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检索条件"任意字段=7th International Conference on Computing in Engineering and Technology, ICCET 2022"

共 10988 条记录，以下是431-440 订阅

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Recognition of Facial Stress System using Machine Learning with an Intelligent Alert System 7

Recognition of Facial Stress System using Machine Learning w...

引用

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

作者： Raja, S. Kanaga Suba Durai Arumugam, S.S.L. Kumar, R. Praveen Selvakumar, J. Easwari Engineering College Chennai India Dept. of Information Technology Easwari Engineering College Chennai India Dept. of Electronics and Communication Engineering Easwari Engineering College Chennai India Dept. of Computer Science and Engineering Sri Ramakrishna Engineering College Coimbatore India

ISBN: (纸本)9781665464086

the primary component in this paper is to investigate the facial emotional states and EEG indicators, especially in pressure, for the duration of the interplay with games. the proposed paper identifies sure precise expressions in game enthusiasts whose facial feelings are segmented frames were separated into special areas, then the mind indicators are classified based on their frequencies, ranges are also analysed, and the signal value is *** on facial features are extracted from the localized areas, used fuzzy c-means class, and directed onto an emotion space. then the EEG sign price is evaluated with the brink fee. After that, the strain data can be ship thru by using a SMS alert by using GSM module and buzzer alerts the use of Arduino micro controller. the cease results are accurate and robust. © 2023 IEEE.

关键词： C (programming language)

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An Efficient Way to Predict Stock Price using LSTM-RNN Algorithm 7

An Efficient Way to Predict Stock Price using LSTM-RNN Algor...

引用

7th international conference on Intelligent computing and Control Systems, ICICCS 2023

作者： Polepally, Vijay Kumar Jakka, Neha Reddy Vishnukanth, Pendly Raj, Rachakatla Sushanth Anish, Gudavelli Kakatiya Institute of Technology and Sciences Department of Computer Science and Engineering Telangana Warangal India

ISBN: (纸本)9798350397253

Stock price prediction is a challenging and important task in finance. Machine learning algorithms have shown promise in predicting stock prices, with the ability to analyze large datasets and identify complex patterns. this study presents a comprehensive study of machine learning algorithms for stock price prediction. the proposed approach uses a variety of machine learning algorithms, including decision tree, random forest, support vector regression, and artificial neural networks. the models are trained on historical stock price data and evaluated using real-world data from various companies. this study calculates the RMSE, Error rate and the closing price of the stock for that day. © 2023 IEEE.

关键词： Forecasting

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A Hybrid Approach of Spider Monkey Optimization with Taylor Series for Optimal Routing in Wireless Sensor Network 7

A Hybrid Approach of Spider Monkey Optimization with Taylor ...

引用

7th international conference on Inventive Computation Technologies, ICICT 2024

作者： Sindhuja, M. Srm Institute of Science And Technology School of Computing College of Engineering And Technology Department of Computing Technologies Chennai Tamil Nadu Kattankulathur India

ISBN: (纸本)9798350359299

Clustering that facilitates routing protocols has been created in recent years to cut down on energy usage and increase the lifespan of WSNs. the LEACH cluster is well-known among WSNs. the LEACH selects a few sensor nodes at random from each cluster. Cluster heads (CHs) are the aforementioned nodes. Cluster members are the sensor nodes that make up each CH. CHs hold up extra load to coordinate diverse tasks during the cluster. Energy usage and overall network performance can both suffer if the wrong CHs are selected for the LEACH. therefore, a significant factor in extending the WSN's lifetime is selecting an appropriate CH and an efficient routing algorithm. this work introduces a new approach to CH selection and optimal routing in WSN, combining the Spider monkey optimization technique with a Taylor-based gravitational search algorithm. the CHs are selected, and cluster-based routing algorithms are developed using Spider Monkey Optimization (SMO). the sensor nodes are first organized into clusters, with the maximum competent node being the cluster head. From there, communication is sent across several nodes in a multi-hop fashion. Taylor dependent gravitational search method (TDGSM) is introduced which uses the taylor series along with gravitational search method to find the optimal routing. the suggested algorithm has achieved superior results when compared to the existing methods. © 2024 IEEE.

关键词： Sensor nodes

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Early Prediction of Obesity Risk in Older Adults using XGBoost Classifier 7

Early Prediction of Obesity Risk in Older Adults using XGBoo...

引用

7th international conference on Circuit Power and computing Technologies, ICCPCT 2024

作者： Prasher, Shikha Nelson, Leema Chitkara University Insititue of Engineering & Technology Chitkara University Punjab India

ISBN: (纸本)9798350372816

Obesity is a complex disorder caused by hereditary, environmental, and behavioural factors. this work proposes a solid predictive model for assessing obesity risk, with a stunning 96% accuracy rate. the model use machine learning approaches to categorise individuals into different obesity risk categories based on pertinent variables such as demographic information, lifestyle habits, and medical history. the generated model predicts obesity risk levels with improved accuracy thanks to thorough data preparation, feature engineering, and model optimisation. With an accuracy of 96%, the model assists healthcare providers in identifying individuals with varied levels of obesity risk, allowing for focused interventions and personalised health management plans. Further research and validation efforts are needed to evaluate the model's efficacy across varied populations and healthcare contexts, assuring wider acceptance and applicability in real-world healthcare practice. © 2024 IEEE.

