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Development of an Automated Tool for Driver Drowsiness Detection 7

Development of an Automated Tool for Driver Drowsiness Detec...

引用

7th international conference on intelligent Computing and control systems, ICICCS 2023

作者： Elizabeth Rani, G. Sakthimohan, M. Sornalakshmi, M. Rajkumar, P. Deepika, S. Raguram, G. KGiSL Institute of Technology Department of CSBS Tamilnadu Coimbatore India Arulmigu Kalasalingam College of Arts and Science Dept of Computer Applications Tamilnadu India

ISBN: (纸本)9798350397253

It is important to identify ocular sleepiness as soon as possible to prevent accidents. More than 1.3 million people lose their lives in traffic-related incidents every year. In such incidents, the majority (78.4%) of collisions are the result of driver error, including excessive speeding, intoxication, and sleepy driving, which accounts for 21% of collisions. In order to prevent accidents, we should warn the motorist before they happen. This study uses face detection to identify the driver's face and then extract characteristics to identify their level of tiredness. The system then warns the motorist before a potential collision. © 2023 ieee.

关键词： Accidents

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Optimized Dispatching of Integrated Energy System Based on cyber-Physical-Social System Under the Influence of Electricity Price 3

Optimized Dispatching of Integrated Energy System Based on C...

引用

3rd international Signal Processing, Communications and Engineering Management conference, ISPCEM 2023

作者： Li, Jiayin Yu, Yuan Zhang, Zhen Wang, Donglai Zhao, Yan Shenyang Institute of Engineering Key Laboratory of Regional Multi- Energy System Integration and Control of Liaoning Province Shenyang China College of International Education Shenyang Institute of Engineering Shenyang China

ISBN: (纸本)9798350307023

The development and integration of information technology will make the data of the integrated energy system more real-time and transparent, which will help improve the demand-side management of Integrated Energy systems (IES). For the demand side of IES, the cyber-Physical-Social System (CPSS) architecture is constructed and analyzed. An interactive energy management method of CPSS is presented to cover supply-demand interaction and real-virtual interaction. Aiming at the social attributes of power users, the demand-side guidance control strategy mediated by network guidance information is proposed. The impact of the difference in electricity price on the consumption psychology of the users is considered. Simulations of the model are conducted. The results show that the CPSS architecture proposed in this paper can effectively improve the economic benefits of the integrated energy system and make power users actively participate in the CPSS integrated energy system. © 2023 ieee.

关键词： Real time systems

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A Fast Index-based intelligent Threat Disposal Model Search 5

A Fast Index-based Intelligent Threat Disposal Model Search

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5th ieee international conference on automation, Electronics and Electrical Engineering, AUTEEE 2022

作者： Sun, Yuyang Xu, Heng He, Chun Yuan, Xueyu School of Computer and Cyber Security Oxford Brookes College Chengdu University of Technology Chengdu China

ISBN: (纸本)9781665471978

In recent years, with the increasing popularity of the Internet, Trojan horses, viruses and other zombie programs and other backdoor programs are also increasingly concerned about the problem. In the face of constantly updated iterations of new viruses, relying on real-time updates of antivirus software alone for disposal is inefficient. Therefore, there is a need to provide a threat disposal solution to improve the efficiency of disposal of network threat events and to guarantee the removal of threats in computers in the shortest possible time to minimize losses. In this paper, we establish a more intelligent threat disposal tool model, by the user manually or according to the file directly add threats, based on the existence of the sample of key information, including process PID or name, registry entries or values, service name or service file path and file name, etc., using 'Everything' for fast Index search for local files, for the system to intelligently associate and remove threats, to improve the speed and effectiveness of the scan for the disposal of network threat events. At the same time, you can also directly carry out a rapid search traversal of the whole disk, through the Supevised learning for intelligent weighted calculation of the score to determine whether the threat file, to achieve intelligent removal, to improve the speed and accuracy of scanning. © 2022 ieee.

关键词： Network security

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IoT in Smart Homes: Enhancing Lifestyle Through intelligent automation and control 3

IoT in Smart Homes: Enhancing Lifestyle Through Intelligent ...

