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检索条件"任意字段=International Conference on Soft Computing and Pattern Recognition"

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Enhancing Sequential Recommendation System For MOOCs Based On Heterogeneous Information Networks

Enhancing Sequential Recommendation System For MOOCs Based O...

引用

international conference on Multimedia Analysis and pattern recognition (MAPR)

作者： Long Nguyen Thu Nguyen Khoa Tan-Vo Tu-Anh Nguyen Hoang Tri Nguyen Ngoc-Thanh Dinh Faculty of Computer Science University of Information Technology Ho Chi Minh City Vietnam Vietnam National University Ho Chi Minh City Vietnam Faculty of Information Science and Engineering University of Information Technology Ho Chi Minh City Vietnam Aalto University Finland The Industrial University Ho Chi Minh City Vietnam

ISBN: (数字)9798350368437

ISBN: (纸本)9798350368444

This study introduces a novel recommendation framework for MOOCs (Massive Open Online Courses)that leverages HINs (Heterogeneous Information Networks) to enhance sequential recommendation models. This is the first attempt to utilize HINs in this context, offering a more comprehensive approach than traditional methods that rely solely on homogeneous data sources. The framework employs HERec, an attentive meta-path based approach to capture contextual information and learn nuanced representations of learners and items. By combining HERec with sequential recommendation models like BERT4Rec and SASRec, the system provides personalized course recommendations based on user preferences, implicit relationships, and contextual factors, addressing the challenges of data diversity and sparsity. Experiments demonstrate a significant increase in accuracy, with the highest improvement reaching 12.69%, providing learners with more relevant and personalized course suggestions.

关键词： Computer aided instruction Electronic learning Accuracy soft sensors Multimedia systems Diversity reception Data models

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Techniques for Influencer Detection, Mapping, and Popularity Prediction in Social Media Networks

Techniques for Influencer Detection, Mapping, and Popularity...

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computing for Sustainability and Intelligent Future (COMP-SIF), international conference on

作者： Chandana T M Sreekanth Rallapalli Department of Master of Computer Applications Visveswaraya Technology University Nitte Meenakshi Institute of Technology Bengaluru Karnataka Department of Master of Computer Applications Nitte Meenakshi Institute of Technology Bengaluru Karnataka

ISBN: (数字)9798331538538

ISBN: (纸本)9798331538545

This paper recognizes the fact that in an age where consumption patterns are closely linked with social media platforms the measurement of key influential personalities and their effects on consumers is crucial. This paper offers an extensive analysis of the state-of-the-art methods for influencer identification and influence mapping. Approaches used in this research are based on Machine Learning and Deep Learning Algorithms which include Graph Attention Networks, Gated Recurrent Units, Graph-based Long Short-Term Memory Neural Networks, Recurrent Neural Networks, Stacked Autoencoders, Centrality Measures, and Frameworks such as Stimulus Organism Response. Comparing all of these approaches reveals their role in improving influencer marketing approaches, targeting, and the level of engagement, and profitability. The current study will benefit this area of knowledge by showing the outcomes, performance, and computational strengths of these approaches, paving the way for the enhancement of influencer marketing technology.

关键词： Deep learning Machine learning algorithms Consumer behavior Social networking (online) Profitability Current measurement Organisms pattern recognition Sustainable development Long short term memory

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A Comparative Technique with Credit card based Fraud detection with Machine Learning and Quantum Algorithm

A Comparative Technique with Credit card based Fraud detecti...

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Self Sustainable Artificial Intelligence Systems (ICSSAS), international conference on

作者： Meenalosini Vimal Cruz G. Usha N. A. S. Vinoth A. Anbarasi R. Thamizhamuthu Kumar Gautam Georgia Southern University USA Department of Computing Technologies SRMInstitute of Science and Technology Kattanlulathur Kanchipuram Dt TamilNadu Quantum Compting Lab Quantum Research And Centre of Excellence New Delhi India

ISBN: (数字)9798350368413

ISBN: (纸本)9798350368420

Quantum computing greatly benefit a wide range of fields, including the detection of credit card fraud, through its twin characteristics of improved computational power and efficiency. Quantum algorithms are used to enhance data analysis, pattern recognition and optimization properly with increased speed and efficiency. In the proposed model, we investigate how quantum machine learnings algorithms (QML) are used to spot credit card fraud using a data set that includes transactions from European cardholders. Various models such as neural network activation functions, epochs, and other factors employed in a hybrid quantum-classical method. The results from the best model employing a quantum hybrid technique, a conventional neural network, and an ML approach are compared. For equivalent prediction performance, we find that the quantum models train substantially more effectively than the conventional models. In order to implement Quantum algorithms, penny lane is used for enabling differentiable scripting of quantum computers that is cross-platform. Similar to how a neural network is trained, a quantum computer is trained. Overall, this in-depth investigation of the application of hybrid QML in credit card fraud detection shows significant promise.

