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Unsupervised Rail Surface Defect Detection Method 9

Unsupervised Rail Surface Defect Detection Method

引用

9th international conference on Intelligent Informatics and BioMedical Sciences, ICIIBMS 2024

作者： Zhao, ChenYu Han, Yi Ouyang, Ningkang Zhao, YiFan School of Artificial Intelligence Zhengzhou Software Vocational and Technical College Zhengzhou China Anyang Institute of Technology Engineering Department of Computer Science and Information Anyang China North China University of Water Resources and Electric Power School of Information Engineering Zhengzhou China

ISBN: (纸本)9798350363043

Railroad travel has become an essential part of modern life, therefore, rail surface defect detection has become a problem that cannot be ignored. However, most of the currently existing methods often require a large number of defect samples for learning, which are labor-intensive and very difficult to obtain. In order to alleviate the data dependence of the detection model, this paper proposes an unsupervised method. Specifically, we use Transformer's attention mechanism to construct the encoder-decoder structure and train it only on normal samples with the purpose of reconstruction, so that those regions that cannot be reconstructed will be regarded as defects at the time of detection. To prevent the model from generalizing its generalization ability to those unknown defective samples, i.e., to avoid overgeneralization, we introduce a noise perturbation in the training so that the model focuses on the reconstruction of normal features. Experiments show that the proposed unsupervised approach outperforms a host of supervised models with low data requirements and can effectively address the current challenges of track defect detection. © 2024 IEEE.

关键词： Unsupervised learning

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A Machine Learning Based predictive Model to Diagnose Heart Failure Patients using Imbalanced Classification Problem 4

A Machine Learning Based Predictive Model to Diagnose Heart ...

引用

4th international conference on Advancements in Computational Sciences, ICACS 2023

作者： Mudassar, Muhammad Afzal, Mehtab Muhammad, Tufail Univeristy of Lahore Department of Software Engineering Lahore Pakistan Air Univeristy Islamabad Aerospace and Aviation Campus Department of Computer Science Kamra Pakistan

ISBN: (纸本)9781665463775

Heart failure (HF) is now one of the most common diseases, causing approximately seventeen million death cases every year all over the world. HF occurs due to less pumping ratio of blood by the heart that a normal human being needs to survive. In this regard, research studies have been proposed to predict the causes behind the heart failure of a patient using the 'Heart failure clinical records (HFCR's) dataset. Although, much research has been performed on this dataset, however, there is a lack of construction of a more reliable predictive model that helps to predict HF patients with better prediction results. We aimed to apply imbalance learning to handle the imbalance dataset as a very few researchers applied it. We trained the models using six ensemble and three non-ensemble classifiers with the help of multiple experiments. In the end, we performed an evaluation measure to compare our prediction results with the previous research work. Our proposed model gives a significant increase in accuracy value as well as in precision, recall, and f1-score. © 2023 IEEE.

关键词： Forecasting

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Textual Approach for Designing Database Conceptual models: A Focus Group 9th

Textual Approach for Designing Database Conceptual Models: A...

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9th international conference on Model-Driven engineering and software Development (modelsWARD)

作者： Lopes, Jonnathan Bernardino, Maicon Basso, Fabio Rodrigues, Elder Fed Univ Pampa PPGES LESSE Av Tiaraju 810 BR-97546550 Alegrete RS Brazil

ISBN: (纸本)9789897584879

Different approaches to software development are based on at least three database models: conceptual, logical, and physical, requiring distinct abstraction levels to represent complementary concepts. the selection of a conceptual database modeling approach, among other things, depends on the problem domain, knowledge, and preferences of the developer. this paper presents a new domain-specific textual language devoted to the conceptual relational database modeling, i.e., entity-relationship modeling. Furthermore, we present a preliminary evaluation conducted to analyze our proposed DSL, comparing two grammar versions in a focus group research method.

关键词： Domain Specific Language Conceptual Data Model Conceptual Model Database Modeling

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Research on Intelligent System of English Communication Aid software Based on Speech Recognition 5

Research on Intelligent System of English Communication Aid ...

