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Hate Speech Detection Using Machine Learning In Bengali Languages 6

Hate Speech Detection Using Machine Learning In Bengali Lang...

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6th international conference on Intelligent computing and Control systems, ICICCS 2022

作者： Islam, Mominul Hossain, Md Sanjid Akhter, Nasrin Daffodil International University Dept. of Cse Dhaka Bangladesh

ISBN: (纸本)9781665410359

Hate speech is a common problem in the current time of social media and the internet as it is very easy to be in touch with everything through the internet and social media. Hate speech detection research is not very rare but in terms of Bengali language there are very few works related to hate speech in Bengali language. the proposed research experiment has developed a machine learning based project to detect hate speech from Bengali language data or comments, posts in social media that are in Bengali language. this research work has used 3006 pure Bengali data from social media pages (such as Facebook, YouTube) groups, comment sections of news portals. Further, this research work has categorized them in 0 for non-Hate-Speech and 1 for Hate-Speech to classify the data between non-abusive and abusive data. this research work has used several algorithms to find the best possible result in order to determine whether the sentence is abusive or non-abusive such as Logistic Regression, Naive Bayes, Random Forest, Support Vector Machine, K Nearest Neighbor Classifier. From these algorithms, the best result for detecting non-abusive data is the Random Forest [RF] algorithm, which is 67%. © 2022 IEEE.

关键词： Decision trees

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BIOIMAGING 2020 - 7th international conference on Bioimaging, proceedings;Part of 13th international Joint conference on Biomedical Engineering systems and Technologies, BIOSTEC 2020

BIOIMAGING 2020 - 7th International Conference on Bioimaging...

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7th international conference on Bioimaging, BIOIMAGING 2020 - Part of 13th international Joint conference on Biomedical Engineering systems and Technologies, BIOSTEC 2020

ISBN: (纸本)9789897583988

the proceedings contain 28 papers. the topics discussed include: photoluminescent imaging for an effective cancer diagnosis using upconversion nanoparticles;assessment of gallbladder wall vascularity from laparoscopic images using deep learning;curriculum deep reinforcement learning with different exploration strategies: a feasibility study on cardiac landmark detection;low-density EEG for source activity reconstruction using partial brain models;fully automated volumetric measurement of malignant pleural mesothelioma from computed tomography images by deep learning: preliminary results of an internal validation;segmentation of diabetic retinopathy lesions by deep learning: achievements and limitations;and comparison of gadolinium contrast agent retention in patients receiving multiple contrast-enhanced MRI exams.

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VLocSense: Integrated VLC System for Indoor Passive Localization and Human Sensing 30

VLocSense: Integrated VLC System for Indoor Passive Localiza...

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30th international conference on Mobile computing and Networking, ACM MobiCom 2024

作者： Li, Jiarong Ge, Changshuo Xu, Chihan Gong, Junhao Gui, Weihua Zhang, Chaobo Liang, Xiaojun Ding, Wenbo Tsinghua-Berkeley Shenzhen Institute Shenzhen International Graduate School Tsinghua University Shenzhen China Pengcheng Laboratory Shenzhen China Shenzhen International Graduate School Tsinghua University Shenzhen China School of Automation Central South University Changsha China Pengcheng Laboratory RISC-V International Open Source Laboratory Shenzhen China

ISBN: (纸本)9798400704895

the demand for accurate and real-time indoor localization and human sensing is rising with the development of smart environments, with applications in security and smart homes. Effective systems enhance safety, energy efficiency, and user experience by leveraging existing infrastructure, reducing deployment costs, and integrating seamlessly. Traditional methods rely on dedicated hardware, while communication or lighting infrastructure can provide dual-purpose solutions. this research focuses on Visible Light Communication (VLC) technology, which uses visible light for data transmission. Our VLC system utilizes existing lighting infrastructure to transmit data, providing localization and human sensing functionalities. the system design strategically incorporates specific VLC transmitters and receivers to enhance sensing performance. the collected data is processed using advanced algorithms and machine learning models, ensuring robust, real-time, and cost-effective localization with an accuracy of 96.6% and human activity recognition with an accuracy of 98.3%. this multi-functionality system demonstrates the potential for VLC in healthcare monitoring and home automation applications. © 2024 Copyright held by the owner/author(s).