关键词： Nutrition

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Secure Transmission with a Full-Duplex Relay in Power Line Communications 7

Secure Transmission with a Full-Duplex Relay in Power Line C...

引用

7th IEEE international Electrical and Energy conference, CIEEC 2024

作者： Zhang, Jiarui Du, Baosen Liu, Xiaosheng Xu, Dianguo School of Electrical Engineering and Automation Harbin Institute of Technology Harbin China Beijing Institute of Precision Mechatronics and Controls Beijing China Laboratory of Aerospace Servo Actuation and Transmission Beijing China

ISBN: (纸本)9798350359558

With the increasingly prominent security problems of Industrial Internet and the rapid development of computing technology, the security of power line communication (PLC) based on classical encryption technology faces new challenges. In this paper, a secure transmission scheme of PLC relay network based on full-duplex (FD) is proposed. In this scheme, the transmitter transmits the composite signal containing the information-bearing signal and the jamming signal. the relay forwards the received signal in the last time slot according to the amplify-and-forward (AF) strategy while receiving the signal transmitted by the transmitter. the receiver transmits the jamming signal while receiving the signal transmitted by the relay. Based on the lognormal correlated channel model and the Bernoulli-Gaussian noise model, we derive the closed-form expressions for average secrecy capacity (ASC), secrecy outage probability (SOP), and effective secrecy throughput (EST), assuming maximum ratio combining are utilized at the eavesdropper. According to the theoretical analysis, we find the optimal power allocation to improve the secrecy performance with the external eavesdropper or the untrusted relay. Furthermore, Monte-Carlo simulation is utilized to verify our analysis. Simulation results show that the proposed method is superior to the traditional scheme. © 2024 IEEE.

关键词： Transmitters

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Simulation of Battery Driven Electric Vehicle with Regenerative Braking 7

Simulation of Battery Driven Electric Vehicle with Regenerat...

引用

7th international conference on Circuit Power and computing Technologies, ICCPCT 2024

作者： Patan, Muzeeb Khan Srinivasu, Nakka Mounica, Patil Reddy, Putchakayala Yanna Kiran Kumar, Kukkamalla UTAS-Muscat Electrical Engineering Oman SRKR Engineering College Dept. of EEE Bhimavaram India Vardhaman College of Engineering Dept. of EEE Hyderabad India Bharat Institute of Engineering and Technology Department of Electrical & Electronics Engineering Hyderabad India

ISBN: (纸本)9798350372816

this work introduces a simulation framework aimed at evaluating the efficacy of regenerative braking systems in electric vehicles (EVs) utilizing brushless DC (BLDC) motors. Central to the simulation is the regenerative braking system, which efficiently captures energy during braking utilizing PID controllers to optimize performance while ensuring vehicle stability. Moreover, closed-loop control strategies are incorporated to adapt motor speed and torque in response to real-time inputs from the braking pedal, enhancing the overall responsiveness and efficiency of the system. With a focus on monitoring and visualization tools, this work facilitates the analysis of simulation results in real-time, offering valuable insights into optimal vehicle design, control strategies, and energy management techniques for sustainable electric mobility. By evaluating the performance of EVs under diverse driving scenarios and assessing the impact of regenerative braking on energy efficiency, this research contributes to the advancement of electric vehicle technology, paving the way for more environmentally friendly and efficient transportation solutions in the future. © 2024 IEEE.

关键词： Regenerative braking

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Research on Multi-Objective Optimization Method for Ship Tank Loading Based on Improved Non-dominated Genetic Algorithm 7

Research on Multi-Objective Optimization Method for Ship Tan...

引用

7th international conference on Intelligent Robotics and Control engineering, IRCE 2024

作者： Qi, Ming Yang, Yue Chai, Song Ni, Hongtao Shanghai Zhongchuan SDT-NERC Co. Ltd Digital Technology Department Shanghai China Suzhou Zainuo Information Technology Co. Ltd Digital Technology Department Suzhou China Suzhou City University Computing Science and Artificial Intelligence College Suzhou China