引用

5th international conference on Computers, Information Processing and Advanced Education, CIPAE 2024

作者： Yu, Wei Xi'an Eurasia University Shaanxi Xi'an China

ISBN: (纸本)9798331527662

this paper aims to explore an innovative English communication aid software intelligent system that utilizes advanced speech recognition technology to improve the accuracy and efficiency of non-native speakers in English communication. the research focuses on the integration of feature parameter extraction methods, speech recognition models and human-computer interaction systems, as well as their application in practical communication scenarios. First, this study proposes an efficient feature parameter extraction method, which extracts key sound features such as Mayer frequency cepstrum coefficient (MFCCs) and linear predictive coding (LPCs) through in-depth analysis of speech signals, which are critical for subsequent speech recognition. By optimizing the extraction process of these parameters, the system can maintain good recognition performance under different background noise. Second, the study employs an advanced speech recognition model that combines deep learning techniques, especially convolutional neural networks (CNNs) and recurrent neural networks (RNNs), to achieve accurate parsing of complex speech patterns. the model is trained with a large amount of spoken English data, and can effectively recognize English pronunciation with a variety of accents and speech speeds. In terms of human-computer interaction system, this research designs an intuitive and user-friendly interface that allows users to easily interact with the system. through real-time feedback and automatic error correction, the system can assist users to correct pronunciation errors in real time, thereby improving the quality of communication. the experimental results show that the proposed system achieves the expected target in terms of recognition accuracy and response speed, and provides a powerful auxiliary tool for English learners and international communicators. © 2024 IEEE.

关键词： Convolutional neural networks

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Comparative analysis of different finite element models of single box and multi-chamber special-shaped PC box girder 9

Comparative analysis of different finite element models of s...

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9th international conference on Electromechanical Control Technology and Transportation, ICECTT 2024

作者： Hao, Xuehai Liu, Shizhong Chen, Qiang Guonan, Yuan Xia, Jiawen Fu, Lukang Lanzhou Jiaotong University Lanzhou730070 China The Fourth Engineering Co. LTD. China Railway Seventh Bureau Group Wuhan430074 China

ISBN: (纸本)9781510682399

Using finite element software, using the single beam method and the beam lattice method, the finite element model of a large-width span special-shaped single-box multi-chamber PC cast-in-place box girder and the ANSYS three-dimensional solid refined finite element model are established, and the stress calculation results of the single beam model and the beam lattice model are compared with the stress results of the ANSYS solid model from the structural stress, firstly, the accuracy of the finite element calculation methods of the two rod systems is discussed, and then the three finite element models are used to analyze the transverse stress distribution law of each mid-span section under lane loadto explore the variation law of shear hysteresis coefficient under different width span ratios. the results show that compared with the ANSYS solid element calculation results, the calculation results of the beam lattice method are in good agreement with the ANSYS results. the single-beam method cannot reflect the real stress state of a single-box multi-chamber wide-body box girder, nor can it reflect its shear hysteresis effect. Under the action of lane load, comparing the shear hysteresis coefficient under different width-span ratios, it can be seen that the larger the width-span ratio, the more obvious the shear lag effect. For single-box multi-chamber wide bridges, the beam lattice method can directly give the axial force, shear force and bending moment required for design review compared with the ANSYS solid model, and has good calculation accuracy. In the extreme case, i.e., when the uplink line is fully loaded and the downline is unloaded, the maximum deviation rate between the shear hysteresis coefficient of the beam lattice model and the shear hysteresis coefficient of the single-beam model is 91.9%, and it can be concluded that for the wide bridge, the load calculation cannot be carried out by the single-girder model. the research methods and conclusions obtained

关键词： Box girder bridges

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Joint Post-proceedings of the 3rd and 4th international conference on Microservices, Microservices 2020 and 2022

Joint Post-Proceedings of the 3rd and 4th International Conf...