关键词： Smart homes

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Numerical Experiments with Artificial Life for Segmentation of Breast Ultrasound. Tests Against State-of-the-art 9

Numerical Experiments with Artificial Life for Segmentation ...

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Joint 9th international conference on Digital Arts, Media and Technology with 7th ECTI Northern Section conference on Electrical, Electronics, Computer and Telecommunications Engineering, ECTI DAMT and NCON 2024

作者： Makhanov, Stanislav S. Karunanayake, Nalan Sirindhorn International Institute of Technology Thammasat University School of Information and Computer Technology Thailand

ISBN: (纸本)9798350318241

In 2023 we offered a new model for segmentation of ultrasound (US) images of the breast which combines a grey level mask, Artificial Life (AL) and a Genetic Algorithm (GA) [1]. the model has been compared with 14 segmentation models which represented different ways to approach the problem i.e. deformable shapes, machine learning, superpixels, edge linking, Deep learning (DL) networks and various hybrids of DL with the conventional methods. the method outperformed 14 selected state-of-the-art algorithms applied to the US images characterised by complex geometry and a high level of noise. the present paper offers an extension of this algorithm where the step of the thresholding for generation of the image mask (fast but often not accurate) is replaced by a DL method. the proposed structure is a critical modification of the previous idea. It offers a new combination of the DL and AL. the novelty is an efficient compromise between the simplicity of the black-box DL network and the interpretability of the deterministic AL. the trained DL generates a mask which approximates the tumour. Since it is a rough approximation of the object, the DL network performs this task faster than an actual segmentation. Further, the AL exists inside the mask superimposed on the edge map. the AL trained by the GA outlines the tumors. the method shows promising results as applied to segmentation of complex US tumours handling even previously unseen data. the tests based on the characteristics of the US edge maps and the tumour shapes highlight the advantages of the proposed model. © 2024 IEEE.

关键词： Deep learning

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7th international Congress and Workshop on Industrial AI and eMaintenance, IAI 2023

7th International Congress and Workshop on Industrial AI and...

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7th international Congress and Workshop on Industrial AI and eMaintenance, IAI 2023

ISBN: (纸本)9783031396182

the proceedings contain 58 papers. the special focus in this conference is on Industrial AI and eMaintenance. the topics include: A Conceptual Model for AI-Enabled Digitalization of Construction Site Management Decision Making;Risk-Based Dependability Assessment of Digitalised Condition-Based Maintenance in Railway—Part II–Event Tree Analysis (ETA);making Tracks—Combining Data Sources in Support of Railway Fault Finding;Simulation Environment Evaluating AI algorithms for Search Missions Using Drone Swarms;Risk-Based Dependability Assessment of Digitalised Condition-Based Maintenance in Railway Part I–FMECA;climate Zone Reliability Analysis of Railway Assets;remaining Useful Life Estimation for Anti-friction Bearing Prognosis Based on Envelope Spectrum and Variational Autoencoder;artificial Intelligence in Predictive Maintenance: A Systematic Literature Review on Review Papers;using a Drone Swarm/Team for Safety, Security and Protection Against Unauthorized Drones;Use Cases of Generative AI in Asset Management of Railways;design, Development and Field Trial Evaluation of an Intelligent Asset Management System for Railway Networks;analysing Maintenance and Renewal Decision of Sealed Roads at City Council in Australia;issues and Challenges in Implementing the Metaverse in the Industrial Contexts from a Human-System Interaction Perspective;development of a Biologically Inspired Condition Management System for Equipment;application of Autoencoder for Control Valve Predictive Analytics;LCC Based Requirement Specification for Railway Track System;pre-processing of Track Geometry Measurements: A Comparative Case Study;Wind Turbine Blade Surface Defect Detection Based on YOLO Algorithm;cooperative Search and Rescue with Drone Swarm;domain Knowledge Regularised Fault Detection;a Neuroergonomics Mirror-Based Platform to Mitigate Cognitive Impairments in Fighter Pilots;HFedRF: Horizontal Federated Random Forest.

