This paper studies the flexible job-shop scheduling problem (FJSPT) with AGVs, which can be regarded as an extension of the flexible job-shop scheduling problem (FJSP). Based on the FJSP problem, AGVs or transfer robo...
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In this work, we develop a control algorithm for mobile manipulators manipulating an object within a leader-follower framework. Unlike existing literature, we avoid the knowledge of the object's dynamics, and only...
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ISBN:
(纸本)9798350377712;9798350377705
In this work, we develop a control algorithm for mobile manipulators manipulating an object within a leader-follower framework. Unlike existing literature, we avoid the knowledge of the object's dynamics, and only the leader is aware of the tasks to be executed by the object. The followers are primarily tasked to lift the object and maintain a desired posture while the leader manipulates the object despite its unknown dynamic parameters. We employ a stiffness-based controller for the followers, allowing set-point stabilisation with permissible flexibility and a high-gain prescribed performance controller for the leader to facilitate manipulation from the object's equilibrium state. We present simulation results with two followers and one leader KUKA youbots to validate our proposed framework.
To address the issue of low channel estimation accuracy in intelligent reflecting surface (IRS)-assisted communication systems, a channel estimation scheme based on a Channel Denoising Network (CDN) is proposed, model...
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ISBN:
(纸本)9798331530372;9798331530365
To address the issue of low channel estimation accuracy in intelligent reflecting surface (IRS)-assisted communication systems, a channel estimation scheme based on a Channel Denoising Network (CDN) is proposed, modeling the channel estimation problem as a channel noise elimination problem. First, traditional algorithms are used to perform an initial estimation of the received pilot signals, and then the estimates are fed into the channel estimation network to learn noise information and perform denoising, thereby recovering accurate channel coefficients. To enhance the network's denoising capability, an attention mechanism module and a dilated convolution module are designed to improve the extraction of primary noise information, while a feature fusion module is designed to prevent the loss of shallow features. Simulation results show that, compared to the classic DNCNN and CDRN networks, the proposed method reduces the normalized mean square error (NMSE) by an average of 2 to 2.89 dB across different signal-to-noise ratios.
The proceedings contain 11 papers. The topics discussed include: 2D image segmentation using cell like spiking neural p system;sparse modeling of dictionary learning in compressive sensing for medical images;a deep le...
The proceedings contain 11 papers. The topics discussed include: 2D image segmentation using cell like spiking neural p system;sparse modeling of dictionary learning in compressive sensing for medical images;a deep learning framework for human action recognition on YouTube videos;analysis of different loss function for designing custom CNN for traffic sign recognition;interpretable deep learning models;review of copy-move image forgery detection;selective review on adaptive normalization techniques;analysis of the professional burnout syndrome in times of pandemic by covid-19, an approach to practice using artificial intelligence;smart system model for the recruitment of teachers;and optimal plant leaf disease detection using SVM classifier with fuzzy system.
Curb following is a key technology for autonomous road sweeping vehicles. Currently, existing implementations primarily involve pre-recording waypoints during human driving and subsequently retracing them autonomously...
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ISBN:
(纸本)9798350377712;9798350377705
Curb following is a key technology for autonomous road sweeping vehicles. Currently, existing implementations primarily involve pre-recording waypoints during human driving and subsequently retracing them autonomously. Moreover, existing research related to this topic predominately focuses on curb detection for driver assistance, yet the resultant curb detection outcomes remain underutilized in the development of autonomous curb following systems. To fill this gap, this paper proposes a real-time path generation and alignment control approach to facilitate autonomous curb following. Firstly, a segmented path generation algorithm is introduced that progressively generates reference path segments while ensuring the overall continuity of the reference path. Secondly, a parameterized alignment control algorithm is developed to accurately navigate the vehicle along the planned reference path with proved stability. Real public road experiments have been conducted to validate the proposed approach. The experimental results demonstrate the efficacy of the proposed methodologies across various curb following scenarios, including common concave, convex, and straight-concave curbs, thereby showcasing the practical viability of our methods in real-world applications.
Accurate information is vital for countering misinformation, enabling informed decisions, and shaping societal outcomes. Many studies explore various methods of fake news detection. Yet, no effort has been made to sys...
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ISBN:
(纸本)9798350372113;9798350372106
Accurate information is vital for countering misinformation, enabling informed decisions, and shaping societal outcomes. Many studies explore various methods of fake news detection. Yet, no effort has been made to systematically review existing notification systems that alert users to fake news in the advocacy of accurate information. This advocacy empowers individuals to discern truth, fosters accountability, and safeguards democratic values. This paper presents our synthesis review study, conducted through the Systematic Literature Review (SLR) methodology, to assess the existing notification systems employed in various use cases, addressing this gap, and identifying research opportunities in alerting users to fake news. This study focuses on four primary technologies: cell broadcast, short message system, mobile notification, and email notification. Our study found that content challenges, frequency, communication, security, and reliability provided opportunities for content sufficiency, personalization with privacy considerations, and enhanced safety. The results of this study present a consolidated view of current notification systems for future interventions in employing methods of alerting users to fake news and identifying potential research opportunities.
The proceedings contain 115 papers. The topics discussed include: emphasized research on heart disease divination applying tree based algorithms and feature selection;visual and auditory assistant for people with vari...
ISBN:
(纸本)9781665435215
The proceedings contain 115 papers. The topics discussed include: emphasized research on heart disease divination applying tree based algorithms and feature selection;visual and auditory assistant for people with various cognitive impairments;a comparative assessment study on machine learning classifiers for cardiac arrest diagnosis and prediction;forecasting the cloud cover for agronomical function based on real time valuation;a semantic approach for fashion recommendation using logistic regression and ontologies;comparison of different lossy image compression techniques;and capsule networks based acoustic emotion recognition using mel cepstral features.
The multi-agent systems (MAS) for forest fire prevention and control are large-scale, with varied structural characteristics, leading to high complexity in management. This paper delves into the Coalition Formation (C...
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ISBN:
(纸本)9798350354416;9798350354409
The multi-agent systems (MAS) for forest fire prevention and control are large-scale, with varied structural characteristics, leading to high complexity in management. This paper delves into the Coalition Formation (CF) strategy of MAS in this scenario. Considering the characteristic and the actual utility of coalitions, as well as the multiple dimensions of constraints and optimization indicators, a model for the agent CF problem is established. A two-stage hybrid intelligent algorithm is proposed to solve the problem. The algorithm is based on the K-means Clustering algorithm, Variable Neighborhood Search (VNS) algorithm and Genetic Algorithm (GA). This method can form a high-quality feasible CF scheme, which provides support for the intelligentcontrol of fire system resources and the implementation of subsequent task allocation.
With the rapid advancement of aerospace electronics, the traditional single-satellite application paradigm is transitioning towards collaborative networking involving multiple satellites. Furthermore, the continuous i...
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To address the issue of service reliability for base stations participating in demand response programs, an adaptive two stage demand response control method is proposed. In the first stage, considering the extremely ...
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