引用

3rd and 4th international conference on Microservices, Microservices 2020 and 2022

ISBN: (纸本)9783959773065

the proceedings contain 9 papers. the topics discussed include: microservice-aware static analysis: opportunities, gaps, and advancements;modular choreographies: bridging Alice and Bob notation to Java;ZVAX – a microservice reference architecture for nation-scale pandemic management;custom serverless function scheduling policies: an APP tutorial;model-driven code generation for microservices: service models;towards self-architecting autonomic microservices;correct-by-construction microservices with model-driven engineering: the case for architectural pattern conformance checking and pattern-conform code generation;and applying QoS in FaaS applications: a software product line approach.

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Edge Intelligence Hybrid Framework for Real-Time IoT Applications using Multi-Stage Adaptive Processing Methods 6

Edge Intelligence Hybrid Framework for Real-Time IoT Applica...

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

作者： Suneel, Sajja Yadav, Rakesh Kumar Nirmala Devi, K. Teja sree, B. Aarthi, R. Upadhyay, Shrikant Institute of Aeronautical Engineering Dundigal Telangana Hyderabad500043 India Amity School of Engineering and Technology Amity University Bihar Patna India Department of Computer Applications Madanapalle Institute of Technology & Science India Department of IT S.R.K.R Engineering College Bhimavaram India Department of ECE Rajalakshmi Institute of Technology Kuthambakkam Post Tamil Nadu Chembarambakkam600124 India Department of Electronics and Communication Engineering MLR Institute of Technology Hyderabad India

ISBN: (纸本)9798331522667

the rapid proliferation of IoT devices has created an unprecedented need for real-time data processing and decision-making. this paper proposes an Edge Intelligence Hybrid Framework designed for real-time IoT applications using multi-stage adaptive processing methods. the framework structured into three layers: edge-level processing, fog-level aggregation, and cloud-level computation, enabling efficient distribution of tasks across the hierarchy. At the edge, lightweight models and preprocessing techniques, such as Kalman Filtering and Huffman Coding, ensure low-latency and energy-efficient operation. Intermediate computations and model synchronization occur at the fog level, while high-complexity tasks like deep learning model training performed at the cloud level. Results demonstrate that edge-level processing achieves an accuracy of 85.4%, while fog and cloud levels improve accuracy to 89.4% and 94.9%, respectively. Latency at the edge is as low as 9–13ms, compared to fog (23–29ms) and cloud (117–125ms), ensuring suitability for time-critical IoT tasks. the proposed framework effectively balances latency, accuracy, and resource optimization, making it ideal for applications such as predictive maintenance, healthcare, and smart surveillance. © 2025 IEEE.

关键词： Kalman filters

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Evaluating the Performance of Deep Learning models in Predicting Brain Ischemic Stroke Risk using EEG Signals. 8

Evaluating the Performance of Deep Learning Models in Predic...

引用

8th international conference on Electronics, Communication and Aerospace Technology, ICECA 2024

作者： Shyamala, N. Marjorie, S.Roji Saveetha Institute of Medical and Technical Sciences Saveetha University Saveetha School of Engineering Department of Computer Science and Engineering TamilNadu Chennai India Srm Institute of Science and Technology Department of Electronics and Communication Engineering Kattankulathur TamilNadu Chennai India

Stroke is the third most common cause of fatalities worldwide. It9;s a hazardous condition that may cut off blood flow to the brain and result in death, serious illness, or disability. In order to begin treatment e... 详细信息

