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Siamese capsule gorilla troops network-based multimodal sentiment analysis for car reviews

Soft Computing 2024年第13-14期28卷 7627-7647页

作者： Kothuri, Sri raman rajaLakshmi, N.r. Department of Computer Science and Engineering School of Computing Vel Tech Rangarajan Dr. Sagunthala R & ampD Institute of Science and Technology Avadi Tamil Nadu Chennai600062 India

Sentiment analysis of online car reviews is a significant process in natural language processing. Numerous car enthusiasts and influencers create video reviews of automobiles on platforms for example YouTube. In realistic settings for sentiment analysis within this context, the task includes evaluating spoken reviews, the video content, and the emotions expressed by both the content creators and the viewers as reflected in the comments section. The vulnerability to facing circumstances in real-world scenarios where critical components are necessary for performing sentiment analysis on multimedia car reviews may unexpectedly be absent. To overcome this issue, siamese capsule gorilla troops network-based multimodal sentiment analysis for car reviews is proposed in this research work. Initially, pre-processing and feature extraction are performed on the audio, video and text information. The feature fusion is performed by enhancing spiking neural networks with geometric attention fusion network. The fused feature is fed as an input to siamese capsule gorilla troops network which classifies the emotion states as valence, arousal, and trustworthiness. Also, the algorithm called gorilla troop optimization (GTO) optimizes the classification error of the proposed siamese capsule network. Finally, this research work assesses high- and low-level features across modalities, introduces a novel enhancing spiking neural networks with geometric attention fusion network, enhances classification accuracy through new audio, video, and text embeddings, and boosts system robustness by integrating incomplete multimodal data. The achieved accuracy, precision, recall, and F-score values are 99%, 98.55%, 98.75%, and 98.02%, respectively, for the active multimodal sentimental analysis in car review (MuSe-Car) dataset. © The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature 2024.

关键词： Sentiment analysis

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Magnus Effect Wind Turbines using dC -Servo drive system for the cylinders 2

Magnus Effect Wind Turbines using DC -Servo Drive system for...

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2nd International Conference on Cyber Physical Systems, Power Electronics and Electric Vehicles, ICPEEV 2024

作者： Priya, r.A. Prakash, Vinoth John rajakumar, P. Department of Electrical and Electronics Engineering Vel Tech Rangarajan Dr. Sagunthala R&D Institute of Science and Technology Tamil Nadu Chennai India

ISBN: (纸本)9798350388664

This paper aims to produce energy at a very low wind speed. This fact, as well as the growing interest in the field of block chain technology, makes it possible to use this type of wind turbine in private household and domestic use as part of a distributed energy system instead of solar panels. To avoid a von Karman vortex street effect that occur when the cylinders rotate in the air flow, as well as to ensure maximum power, the optimal ratio between the wind speed and the cylinder rotation speed is determined using finite element analysis. © 2024 IEEE.

关键词： Wind turbines

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deep Learning Based drowsiness detection With Alert System Using raspberry Pi Pico

Deep Learning Based Drowsiness Detection With Alert System U...

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2023 International Conference on data science, Agents and Artificial Intelligence, ICdSAAI 2023

作者： Ashwini, A. Vaishnavi, T. rosi, A. Shahila, d. Ferlin deva Nalini, N. Vel Tech Rangarajan Dr. Sagunthala R&d Institute of Science and Technology Department of Ece Chennai India

ISBN: (纸本)9798350348910

Most people are losing their lives each year as a result of vehicle accidents caused by sleepy drivers. A device that can identify tiredness and notify the driver to it is necessary to prevent car accidents and save lives. Finding drowsy drivers is perhaps the most important step in stopping any traffic accident, everywhere in the globe. The goal of this work is to create alert strategy for smart vehicles which immediately halt drowsy driving problems. However, feeling tired is a normal physical phenomenon that can happen for a number of different causes. In order to stop the accident's cause, an accurate alarm system must be developed. The system for alerting sleepy drivers that has been developed using this technique is discussed in the proposed study where Video Stream Processing (VSP) is processed using the blinking criteria based on the eyes Euclidean distance. Additionally, the face marking method is created. The results of proposed work uses dlib, an OpenCV deep learning technique using raspberry Pi with a mounted camera for accurate detection, showing good results for detecting drowsiness, reducing the accident occurrence on the roads. The facial recognition algorithm developed by Haar starts with collected photographs as its input and outputs faces that are identified. © 2023 IEEE.