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Message from the conference Chair

Proceedings - 7th International Conference on Computing Meth...

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proceedings - 7th international conference on computing Methodologies and Communication, ICCMC 2023 2023年

作者： Senthilnathan, K.

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4th international conference of Artificial Intelligence, Medical Engineering, Education, AIMEE 2020 held at the Mechanical Engineering Institute of the Russian Academy of Sciences, 2020

4th International Conference of Artificial Intelligence, Med...

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4th international conference of Artificial Intelligence, Medical Engineering, Education, AIMEE 2020 held at the Mechanical Engineering Institute of the Russian Academy of Sciences, 2020

ISBN: (纸本)9783030671327

the proceedings contain 37 papers. the special focus in this conference is on Artificial Intelligence, Medical Engineering, Education. the topics include: A Neural Network Featured System for Learning Performance of Students;method of Fuzzy Agreed Alternative Selection in Multi-agent systems;Evaluation of the Effect of Preprocessing Data on Network Traffic Classifier Based on ML Methods for Qos Predication in Real-Time;the Task of Improving the University Ranking Based on the Statistical Analysis Methods;deep-Learned Artificial Intelligence for Consciousness – thinking Objectization to Rationalize a Person;algorithmization of Computational Experiment Planning Based on Sobol Sequences in the Tasks of Dynamic systems Research;Modification of the Hausdorff Metric in Combination with the Nearest Point Algorithm ICP in Point Cloud Construction Problems;functional systems Integrated with a Universal Agent of Artificial Intelligence and Higher Neurocategories;calculation of the Current Distribution Function Over a Radiating Structure with a Chiral Substrate Using Hypersingular Integral Equations;influence of Image Pre-processing algorithms on Segmentation Results by Method of Persistence Homology;influence of Delays on Self-oscillations in System with Limited Power-Supply;cognitive Prediction Model of University Activity;temperature Reaction of a Person with a Contact Method of Exposure to a thermal Signal;study of the Force-Moment Sensing System of a Manipulative Robot in Contact Situations with Tenzoalgometry of Soft Biological Tissues;the Influence of Hydroplasma on the Proliferative and Secretory Activity of Human Mesenchymal Stromal Cells;the Biotechnological Method for Constructing Acoustic and Vibration Sequences Based on Genetic DNA Sequences;telemedicine Monitoring with Artificial Intelligence Elements.

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Relaxation State Assessment on Sleepy Driver through EEG-Based Ensemble Learning 9

Relaxation State Assessment on Sleepy Driver through EEG-Bas...

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作者： Umsura, Bunyarat Chaisricharoen, Roungsan Sittiprapaporn, Phakkharawat Srimaharaj, Wanus Mae Fah Luang University School of Information Technology Chiang Rai57100 Thailand Mae Fah Luang University Neuropsychological Research Laboratory Neuroscience Research Center School of Anti-Aging and Regenerative Medicine Bangkok10120 Thailand Payap University The International College Chiang Mai50000 Thailand

ISBN: (纸本)9798350318241

As the prevalence of sleepy driving continues to pose a significant threat to road safety, the need for alternative methods to assess the relaxation state of sleepy drivers becomes necessity. this study presents an alternative approach utilizing Electroencephalography (EEG) data and a synergistic ensemble learning on Neural Networks (NN) and Random Forest (RF) models with hyperparameter tuning. EEG signals, obtained from drivers in simulated or real-world scenarios, capture neurophysiological patterns indicative of relaxation levels. the proposed methodology involves meticulous preprocessing of EEG data to normalize features and split the dataset for training and testing. A Neural Network is designed to capture intricate patterns in the EEG data, while a Random Forest, optimized through hyperparameter tuning, enhances robustness and generalization. Ensemble learning, combining the strengths of both models, provides a comprehensive evaluation of the relaxation state. Results demonstrate the efficacy of the EEG-NN-RF ensemble in accurately assessing drivers' relaxation states, paving the way for effective monitoring systems and adaptive driver assistance technologies. this research advances proactive measures to mitigate risks associated with sleepy driving, contributing to road safety and accident prevention. © 2024 IEEE.