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3rd ieee international conference on automation and Computation, AUTOCOM 2025

作者： Sarada, W. Prashanth, K.V. Mary, A.Beneta Premkumar, K. Vijayan, Vinodh P. Radha, G. Rbvrr Women's College Department of Computer Science Narayanaguda Telangana Hyderabad India Koneru Lakshmaiah Education Foundation Department of Electronics & Communication Engineering Telangana Hyderabad India St.Joseph College of Engineering Department of Computer Science and Engineering Kancheepuram India St. Joseph College of Engineering Department of Cse Chennai India Mangalam College of Engineering Kerala Kottayam India Department of Computer Science and Engineering Rathinam Technical Campus Coimbatore India

ISBN: (纸本)9798331542375

Internet of Things (IoT) functionality integrated into smart homes has transformed residents' ways of engaging with homes, from comfort, security, and energy saving aspects. This study aims at understanding the role played by IoT based smart automation and control in enhancing people's living standards within homes. Smart homes are designed utilizing applications that centralize the control of other smart devices like smart manage thermostat, smart lighting, home security cameras and smart voice assistant. These systems allow people to automate jobs, conserve and manage energy, and design environments to people's specific needs. Moreover, the study investigates threat mechanisms of IoT in smart home with respect to data privacy issues as well as the weaknesses of devices and the possibility of cyber threats. One of the major considerations of this work is focused on ways through which IoT systems can be designed to learn about users and their requirements as well as make decisions on their own using machine learning techniques. Thus, the study shows that through IoT technology not only by providing convenience and energy-saving opportunities, but also giving homeowners control to create and establish safer and more comfortable home environment. In this research, recommendations are made for the need to bring improvement on the reliability, security, and accessibility of IoT in home automation market it has made. © 2025 ieee.

关键词： Energy efficiency

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A Review on Leveraging Reinforcement Learning for Enhanced Decision-Making in Power and Energy systems

A Review on Leveraging Reinforcement Learning for Enhanced D...

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2024 international conference on Science, technology, Engineering and Management, ICSTEM 2024

作者： Pushpalatha, N. Murugesan, M. Ravi, A. Pal Pandian, P. Kannan, K. Gunapriya, D. Department of Electrical and Electronics Engineering Sri Eshwar College of Engineering Tamilnadu Coimbatore641 202 India Department of Electrical and Electronics Engineering Karpagam Institute of Technology Tamilnadu India Department of Electrical and Electronics Engineering K.S.R College of Engineering Tamilnadu India Department of Electrical and Electronics Engineering Karpagam College of Engineering Tamilnadu India Department of Electrical and Electronics Engineering Annapoorna Engineerin College Tamilnadu India

ISBN: (纸本)9798350376913

Reinforcement learning (RL) is a potential method for tackling difficult decision-making problems in power and energy systems. This review paper presents a thorough examination of the utilization of reinforcement learning (RL) methods in many areas of power and energy systems. These areas encompass demand-side management, energy optimization, grid control, and the integration of renewable energy. Through the utilization of RL algorithms, researchers and practitioners have successfully created intelligent and adaptable solutions that improve the efficiency, dependability, and sustainability of systems. This work analyses the theoretical underpinnings of reinforcement learning (RL), investigates its implementation in several domains of power and energy systems, deliberates on the obstacles and constraints, and proposes potential avenues for further research. This paper emphasizes the significant impact of Reinforcement Learning (RL) on the future of power and energy systems. By examining case studies and current breakthroughs, it showcases how RL has the ability to revolutionize these systems, making them more efficient and sustainable. © 2024 ieee.

关键词： Reinforcement learning

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Enhanced English Learning through Integrated Interactive systems and Deep Learning Utilizing Digital Resources

Enhanced English Learning through Integrated Interactive Sys...

引用

2024 international conference on Interactive intelligent systems and Techniques, IIST 2024

作者： Hong, Yang Ningbo College of Health Sciences School of TCM and Pharmacology Health and Early Childhood Care Ningbo City China

ISBN: (纸本)9798350374421

The purpose of this study is to explore the effect of the integration of interactive systems and deep learning (DL) on English learning utilizing digital resources. This paper adopts a comparative analysis method within the experimental group (EG) and its control group (CG). Through a comparative study of EG students' use of interactive systems and DL integrated English learning platform, and CG students' use of traditional learning methods, the influence of the fusion mode is evaluated on the basis of the learning effect and learning efficiency. The experimental results indicated that the interactive systems and DL integrated learning platform can provide personalized path of learning, real-time feedback and multi-modal learning experience, which significantly improve students' learning interest and outcomes. Although EG students spend less engaged time per week on average, their learning efficiency turns out higher than CG students, with their academic performance improved accordingly. The findings demonstrate that the integration of interactive systems and DL plays a positive role in promoting English learning under the condition that digital resources are sufficiently utilized, and thus offer new perspectives and methods for the enhancement and innovation within the arena of English language education. © 2024 ieee.

关键词： Contrastive Learning

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An Improved Model Predictive control method with Luenberger Observer for Measurement Noise Suppression and Reduction of Current Ripples 3

An Improved Model Predictive Control method with Luenberger ...