ISBN: (纸本)9798350352399

Ship tank loading and unloading is one of the most frequent and typical operational scenarios. Meanwhile, ship loading and unloading operations are influenced by various factors such as meteorological and hydrological conditions in the operational waters, operational safety redundancy, operational windows, and more, all of which place extremely high demands on the efficiency and reliability of the loading plan. To improve the efficiency of ship tank loading and enhance control over the safety of the loading process, this paper constructs a complex loading condition characterized by calibrated loading capacity and floating state. An optimization model for ship tank loading plans is proposed, aiming to optimize the strength of the loading state. Based on the characteristics of this model, multiple optimization objectives and boundary conditions are sorted out. the NSGA-III method adapted to the specific needs, is used to facilitate the iteration of effective populations, thereby enabling the rapid generation of loading plans. this approach changes the traditional process of generating loading plans through multiple interactive iterations of first loading and then verifying against loading targets. Instead, it first determines the loading targets and then uses algorithms to find the optimal loading plan, improving the purposefulness of the loading work and optimizing the search process for loading plans. © 2024 IEEE.

关键词： Tanks (containers)

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Research progress and trend analysis of object tracking technology based on CiteSpace 7

Research progress and trend analysis of object tracking tech...

引用

7th international conference on Intelligent computing and Signal Processing, ICSP 2022

作者： Yu, Liang Qingdao University of Technology School of Information and Control Engineering Qingdao China

ISBN: (纸本)9781665478571

Object tracking technology is an important research direction in the field of computer vision, and nowadays, it has played an increasingly indispensable role in the fields of intelligent surveillance, modern military, human-computer interaction, intelligent transportation, etc. While making breakthroughs, it has also brought great convenience to people's lives. In this paper, CiteSpace information visualization software is used to visualize the object tracking research literature based on nearly 10,000 papers in the field of object tracking from 2001 to 2021. From the bibliometric perspective, the visual knowledge graphs of information on three aspects of object tracking technology: scientific cooperation, research fields, and recent progress are analyzed, in which the analysis of scientific cooperation includes the distribution of countries and institutions, the analysis of research fields includes the distribution of categories and keywords, and the analysis of recent progress and frontiers includes the distribution of references and the analysis of keyword timeline graph. then, we present the three main problems and challenges facing this technology: changes of illumination and color, changes of scene and posture, and the distinction between foreground and background. And three targeted suggestions are proposed for feature fusion, 3D reconstruction, and deeper development based on Siamese Network in deep learning algorithms. Finally, the future development of object tracking technology has been prospected. © 2022 IEEE.

关键词： Computer vision

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Design of Intelligent Teaching Evaluation System Based on Emotion Recognition Algorithm 7

Design of Intelligent Teaching Evaluation System Based on Em...

引用

7th international conference on Education, Network and Information technology, ICENIT 2024

作者： Xue, Wei Liu, Jie Guangxi Vocational Normal University School of Communications Nanning China Guangxi Vocational Normal University School of Computer and Information Engineering Nanning China

ISBN: (纸本)9798350374919

Recently, with the rapid development of artificial intelligence technology, emotion recognition algorithms provide new possibilities for innovative intelligent teaching evaluation methods, which is both an important direction for the development of modern educational technology and a research hotspot in the field of educational evaluation. Taking the emotion algorithm as the theoretical basis and using advanced computer vision technology, this paper designed an intelligent teaching evaluation system based on facial expressions and postural movements to accurately assess the classroom status of students in real time. the system uses residual network model to classify and recognize facial expressions and postural movements, and designs an event statistical model to calculate student engagement and status scores as one of the reference indicators for quality evaluation in real-time classrooms. the experimental results show that the system can correctly record the real-time situation of the classroom, provide educators with intelligent teaching evaluation, innovate the teaching evaluation system, and provide a strong guarantee for improving the quality of teaching and the learning effect of students. © 2024 IEEE.

关键词： Emotion Recognition

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Advancements in Face Masking Anonymization: Novel Approaches, Robust Privacy Metrics, and Real-Time Solutions 7

Advancements in Face Masking Anonymization: Novel Approaches...

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7th international conference on Electronics, Communication and Aerospace technology, ICECA 2023

作者： Gs, Prabith Abhishek, S. Anjali, T. Ramlal, Nandakishor Prabhu Amrita School of Computing Department of Computer Science and Engineering Amrita Vishwa Vidyapeetham Amritapuri India Altair Engineering AIOT-Development Stockholm Sweden

ISBN: (纸本)9798350340600

In todays world, where concerns about privacy are on the rise the use of techniques to mask faces and protect individuals identities in multimedia content has become extremely important. this study thoroughly examines methods of anonymization with a specific focus on how Generative Adversarial Networks (GANs) can be used to enhance privacy preservation. By conducting an analysis that includes techniques like Gaussian Blur, Pixelation, Deep Learning and hybrid approaches our research highlights the impressive effectiveness of GAN based anonymization. this innovative approach not effectively hides identities but also ensures that the anonymized content remains understandable and usable. Alongside evaluating existing techniques our paper also sets the stage for exploration, in this field with the goal of advancing face masking anonymization techniques. © 2023 IEEE.

关键词： Semantics

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