关键词： Computers Training Machine learning algorithms Quantum algorithm Computational modeling Neural networks Predictive models Credit cards Fraud pattern recognition

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international conference on Modern Electronics Devices and Communication Systems, MEDCOM 2021

International Conference on Modern Electronics Devices and C...

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international conference on Modern Electronics Devices and Communication Systems, MEDCOM 2021

ISBN: (纸本)9789811963827

The proceedings contain 46 papers. The special focus in this conference is on Modern Electronics Devices and Communication Systems. The topics include: Medical Image Analysis Using soft computing Feature Selection and Classification of Skin Cancer;Comparative Study of Fuzzy, PID, and 2DOF-PID Controller for Liquid Level Control System;IOT-Based Self-nourishing System for Plants;Social Distance Alerting Device for COVID-19;BWDS-Based Spatially Dabble Couple Horizontal-Vertical 4-Port PIPO DRA with Poly-pattern Diversity;Design of U-Shaped MIMO Antenna for Wi-Fi Application;comparative Study of Parametric Disturbances Effect on Cart-Inverted Pendulum System Stabilization;Efficient Design of QCA ADD-SUB Subsystem for Future Microprocessors;predication of Diabetes Through Machine Learning Technique;comparative Analysis for Email Spam Detection Using Machine Learning Algorithms;Study of Gate Workfunction Modulated FinFET with Effect of TID;prediction of Accuracy and Performance of Crop Production by Using Machine Learning Algorithm;cognitive Load Classification in Alcoholic and Control Subjects Performing Delayed Matching Task Using Optimizable Classifier Networks;energy Detection in Cognitive Radio Networks to Optimize the Spectrum Utilization Through Cooperative Spectrum Sensing Using Weights;Real-Time Tracking of Health Parameters Using IOT and Data Logger: Application to COVID-19;Real-Time Facial Detection Using MATLAB (Utilizing VJ Method);Hardening of EMP in Shielded Enclosure for Radiated Fields;Review on Optimizing Text-Video Retrieval Using CLIP (Contrastive Language-Image Pre-training);argument Mining: A Categorical Review;optimizing Text: Representation of Similarity Using Machine Learning;post-quantum Cryptography: A Solution to the Challenges of Classical Encryption Algorithms;experimental Analysis on Aging Evaluation of Transformer Oil via Data Collection;designing Adiabatic Techniques for Logic Circuits.

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3rd international Workshop on Multiscale Multimodal Medical Imaging, MMMI 2022, held in conjunction with the 25th international conference on Medical Image computing and Computer Assisted Intervention, MICCAI 2022

3rd International Workshop on Multiscale Multimodal Medical ...

引用

3rd international Workshop on Multiscale Multimodal Medical Imaging, MMMI 2022, held in conjunction with the 25th international conference on Medical Image computing and Computer Assisted Intervention, MICCAI 2022

ISBN: (纸本)9783031188138

The proceedings contain 12 papers. The special focus in this conference is on Multiscale Multimodal Medical Imaging. The topics include: Towards Optimal Patch Size in Vision Transformers for Tumor Segmentation;Improved Multi-modal Patch Based Lymphoma Segmentation with Negative Sample Augmentation and Label Guidance on PET/CT Scans;visual Modalities Based Multimodal Fusion for Surgical Phase recognition;cross-Scale Attention Guided Multi-instance Learning for Crohn’s Disease Diagnosis with Pathological Images;vessel Segmentation via Link Prediction of Graph Neural Networks;A Bagging Strategy-Based Multi-scale Texture GLCM-CNN Model for Differentiating Malignant from Benign Lesions Using Small Pathologically Proven Dataset;Liver Segmentation Quality Control in Multi-sequence MR Studies;pattern Analysis of Substantia Nigra in Parkinson Disease by Fifth-Order Tensor Decomposition and Multi-sequence MRI;gabor Filter-Embedded U-Net with Transformer-Based Encoding for Biomedical Image Segmentation;Learning-Based Detection of MYCN Amplification in Clinical Neuroblastoma Patients: A Pilot Study.

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RIME-SVM for Electromagnetic Radiation Signal Identification in Coal Mining Environment

RIME-SVM for Electromagnetic Radiation Signal Identification...

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IEEE international conference on Power, Intelligent computing and Systems (ICPICS)

作者： Pengxue Zhu Shiqi Huang Le Liu Zheng Zhang China West Normal University Nanchong China

ISBN: (数字)9798350374315

ISBN: (纸本)9798350374322

In this study, an innovative signal classification and recognition system is proposed for the early warning needs of disasters such as impact ground pressure in coal mining. The RIME-SVM model is introduced, which combines the Rime Optimization Algorithm and Support Vector Machine to optimize the classifier parameter configuration and significantly improve the classification performance. Experiments have demonstrated that the model has excellent signal classification ability in industrial environments, which is especially suitable for the identification of electromagnetic radiation signals in coal mine environments. Compared with the traditional method, RIME-SVM significantly improves the classification accuracy, demonstrates the efficiency and accuracy of processing complex industrial signal data, and brings important progress to the field of coal mine safety monitoring technology.

