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检索条件"任意字段=International Multi-Conference in Computer Science and Computer Engineering"

共 584311 条记录，以下是4271-4280 订阅

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Invariant Set Analysis and Control Synthesis of multi-Equilibrium Switched Systems under Control Constraints 13

Invariant Set Analysis and Control Synthesis of Multi-Equili...

引用

13th international conference on Intelligent Control and Information Processing, ICICIP 2025

作者： Han, Yuejiang Zhang, Lixian Ding, Yihang Dong, Yifei Liang, Ye School of Astronautics Harbin Institute of Technology Harbin China College of Computer and Control Engineering Northeast Forestry University Harbin China

ISBN: (纸本)9798331516147

This paper investigates the problems of invariant set analysis and control synthesis for multi-equilibrium switched systems under control constraints. A control strategy based on the invariant set method is proposed, accompanied by criteria formulated as linear matrix inequalities, ensuring that the state remains within the mode-dependent invariant sets. Furthermore, considering the control constraints in practical scenarios, a multi-equilibrium switched controller with control constraints (MESCC controller) is designed. Compared to existing works, the proposed method incorporates mode-dependent dwell time conditions and mode-dependent invariant sets, thereby offering enhanced design flexibility. An example of an aero-engine control system is presented to demonstrate the effectiveness and potential of the theoretical results. © 2025 IEEE.

关键词： Control system synthesis

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Probabilistic Markow Modeling with Trading Strategies for Efficient Stock Market Predictions 1

Probabilistic Markow Modeling with Trading Strategies for Ef...

引用

1st international conference on Pioneering Developments in computer science and Digital Technologies, IC2SDT 2024

作者： Yadav, Pramod Kumar Altaf, Hunain National Institue of Technology Srinagar Department of Computer Science and Engineering Srinagar India

ISBN: (纸本)9798350365016

Financial markets are considered the most chaotic and complex dynamic systems as factors responsible for the fluctuation of share prices are numerous and plentiful. Owing to the advancements in the field of machine learning and artificial intelligence the predictive nature of the stocks has been a topic of debate among researchers since then. From factors such as historical prices to technical indicators, the stock prediction needs a strategy that simply combines the present status with the indicators of the past time series data. In this work, we proposed a Hidden Markov strategy with the ability to determine the future state based on the present state and further combine these hidden states with the traditional moving average crossover strategy to develop a combined signal to classify the stock and depict timely buy, hold, or sell signals. Results indicate an improvement of the Sharpe ratio along with the higher returns when the combined signal is being used to make decisions. © 2024 IEEE.

关键词： Hidden Markov models

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Design of Traceability Platform for Animal Husbandry Products Supply Chain Based on RFID Internet of Things

Design of Traceability Platform for Animal Husbandry Product...

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2024 international conference on Smart Systems for Electrical, Electronics, Communication and computer engineering, ICSSEEC 2024

作者： Dawood, Mustafa Nazar Adile, Mohaned Fahidhil, Eay Hassan, Ahmed R. Shukur Ali, Hanan Mahmood Noori, Mohammed Adnan, Myasar Mundher Al-Turath University College Computer Technologies Engineering Baghdad Iraq Al-farahidi University Medical Instruments Engineering Techniques Baghdad Iraq Al-Kunooze University College Technical Computer EngineeringDepartment Basrah Iraq National University of Science and Technology Department of Medical Devices Engineering Technologies Nasiriyah Dhi Qar Iraq AI-Kitab University Department of Computer Engineering Technologies Kirkuk Iraq Al-Maamoun University College Computer Technology Engineering Baghdad Iraq College of Technical Engineering The Islamic University Department of Computers Techniques Engineering Iraq

ISBN: (纸本)9798350378177

According to the current needs of the meat vendor market monitoring, the key aims of the organization are to optimize data collection for the reproduction process, enhance the slaughter method, track sales data, and continuously improve meat products and overall effectiveness. Animal Husbandry Products using a supply chain (AHP-SC) system is proposed in this article. Radio frequency identification (RFID), information synchronization, and base integration are part of the architecture. The use of RFID has been seamlessly incorporated into the system. The smart terminal gathers vital data about bovine and mutton animals in real-time, including information on breeding, slaughter, and the supply chain. Data synchronization is accomplished by combining and duplicating technology amongst networked mobile devices. Finally, the required traceability for making informed selections of bovine and bovine animals has been developed throughout the production process, from slaughtering, breeding, and processing to the supply chain network. © 2024 IEEE.

关键词： Animal Husbandry Products Internet of Things RFID Supply Chain Traceability

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Maestro: A Robust multi-Head Attention Enhanced CNN Architecture for Heat-Induced Stress Recognition Using EEG Signals 8

Maestro: A Robust Multi-Head Attention Enhanced CNN Architec...

