and firmware vulnerabilities. Experiments show this intelligent solution greatly improves efficiency over manual penetration by promptly discovering vulnerabilities, boosting security of power information system. © 2023 IEEE.

关键词： electric power information system machine learning network security vulnerability identification

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Towards an intelligent Triage Bracelet: A Conceptual Study of a Semi-automated Prehospital Triage Algorithm and the Integration of Blood Pressure Measurement

Towards an Intelligent Triage Bracelet: A Conceptual Study o...

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16th international Joint conference on Biomedical engineering Systems and Technologies, BIOSTEC 2023

作者： Grünerbel, Lorenz Heinrich, Ferdinand Zett, Oliver Axelsson, Kristjan Schumann, Maximilian Fraunhofer EMFT Hansastr. 27d Munich Germany

First responders often reach their limit when they have to find and triage dozens of victims in a mass-casualty incident. However, a delay in treatment directly affects the survival chances of seriously injured people. A method to reduce the time for the prehospital triage could potentially save lives. Hence, this work outlines the conceptual development of an intelligent bracelet that semi-automates the prehospital triage. this bracelet is supposed to enable non-professional first responders to help with the triage, which maximises the utilisation of man power at a mass-casualty incident. the bracelet should automate the part of the triage that is based on vital, position and movement data and it should guide through the necessary patient interactions. As a step towards this goal, this work proposes a semi-automated triage algorithm that is based on mSTaRT. One of the challenges to implement this concept is to measure the blood pressure with a small and easy to attach system. therefore, this work presents a wrist worn oscillometric blood pressure measurement prototype. Furthermore, we discuss the use of machine learning methods to forecast triage level changes. © 2023 by SCITEPRESS – Science and Technology Publications, Lda.

关键词： Machine learning

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Adaptive Path Tracking Control for Autonomous Vehicles with Input Constraints and Actuator Faults 11

Adaptive Path Tracking Control for Autonomous Vehicles with ...

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11th IEEE data Driven Control and learning Systems conference, DDCLS 2022

作者： Li, Hongbo Li, Xuefang School of Intelligent Systems Engineering Sun Yat-Sen University Guangzhou510275 China

ISBN: (数字)9781665496759

ISBN: (纸本)9781665496759

In this work, an adaptive path tracking control approach for autonomous vehicle systems is proposed in presence of dynamical uncertainties, input saturation, and actuator failures. the unknown system characteristics are described as a coefficient matrix, which is estimated by utilizing an iterative learning algorithm. Furthermore, a fault-tolerant learning scheme is developed to deal with potential actuator failures caused by the vehicle loss or accidents. In addition, a saturation compensator is used to mitigate the negative effects of the actuator saturation. the adaptive path tracking controller is then designed by adopting the adaptive backstepping approach. the convergence of the proposed control method is analyzed by applying the composite energy function methodology, and its efficacy is demonstrated by using numerical simulation. © 2022 IEEE.

关键词： Autonomous vehicles

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11th international Work-conference on Bioinformatics and Biomedical engineering, IWBBIO 2024

11th International Work-Conference on Bioinformatics and Bio...

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11th international Work-conference on Bioinformatics and Biomedical engineering, IWBBIO 2024

ISBN: (纸本)9783031646287

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Survey on Improving Spacecraft Autonomy Based on Real-Time database 11th

Survey on Improving Spacecraft Autonomy Based on Real-Time D...

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11th international conference on Signal and Information Processing, Network and Computers, ICSINC 2023

作者： Ji, Huifang Liu, Bo Xu, Jian Zhou, Yukui Zhang, Xiaorui Beijing Institute of Control Engineering Beijing100090 China

ISBN: (纸本)9789819721191

Real-time database technology is increasingly being used in space missions abroad. It allows space agencies to process and analyze data in real time, increasing their autonomy and responsiveness. the technology has been applied to perception enhancement, natural disaster monitoring and prediction, traffic congestion prediction, energy consumption monitoring, crop growth monitoring and navigation. It is used to improve the autonomous control capability of spacecraft operation control modes, reduce labor costs, and improve the characteristics of deep space exploration missions. the use of real-time database technology has also been validated in intelligent decision systems for generating effective satellite flight mission plans. Current limited communication links to Earth still pose challenges for the teleoperation of Mars missions, limiting the potential scientific payoffs. Real-time database technology can bring application value in improving spacecraft autonomy. © the Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2024.

关键词： Traffic congestion

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Finding critical edges in networks through deep reinforcement learning 11

Finding critical edges in networks through deep reinforcemen...

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2023 IEEE 11th international conference on Information, Communication and Networks, ICICN 2023

作者： Wang, Xuecheng Zeng, Chen Han, Lu Zeng, Xi Wang, Junxia Luo, Wei Jiang, Bei Peng, Jiajie Research & Development Institution of Northwestern Polytechnical University in Shenzhen Xi'an China Northwestern Polytechnical University School of Computer Science Xi'an71007 China China Ship Development and Design Center Wuhan China Shanghai Jiao Tong University School of Naval Architecture Ocean & Civial Engineering Wuhan China Tianjin Second People's Hospital Tianjin China

ISBN: (纸本)9798350314014

the network is a powerful tool to study the interaction of system units, and the edge is an important part of the network as it represents relationships between nodes. Critical edges play an irreplaceable role in information transmission between nodes and maintaining network connectivity and integrity. therefore, the identification of critical edges in networks is an indispensable part of network analysis, which has great practical significance. Here, we propose an algorithm IKEoN. Based on the Deep Q-learning algorithm, this algorithm identify the critical edges in the network. Instead of using labeled data sets, IKEoN uses the constant interaction between agents and the environment to train the model, which reduces the influence of network noise and improves the recognition performance. the experimental results show that the proposed method outperforms the existing methods. © 2023 IEEE.

关键词： Reinforcement learning

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