关键词： Aspect ratio

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IoT-rPC Based remote Controlling System for Energy-Efficient Air Conditioning and Ventilation in Shopping Malls

IoT-RPC Based Remote Controlling System for Energy-Efficient...

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2023 Intelligent Computing and Control for Engineering and Business Systems, ICCEBS 2023

作者： Arun, C.A. Gadde, Mukesh Narayana Sharma, Aditya raj, Tanya Dept of Ece Vel Tech Rangarajan Dr. Sagunthala R&d Institute of Science and Technology Chennai India

ISBN: (纸本)9798350394580

The rapid increase in public places, such as shopping malls, theatres, and supermarkets, has made it imperative to maintain a comfortable indoor environment for visitors. This work proposes a remote-controlling system to optimize the operation of air conditioners, ventilators, lights, and fans in shopping malls, ensuring both visitor comfort and energy efficiency. The system integrates the ESP32 microcontroller and the ThingsBoard IoT platform for seamless communication between devices and by utilizing the JSON-rPC protocol over MQTT communication. The proposed hardware setup involves deploying ESP32 microcontrollers on each shopping mall floor. MQTT communication is established between the ESP32 microcontroller and the ThingsBoard platform, enabling remote control of devices through an intuitive dashboard. The results demonstrate effective control over air conditioners and ventilators, leading to significant energy savings and enhanced visitor comfort. © 2023 IEEE.

关键词： dHT22 ESP32 MQTT PZEM004T rPC ThingsBoard

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Speed directive for Connected Autonomous Vehicles(CAV) on freeways 7

Speed directive for Connected Autonomous Vehicles(CAV) on fr...

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7th International Conference on Circuit Power and Computing technologies, ICCPCT 2024

作者： Vaishnavi, T. deva Shahila, d Ferlin Nalini, N. rosi, A. Ashwini, A. Priya, M. Sangeetha Vel Tech Rangarajan Dr. Sagunthala R&D Institute of Science and Technology Department of ECE Chennai India Department of Computer Science and Engineering Chennai India

ISBN: (纸本)9798350372816

Connected Autonomous Vehicles (CAV) is happening due to sensors incorporation in all road conditions and make driving judgements, and these sensors must be reliable for the vehicles to be safe. Accelerated devices hold the main segment among entire hindrance recognition devices. Generally, estimated to be built on vehicles more often. To identify obstacles, these sensors analyze ultrasonic emission and reflection data. Using the intrinsic weaknesses in sensors, we developed adaptive attacks using jamming, random spoofing, and spoofing on ultrasonic sensors. By doing this, we were able to a car into stopping when it shouldn't have and let it keep going. It substantiates our assaults using independent devices and mobile automobiles, like a Tesla Model that has Autopilot. Here, results show that occurrences induce blindness and malfunctions in both autonomous vehicles and sensors, which could lead towards crashes. The proposed deuce resistance strategies nearly improve the safety of accelerated devices and CAV with two methods of verifying signals. The suggested verified signals are sensor leveling physical shift authentication and multiple sensor consistency check, which uses multiple sensors to verify signals at the system level. © 2024 IEEE.

关键词： Ultrasonic sensors

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Pneumonia detection Using deep Learning techniques

Pneumonia Detection Using Deep Learning Techniques

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2023 IEEE International Conference on research Methodologies in Knowledge Management, Artificial Intelligence and Telecommunication Engineering, rMKMATE 2023

作者： Kavitha, M. Srinivsan, r. Triveni, Kandimalla Chowdary, Chilukuri Pavan Department of CSE Vel Tech Rangarajan Dr. Sagunthala R&D Institute of Science and Technology Chennai India