关键词： Support vector machines Time-frequency analysis Accuracy pattern classification Electromagnetic radiation Data models Coal mining Classification algorithms Optimization Monitoring

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Intelligent Diagnosis of Pipeline Defects Based on Extreme Learning Machine 2

Intelligent Diagnosis of Pipeline Defects Based on Extreme L...

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2nd international conference on Electronics, Communications and Information Technology, CECIT 2021

作者： Xiong, Jingyi Liang, Wei Ding, Yu Yao, Junming CUP Beijing China Jiangsu Xukuang Energy CO.LTD Safety Supervision Xuzhou China

ISBN: (纸本)9781665437578

In order to carry out effective defect diagnosis of in-service oil and gas pipelines to ensure the safe and stable operation of oil and gas pipelines, this article proposes a pipeline defect intelligent diagnosis method based on particle swarm optimization and extreme learning machine. First, extract the defect signal features to form a feature vector set;then use the particle swarm algorithm to optimize the extreme learning machine to obtain hidden node thresholds;finally, divide the feature vector set into a testing set and a training set, and use improved extreme learning The machine is used as a pattern recognition algorithm for defect pattern recognition. Experimental results show that the method proposed in this paper can effectively perform fault pattern recognition, with a recognition accuracy of 92%, and is suitable for intelligent diagnosis of pipeline defects. © 2021 IEEE.

关键词： pattern recognition

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5th international conference on Inventive Computation Technologies, ICICT 2022 - Proceedings

5th International Conference on Inventive Computation Techno...

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5th international conference on Inventive Computation Technologies, ICICT 2022

ISBN: (纸本)9781665408370

The proceedings contain 243 papers. The topics discussed include: provably secure pseudonyms based authentication protocol for wearable ubiquitous computing environment;analysis of dc motor speed control and interfacing it with drowsiness detection;height and weight estimation of an individual from virtual visuals;projective synchronization of uncertain chaotic systems with different dimensions and external noise disturbance;design and implementation of a rescue and surveillance robot using cross-platform application;design of voice controlled multifunctional computer numerical control (CNC) machine;Bangla font recognition using transfer learning method;electroencephalography (EEG) based home automation for physically challenged people using brain computer interface (BCI);optimization of redirection algorithm based on cache technology in programming implementation of college students' mental health education information platform;a resistance detection device for microelectronic semiconductors: from signal detection to fusion analysis;and research on positioning accuracy of welding robot based on visual data mining and pattern fusion analysis algorithm.

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Theoretical Framework for Integrating IoT and Explainable AI in a Smart Home Intrusion Detection System

Theoretical Framework for Integrating IoT and Explainable AI...

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Contemporary computing and Communications (InC4), IEEE international conference on

作者： Mahi Dixit Swetha Maria Siby Jenefa J Divya Vetriveeran Rakoth Kandan Sambandam Vinodha D Department of Computer Science and Engineering CHRIST University Bengaluru India

ISBN: (数字)9798350383652

ISBN: (纸本)9798350383669

Using IoT devices in smart homes brings benefits and security dangers. This study extensively examines various intrusion detection methods within smart home environments. It also suggests a novel hybrid intrusion detection theoretical framework integrating IoT data with Explainable Artificial Intelligence (XAI) approaches. Using information from multiple IoT devices, including motion sensors, door/window sensors, cameras, and temperature sensors, our theoretical framework can create a comprehensive image of the home environment. By effectively detecting new threats, it offers anomaly detection utilizing unsupervised learning approaches to discover potential breaches without tagged data.

关键词： Temperature sensors Temperature measurement Explainable AI Intrusion detection Smart homes Motion detection pattern recognition

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Feature Fusion of LBP, HELBP & RD-LBP for Face recognition

Feature Fusion of LBP, HELBP & RD-LBP for Face Recognition

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international conference on Distributed computing and Optimization Tech-niques (ICDCOT)

作者： Karanwal, Shekhar Diwakar, Manoj Graph Era Univ CSE Dept Dehra Dun India

ISBN: (纸本)9789811922817;9789811922800

As literature suggests that single descriptor fails to produce desired results therefore the proposed work launches novel Fused Local Descriptor (FLD), by merging 3 state of art local descriptors. The services of FLD was taken from LBP, HELBP & RD-LBP. As all these 3 descriptors adopts different concepts therefore their integration is done. In LBP, the gray value (neighbors of patch (3 x 3 size)) are involved in comparison to center gray value. In HELBP, the gray value (horizontal neighbors of patch (3 x 5 size)) are involved in comparison to center gray value and in RD-LBP, the different scale pixels are compared. PCA is bring next for reduction and classification is further done by SVMs. FLD attains staggering rates than either of LBP, HELBP & RD-LBP. FLD also proves its significance in front of several other literatures based ones. ORL & GT are used for evaluation in MATLAB R2018a environment.

关键词： Horizontal Elliptical LBP (HELBP) Local Binary pattern (LBP) PCA Radial Difference LBP (RD-LBP) SVMs

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