引用

3rd international conference on intelligent Power and systems, ICIPS 2023

作者： Liu, Daojie Wang, Qiwu Li, Yu Gao, Jianbo Dong, Guofeng Zhi, Wenhui Sun, Yuanxiang Wang, Yongdu Laser Institute Qilu University of Technology Shandong Academy of Sciences Jinan China Technical University of Munich Munich Germany

ISBN: (纸本)9798350328691

Model predictive control (MPC) methods have gained popularity in the control of permanent magnet synchronous motors (PMSM) due to its simplicity, easy implementation, and ability to accommodate multiple constraints. However, the current ripple in traditional MPC scheme could be noticeable due to limited vector choices. Moreover, the introduction of sampling noise causes additional current ripple into the feedback loop. Nevertheless, the utilization of an analog filter introduces extra time delay that negatively affects the overall effectiveness of the MPC approach. To address these issues, this paper proposes a predictive control method that combines generalized two-vector-based model predictive current control with Luenberger-observer. The approach employs the Luenberger observer as an alternative for analog filters to suppress current sampling noise, besides the optimal vector combination is obtained by combining deadbeat predictive current control with duty cycle calculation, avoiding the need for exhaustive calculations. The simulation demonstrates that the proposed method can effectively reduce current ripple comparing to traditional MPC approaches, and the total harmonic distortion (THD) is significantly improved. ©2023 ieee.

关键词： Model predictive control

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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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Design and Simulation of a Low Phase Noise Oscillator using Substrate Integrated Waveguide without Metallic Vias 4

Design and Simulation of a Low Phase Noise Oscillator using ...

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4th international conference on intelligent Technologies, CONIT 2024

作者： Anandan, M. Rajeswari, P. Suresh Kumar, N. Divya, M. Ishwarya, R.V. Gobinath, A. Vel Tech Rangarajan Dr.Sagunthala R&d Institute of Science and Technology Department of Ece Chennai India Velammal College of Engineering and Technology Department of Ece Madurai India Rmk College of Engineering and Technology Department of Ece Chennai India Velammal College of Engineering and Technology Department of It Madurai India

ISBN: (纸本)9798350349900

This research paper presents the design and analysis of a low phase noise oscillator operating at 4.9 GHz utilizing an Improved Substrate Integrated Waveguide (SIW) with modifications involving metallic vias. The oscillator's performance is evaluated based on its S-parameters, with a focus on achieving superior impedance matching, signal transmission, and stability. The chosen frequency of operation aligns with various applications in wireless communication, radar systems, satellite communication, industrial automation, scientific research, and medical devices. The oscillator design exhibits an S11 reflection coefficient of -22.9 dB and an S21 transmission coefficient of -5.606 dB, indicating efficient power transfer and satisfactory signal transmission characteristics. These parameters reflect the oscillator's ability to maintain impedance matching while minimizing insertion loss, crucial for ensuring optimal performance in diverse applications. The paper discusses the significance of the 4.9 GHz frequency range in various real-world applications and justifies its selection based on operational requirements and industry standards. The proposed oscillator design aims to address the growing demand for reliable, low phase noise oscillators in modern communication systems and other technological domains. Through detailed analysis and simulation results, this research demonstrates the viability and effectiveness of the proposed oscillator design, contributing to advancing the field of microwave oscillator design and offering insights into optimizing phase noise performance, stability, and efficiency in SIW-based oscillator circuits with modified metallic vias. © 2024 ieee.

关键词： Phase noise

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Homomorphic Encryption for AI-Based Applications: Challenges and Opportunities 15

Homomorphic Encryption for AI-Based Applications: Challenges...

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15th international conference on Knowledge and systems Engineering, KSE 2023

作者： Hamza, Rafik Institute for International Strategy Tokyo International University 4-42-31 Higashi-Ikebukuro Toshima Tokyo170-0013 Japan

ISBN: (纸本)9798350329742

Homomorphic encryption is a technique that allows computations with encrypted data without revealing the data or requiring decryption. This technique has many potential applications in artificial intelligence (AI), where privacy and security are critical. However, implementing homomorphic encryption for AI also presents many challenges and opportunities from a software engineering perspective. In this paper, we provide a comprehensive overview of the current state of the art in homomorphic encryption for AI-based applications and discuss some important software engineering aspects of implementing homomorphic encryption solutions for AI scenarios. We review recent research challenges in applying homomorphic encryption to AI-based applications and discuss their software engineering aspects. We also compare different homomorphic encryption algorithms and libraries in terms of their security, performance, usability, interoperability, functionality, and scalability. Finally, we highlight some open challenges and future directions for research and development in this area. © 2023 ieee.

关键词： Cryptography

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