ISBN: (纸本)9798350305708

during this time of COVId-19, pneumonia needs to be diagnosed and treated properly. An accurate diagnosis of pneumonia requires an analysis of chest X-rays (CXrs). This requires the expertise of a radiologist. The fuzziness of CXr images makes diagnosis quite challenging and time-consuming, even for experienced radiologists. Human judgment can also lead to erroneous identification. The system can therefore play a significant role here if it is authentic and automated. Every sector uses deep Learning (dL) in this era of cutting-edge technology. detecting diseases affecting the chest is possible through chest radiography. Medical imaging research is incorporating computer vision techniques to detect disease. The literature on pneumonia detection is summarised and guidelines for medical practitioners are lacking, despite the fact that several algorithms exist for its detection. In this paper, CNN(Convolution Neural Networks) and VGG-16(Visual Geometry Group) are the algorithms used. The accuracy obtained when training CNN is 89% and for VGG-16 is 85%. The Adam Optimizer is used to assist in improving the accuracy and reduce the total loss. The precision and recall for CNN is 0.79, 0.81 and for VGG-16 is 0.83, 0.81. The dataset is taken from the Kaggle with the size of 2GB containing 16, 000 images of chest Xrays. © 2023 IEEE.

关键词： Adam Optimizer Chest X-ray CNN deep Learning Precision recall VGG-16

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Optimizing Energy Efficiency in Wireless Body Area Networks through NEEMA: A Hybrid Meta-Heuristic Approach

Optimizing Energy Efficiency in Wireless Body Area Networks ...

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2024 IEEE International Conference on recent Advances in science and Engineering technology, ICrASET 2024

作者： Bhuvaneswari, Govindappagari Gomathi, N. Vel Tech Rangarajan Dr. Sagunthala R&d Institute of Science and Technology Dept. of Computer Science and Engineering Avadi Tamil Nadu Chennai India

ISBN: (纸本)9798350388602

recent developments in Wireless Body Area Network (WBAN) technology have created a wide range of sensors capable of monitoring various physiological parameters in patients. However, the limited battery life of these sensors has constrained the potential of WBAN, highlighting the need for energy-efficient algorithms to address their substantial energy demands. To address this challenge, this paper introduces a novel Energy Efficient Hybrid Meta-Heuristic Approach (NEEMA) for WBANs. NEEMA combines the Tunicate Swarm Algorithm (TSA) and Genetic Algorithm (GA), collectively known as T-GA, to achieve high convergence and broad exploitation and exploration capabilities. The approach incorporates a clustering methodology to determine the Cluster Head (CH) using a fitness function derived from T-GA, which considers innovative parameters for conserving energy across the network. The study underscores the importance of multi-hop communication between patients equipped with sensor nodes, enabling data transmission to healthcare providers through multiple relay Head (rH) nodes, transmitting data to subsequent rHs and ultimately to the central data sink. The process for selecting rHs mirrors that of CHs. Experimental results demonstrate that NEEMA outperforms existing algorithms and offers advantages for various WBAN applications. © 2024 IEEE.

关键词： Sensor nodes

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Energy-Efficient I-rAW: An Intelligent-routing Solution for Wireless Body Area Networks 1

Energy-Efficient I-RAW: An Intelligent-Routing Solution for ...

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1st International Conference on Software, Systems and Information technology, SSITCON 2024

作者： Bhuvaneswari, Govindappagari Gomathi, N. Vel Tech Rangarajan Dr. Sagunthala R&d Institute of Science and Technology Avadi Dept. of Computer Science and Engineering Tamil Nadu Chennai India

ISBN: (纸本)9798350352931

recent advancements in sensing technology and the integration of electronic devices have given rise to a promising innovation called Wireless Body Area Networks (WBANs). This technology holds great potential to revolutionize healthcare by enabling remote health monitoring for patients not close to healthcare facilities. However, the sensor nodes placed on or beneath the skin to capture various physiological signals are limited by their battery life. This paper introduces the Intelligent-routing Algorithm for WBANs (I-rAW) to address this challenge, designed to prolong these sensor nodes' operational lifespan. The system uses two sinks on the patient's front and rear body to gather data from sensor nodes arranged into clusters and relay information through a cluster head (CH). The Tunicate Swarm Algorithm (TSA) facilitates the cluster head selection, considering residual energy, average network energy, node-to-sink distance, path loss, and energy consumption rate. Using dual sinks helps mitigate network hot-spot issues by reducing the need for multi-hop communication. According to simulation data, I-rAW outperforms the dual Sink technique, employing the dSCB protocol regarding stability and overall network lifespan. Furthermore, I-rAW outperforms other contemporary protocols across various performance metrics. © 2024 IEEE.