ISBN: (纸本)9798350367904

Stroke is the third most common cause of fatalities worldwide. It's a hazardous condition that may cut off blood flow to the brain and result in death, serious illness, or disability. In order to begin treatment early and reduce the death rate, an exact stroke prediction is essential. Electrical activity inside the brain is reflected in electroencephalography (EEG) data, which provide a non-invasive method of monitoring brain performing to detect abnormalities relating to stroke risk. the intention is to evaluate the way deep learning models predict the risk brain stroke using EEG signals. For training and validate the models, a large set of electroencephalogram (EEG) data from patients with different stroke risk levels was used Using neural network architectures, which include recurrent and convolutional neural networks (RNNs), intends to identify EEG data's temporal and spatial features that are predictive of the emergence of a *** the convolutional layer, preprocessed data is fed into the three-layer CNN-model. From the input data, the layer of convolution extracts features that are useful. after feature extraction, fully interconnected (FC) layers are used to process the features by changing their weights. RNNs are made to handle sequential data by keeping memory states, particularly LSTM (Long Short-Term Memory) networks. RNN excels at recognizing sequential data's In order to take benefit of both architectures, a hybrid approach which utilizes CNN for extraction of features and RNN for modeling sequences can be implemented. In order to simulate temporal dependencies, layers of CNN may first extract spatial information, which are then given to RNN layers. the hybrid algorithm achieved 9 0. 0 2 % accuracy. © 2024 IEEE.

关键词： Electroencephalography

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the executable digital twin: merging the digital and the physics worlds 30

The executable digital twin: merging the digital and the phy...

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30th international conference on Noise and Vibration engineering, ISMA 2022 and 9th international conference on Uncertainty in Structural Dynamics, USD 2022

作者： Van der Auweraer, H. Hartmann, D. Siemens Industry Software NV Strategy & Innovation Interleuvenlaan 68 LeuvenB-3001 Belgium Siemens Industry Software GmbH Strategy & Innovation Otto-Hahn-Ring 6 Munich81739 Germany KU Leuven Department of Mechanical Engineering Celestijnenlaan 300 HeverleeB-3001 Belgium

ISBN: (纸本)9789082893151

While the digital twin has become an intrinsic part of the product creation process, its true power lies in the connectivity of the digital representation with its physical counterpart. Data acquired on the physical asset can validate, update and enrich the digital twin. the knowledge contained in the digital representation brings value to the physical asset itself. When a dedicated encapsulation is extracted from the digital twin to model a specific set of behaviors in a specific context, delivering a stand-alone executable representation, such instantiated and self-contained model is referred to as an Executable Digital Twin. In this contribution, key building blocks such as model order reduction, real-time models, state estimation and co-simulation are reviewed, and a number of characteristic use cases are presented. these include virtual sensing, hybrid testing and hardware-in-the loop, model-based control and model-based diagnostics. © 2022 proceedings of ISMA 2022 - international conference on Noise and Vibration engineering and USD 2022 - international conference on Uncertainty in Structural Dynamics. All rights reserved.

关键词： Structural dynamics

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An efficient vibroacoustic analysis of aerospace structure excited by turbulent boundary layer with pressure gradients 30

An efficient vibroacoustic analysis of aerospace structure e...

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30th international conference on Noise and Vibration engineering, ISMA 2022 and 9th international conference on Uncertainty in Structural Dynamics, USD 2022

作者： Saleh, T. Joshi, P. Klaerner, M. Scharowsky, T. ZAL Center of Applied Aeronautical Research Hein-sass-weg 22 Hamburg21129 Germany Chemnitz University of Technology Faculty of Mechanical Engineering Department of Lightweight Structures and Polymer Technology Chemnitz09107 Germany

ISBN: (纸本)9789082893151

there have been significant improvements in aircraft engine technology in last decade with extremely quieter engines available for commercial aviation. this technological advancement has created renewed interest for research on turbulent boundary layer (TBL) generated cabin noise in passenger aircrafts. Recent studies using computational fluid dynamics (CFD) and wind tunnel tests are focused on getting the reliable spectra of TBL excitation in areas of aircraft with adverse pressure gradient (APG). the aim of this paper is to quantify the impact of such TBL excitation on sound radiation from flat as well as curved aircraft stiffened panel. Comparison of TBL models with pressure gradient shows that the Goody model (which does not consider pressure gradient effects) underestimates the radiated sound by ∼ 10.0 dB when compared to the radiated sound from panels subjected to TBL model with adverse pressure gradient. © 2022 proceedings of ISMA 2022 - international conference on Noise and Vibration engineering and USD 2022 - international conference on Uncertainty in Structural Dynamics. All rights reserved.

关键词： Pressure gradient

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