引用

8th IEEE international conference on Computational System and Information Technology for Sustainable Solutions, CSITSS 2024

作者： De, Sagnik Pavuluri, Sreenija Sayyad, Amaan Gupta, Anil Kumar Institute of Radio Physics and Electronics University of Calcutta Kolkata India Department of Computer Science Engineering Gvpce AP Visakhapatnam India Department of Computer Engineering Meswcoe Maharashtra Pune India Hpc I&e Group Centre for Development of Advanced Computing Maharashtra Pune India

ISBN: (纸本)9798331505462

Heat-induced stress impacts various physiological parameters in the body. Elevated temperature can cause tachycardia (an increase in heart rate), as the body attempts to dissipate heat through vasodilation, leading to dehydration and electrolyte imbalances. In addition, the hypothalamus triggers sweating in order to regulate body temperature;that can culminate in fluid and electrolyte loss, which could impact metabolic processes and blood pressure. A prolonged exposure to high temperatures can cause heat stroke, heat exhaustion, and other ailments including organ damage and systemic dysfunction. Existing electroencephalography (EEG)-based heat-induced stress detection often considers the entire EEG frequency range (delta to gamma), concealing redundant and lossy information and increasing the likelihood of false detection rates. To address the limitations of conventional handcrafted feature engineering approaches in heat stress detection, this paper introduces MAESTRO, a novel model comprising two blocks: Convolutional and multi-head Attention. The Convolutional block extracts precise information from individual EEG frequency bands, while the multi-head Attention block enhances feature representation through attention mechanism. Finally, two dense layers are employed to classify heat stress into three classes: Acute, Chronic, and Control. The proposed framework undergoes validation using EEG data obtained from 40 rodents in a simulated laboratory environment. The outcomes illustrate the viability of the method in classifying heat-induced stress, yielding remarkable results for overall accuracy, precision, recall, and F1 score of 98.88 %, 98.54 %, 98. 67 %, and 98.60 %, respectively. © 2024 IEEE.

关键词： Blood pressure

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An EEG-Driven Framework for Emotion Recognition During Gameplay 5

An EEG-Driven Framework for Emotion Recognition During Gamep...

引用

5th international conference on Advancements in Computational sciences, ICACS 2024

作者： Shahzad, Khurram Ali, Zohaib Rauf, Usman Rehman, Anees Ur Khan, Sheharyar Noorani, Sadam Hussain Comsat University Department of Elect & Comp Engineering Islamabad Pakistan Bahria University Department of Computer Science Islamabad Pakistan University of Engineering & Technology Department of Computer Engineering Taxila Pakistan

ISBN: (纸本)9798350394764

Gaming transcends mere entertainment, serving as a unique realm to explore human emotions. This research utilizes Brain-computer Interface (BCI) technology, specifically Electroencephalogram (EEG) signals, to unravel player emotions. Pioneering an innovative approach, our study decodes and interprets emotions exhibited during gaming experiences. Through meticulous analysis, we demonstrate the efficacy of EEG signals in revealing emotional states. Findings illuminate the dynamic interplay between the brain and gaming environments. Leveraging datasets like GAMEEMO, our study employs various data and feature extraction processes to detect emotions (boring, calm, horror, funny) with a accuracy of 98.21%, achieved by the Random Forest model. © 2024 IEEE.

关键词： Electroencephalography

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A Review on Meta-Learning: How Artificial Intelligence and Machine Learning Can Learn to Adapt Quickly 3

A Review on Meta-Learning: How Artificial Intelligence and M...

引用

3rd international conference on Electronics and Renewable Systems, ICEARS 2025

作者： Khadse, Shrikant Gourshettiwar, Palash Pawar, Adesh Faculty of Engineering and Technology Wardha442001 India Faculty of Engineering and Technology Department of Computer Science and Medical Engineering Wardha442001 India Department of Computer Science and Medical Engineering Maharashtra Wardha442001 India

ISBN: (纸本)9798331509675

Meta-learning aims to create Artificial Intelligence (AI) systems that can adapt to new tasks and improve their performance over time without extensive retraining. The advent of meta-learning paradigms has fundamentally changed how Artificial Intelligence (AI) and Machine Learning (ML) are handled, constantly reshaping these fields. Research study reviews the broad field of meta-learning, highlighting its critical function in bridging the AI-ML divide to improve adaptability. The study starts with a review of past developments, following the development of meta-learning algorithms and their underpinning theories. The historical view lays the groundwork for understanding the course of this dynamic regulation, spanning from early efforts in probabilistic program induction to modern discoveries in model-agnostic meta-learning. The study explores multiple meta-learning applications in AI and ML, revealing how they affect financial forecasting, computer vision, natural language processing, autonomous cars, health informatics, robotics, and personalized recommendation systems. When seen from the perspective of adaptive intelligence, meta-learning may be effectively applied to conditions with limited data, hyperparameter optimization, few-shot learning, and quick adaption in reinforcement learning settings. © 2025 IEEE.