关键词： Sensor nodes

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ML Algorithm-Based Healthcare Predictor

ML Algorithm-Based Healthcare Predictor

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2023 International Conference on System, Computation, Automation and Networking, ICSCAN 2023

作者： Marichamy, d. Sankar, M. Sivaprakash, P. Chithambaramani, r. Yazhinian, S. Vel Tech Rangarajan Dr. Sagunthala R&d Institute of Science and Technology Department of Computer Science and Engineering Chennai India

ISBN: (纸本)9798350315127

By precluding, diagnosing, and treating mortal complaint, illness, injury, and other physical and internal impairments, healthcare aims to maintain or ameliorate overall health. Health professionals(providers or interpreters) in confederated health professions generally give healthcare. It encompasses work done in the fields of public health, primary care, secondary care, and tertiary care. There are cases when you or someone you know needs medical attention right down, but for some reason they aren't available. An online stoner backing and consulting design, our health vaticination design. Health professionals(providers or interpreters) in confederated health professions generally give healthcare. Primary care, secondary care, tertiary care, and public health are all possible stages of the delivery of healthcare. Through an online discussion platform, our work on the Healthcare Prediction System addresses this particular issue by offering health support to the general public. The system is loaded with information about multitudinous conditions, ails, and symptoms that was gathered from dependable sources. When a stoner registers on the website, they're given the option to partake their symptoms and problems. Grounded on this information, the system evaluates the data using the applicable models and estimates the disease that the case's symptoms are most likely to be related to. © 2023 IEEE.

关键词： Public health

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Locating Patient Health data Theft Using Gradient Boosting with Hybrid Microwave Transmission-Based Wearable device

Locating Patient Health Data Theft Using Gradient Boosting w...

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2024 International Conference on Signal Processing, Computation, Electronics, Power and Telecommunication, IConSCEPT 2024

作者： Allimuthu, Udayakumar Singh, Edwin C. Sivaraman, V. ratnavathi, Konagalla Kumar reddy, Y. Pavan Krishna, O. Vamsi Surekha, Addanki Venkata Vel Tech Rangarajan Dr. Sagunthala R&D Institute of Science and Technology Deemed to be University Tamil Nadu Chennai600062 India Madanapalle institute of Technology & Science Andhra Pradesh India Veltech Rangarajan Dr Sagunthala R&D Institute of Science and Technology Tamil Nadu Chennai600062 India

ISBN: (纸本)9798331540685

The research article addresses the intersection of healthcare monitoring and crime prevention via wearable devices in hospital settings. It proposes a system leveraging blockchain, decision-making algorithms, and wireless communication, particularly IoT and gradient-boosting approaches. Existing health care monitoring lacks real-time intervention capabilities, and conventional crime prevention methods are often reactive rather than proactive. The revolutionary combination of gradient boosting and hybrid microwave transmission-based wearable devices is the ultimate solution to combat patient health data theft. With this cutting-edge technology, this research can confidently detect and prevent unauthorised access to sensitive healthcare information, ensuring the safety and privacy of patients. The proposed system ensures continuous health monitoring and prompt interventions while enhancing crime prevention through mobile data analysis. Blockchain and decision-making algorithms are integrated to securely store patient data and enable authorised personnel access for review. IoT and gradient-boosting algorithms facilitate real-time health monitoring and accurate prediction of crime-related patterns through mobile data analysis. The proposed gradient boosting algorithm has an rMSE of 0.105 and an MAE of 0.010, suggesting great prediction accuracy. With a V AF score of 96% and an r-squared score of 0.94, it captures data variability while demonstrating predictive solid power. This comprehensive strategy utilises cutting-edge technology to enhance healthcare monitoring via wearable devices, contribute to crime prevention, and address crucial concerns in healthcare and public safety. © 2024 IEEE.

关键词： data privacy

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