关键词： Electroencephalography

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Window Function Dependency on Male and Female Speech Signals for Pitch Extraction at Low SNRs 7th

Window Function Dependency on Male and Female Speech Signals...

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7th international conference on Soft computing: theories and Applications, SoCTA 2023

作者： Rahman, Md. Saifur Parvin, Nargis Rahman, Moinur Department of Information and Communication Technology Comilla University Cumilla Bangladesh Department of CSE Bangladesh Army International University of Science and Technology Cumilla Cumilla Cantonment Bangladesh

ISBN: (纸本)9789819720309

this research suggests an efficient idea that is better suited for speech processing applications for retrieving the accurate pitch from speech signals in noisy conditions. Almost every pitch detection method has windowing as a significant part of segmentation. this research considers using Hanning, Hamming, and rectangular windows’ function on male and female speech signals separately for pitch extraction. Also, analyze the windowing effect on the speech signal analytically to understand which window function is more suitable and effective for male and female speech signals specifically. For the validation of our idea, we have utilized the conventional autocorrelation function, cepstrum method and state-of-the-art method BaNa. this study puts out a potent idea that will work better for speech processing applications in noisy speech. From experimental results, the proposed idea represents which window function is more appropriate for male and female speech signals in noisy environments. © the Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2024.

关键词： Extraction

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7th international conference on Recent Advances in Geotechnical Earthquake Engineering and Soil Dynamics, ICRAGEE 2020

7th International Conference on Recent Advances in Geotechni...

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7th international conference on Recent Advances in Geotechnical Earthquake Engineering and Soil Dynamics, ICRAGEE 2020

ISBN: (纸本)9789813340046

the proceedings contain 34 papers. the special focus in this conference is on Recent Advances in Geotechnical Earthquake Engineering and Soil Dynamics. the topics include: Behavior of Pile Group in Liquefied Soil Deposits Under Earthquake Loadings;dynamic Response of Soil Nailed Wall;seismic Response of Buildings Resting on Pile-Raft Foundation in Soft Soil;state of the Art on Combined Pile Raft Foundation;analytical Study on Dynamic Coupling Interaction Effects Between Adjacent Building Structures;A Comparative Study on Predictive Capability of Different SSI Models;seismic Performance of Building Frames Considering Soil–Structure Interaction;seismic Analysis of Reinforced Concrete Structure Resting on Liquefiable Soil;Effect of Soil-Structure Interaction on Seismic Performance of RC Framed Building with Viscous Wall Dampers;a Critical Review of Indian Seismic Codes for Buildings in the Light of international Codes of Practice;response of Multistoried Building Considering Soil-Structural Interaction Under Lateral Loading;Seismic Response of Buildings Resting on Sloping Ground Considering SSI Effect—An Experimental Study;a Study on Dynamic Response of Hyperbolic Cooling Tower for Fixed Base Condition;numerical Simulation of Soil-Tunnel Interaction Under Surface Blast Loading;dynamic Analysis of Deep Beams on Vlasov Foundation;seismic Analysis of Soil-Pile-Structure System in Stratified Ash-Soil Deposit;Dynamic Response of Circular Base Slabs (CBS) Attached to the Seismic Bearing systems, Inserted for Base-Isolation Underneath the Buildings;a Case Study on the Evaluation of Seismic Response of Earthen Dam;Behaviour of RC Frame Subjected to Fire Following Earthquake;analysis of Urban Tunnels Under Different Loading Conditions.

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