关键词： Contrastive Learning

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Orientation Accuracy Test and Installation Error Calibration Technology for Vehicle Inertial Navigation System 4

Orientation Accuracy Test and Installation Error Calibration...

引用

4th international conference on Electronic Information engineering and computer science, EIECS 2024

作者： Xie, Jietao Wu, Juan Zang, Yunda College of Systems Engineering National University of Defense Technology China Test and Training Research Center Baicheng Ordnance Test Center of China Jinzhou China

ISBN: (纸本)9798331531409

Aiming at the lack of inertial navigation system (INS) orientation accuracy test and error calibration means in the user's field environment, we systematically sort out and analyze the orientation accuracy indexes of INS, put forward the orientation accuracy test, static north-seeking accuracy test, dynamic north-seeking accuracy test, dynamic orientation holding accuracy test method, put forward the practical method of vehicle INS installation error calibration, and develop the software system. The proposed method and system can meet the field testing and calibration needs. © 2024 IEEE.

关键词： Inertial navigation systems

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Real-Time Semantic Segmentation Model Combining CNN and Transformer to Detect Belt Runout 5

Real-Time Semantic Segmentation Model Combining CNN and Tran...

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5th international conference on Machine Learning and computer Application, ICMLCA 2024

作者： Shen, Yuan Ma, Xiaokun College of Electronic Information Engineering Anhui University China College of Electronic Information and Integrated Circuits Hefei Normal University China

ISBN: (纸本)9798331530334

Along with the development of science and technology, the belt conveyor has been applied on a large scale. Belt runout is one of the common faults of belt conveyors. To address the problem of belt deflection detection, this paper constructs a binary belt segmentation dataset BSG containing two categories of belt and background and designs a real-time semantic segmentation-based belt deflection detection method. Transformer has excellent global modeling capability but lacks spatial location bias, and CNN has spatial location bias and has advantages in local information extraction. In this paper, a real-time semantic segmentation network LCTNet combining CNN and Transfomer is proposed. LCTNet contains the shallow feature extraction module LSBM, the deep feature extraction module LDBM, and an efficient Transfomer Block (SET). Experiments on the CamVid dataset as well as the BSG dataset show that the LCTNet balances accuracy and real-time performance in a good way. © 2024 IEEE.

关键词： Semantic Segmentation

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Machine Learning-Based Approach for Hand Gesture Recognition

Machine Learning-Based Approach for Hand Gesture Recognition

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2023 international conference on Disruptive Technologies, ICDT 2023

作者： Deepika, M. Choudhary, Shilpa Kumar, Sandeep Srinivas, Kodi Neil Gogte Institute of Technology Department of Computer Science & Engineering Hyderabad India Koneru Lakshmaiah Educational Foundation Department of Computer Science & Engineering Andhra Pradesh Vaddeswaram India

ISBN: (纸本)9798350323887

computer vision and Machine Learning are used to comprehend and extract information from photos and videos. This paper examines how computer vision and machine learning are used to recognize hand gestures, which are the most common form of everyday communication. The proposed method intends to demonstrate how to utilize computer vision and machine learning to identify motions and apply these techniques using Python and OpenCV. These allow us to distinguish hand gestures made in the air. The output, or the computer webcam stream, is displayed on the output screen. © 2023 IEEE.

关键词： computer vision

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Kinematic Analysis of Tractor-Trailer Mobile Robot on a Sphere

Kinematic Analysis of Tractor-Trailer Mobile Robot on a Sphe...

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2023 international conference on Intelligent Communication and computer engineering, ICICCE 2023

作者： Chen, K. Deng, J. Zhang, W.Z. School of Mechanical Engineering Inner Mongolia University of Techn-ology Inner Mongolia Key Laboratory of Special Service Intelligent Robotics China

ISBN: (纸本)9798350395617

In order to study the motion control problem of a Tractor-Trailer Mobile Robot (TTWMR) on a spherical container, the kinematics characteristics of the robot on the sphere were analyzed. The position and orientation of a TTWMR system are described using a generalized coordinate vector composed of six variables. Based on the holonomic and nonholonomic constraints imposed on the system, a velocity transfer matrix for adjacent robots in a wheeled multi-body robot system is proposed, and a kinematics model for the motion of a TTWMR on a sphere is established. The kinematic model is theoretically simulated using Matlab and virtually simulated using Adams for robot prototypes. By comparing the results of the theoretical simulation with the virtual simulation, the accuracy of the model is validated, providing a theoretical foundation for the control of trailer mobile robots on a sphere and practical insights for their practical application. © 2023 IEEE.

关键词： MATLAB

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