Aquila Optimizer(AO)is a recently proposed population-based optimization technique inspired by Aquila’s behavior in catching *** is applied in various applications and its numerous variants were proposed in the ***,c...
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Aquila Optimizer(AO)is a recently proposed population-based optimization technique inspired by Aquila’s behavior in catching *** is applied in various applications and its numerous variants were proposed in the ***,chaos theory has not been extensively investigated in ***,it is still not applied in the parameter estimation of electro-hydraulic *** this work,ten well-defined chaotic maps were integrated into a narrowed exploitation of AO for the development of a robust chaotic optimization *** extensive investigation of twenty-three mathematical benchmarks and ten IEEE Congress on Evolutionary Computation(CEC)functions shows that chaotic Aquila optimization techniques perform better than the baseline *** investigation is further conducted on parameter estimation of an electro-hydraulic control system,which is performed on various noise levels and shows that the proposed chaotic AO with Piecewise map(CAO6)achieves the best fitness values of and at noise levels and *** test 2.873E-05,1.014E-04,8.728E-031.300E-03,1.300E-02,1.300E-01,for repeated measures,computational analysis,and Taguchi test reflect the superiority of CAO6 against the state of the arts,demonstrating its potential for addressing various engineering optimization ***,the sensitivity to parameter tuning may limit its direct application to complex optimization scenarios.
Ovarian cancer is a global health concern due to the unavailability of an effective screening strategy and is often diagnosed at a late stage with approximately 70% of the case which reduces the survival chances of pa...
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Every country has a significant problem with road connectivity in terms of development. The road damage assessment along particular thoroughfares has revealed that governmental efforts to preserve road quality whether...
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Every country has a significant problem with road connectivity in terms of development. The road damage assessment along particular thoroughfares has revealed that governmental efforts to preserve road quality whether through construction or maintenance are substantial. Potholes are typically the first thing noticed while assessing roadway quality in developing nations such as India. Intelligent Transportation systems (ITS) have made significant strides in automation and computer vision compared to other methods such as radar, sensor bases, manual methods, etc. Recent research has shown that intelligent transport systems perform exceptionally well, especially in pothole detection and assessment. Recent advances in artificial intelligence, particularly machine learning and deep learning, have advanced robotics and automation. Modern technology has produced better results in production and cost-efficiency than traditional methods. The paper emphasizes the need for better road maintenance to decrease accidents caused by potholes on Indian roadways. Intelligent Transportation systems (ITS) face road abnormalities beyond road damages that pose safety issues. Detecting and managing surface fissures, potholes, road signs, landslides, and animal crossings are the concerns. Deep learning and artificial intelligence can improve Intelligent Transportation systems by providing a holistic approach to road concerns. technology should make transportation networks safer and more efficient. The research aims to examine the effectiveness of three deep-learning object identification frameworks (YOLOv5, YOLOv6, and YOLOv7) in detecting potholes. The results demonstrate that deep learning methods are highly effective for identifying road damage within the Intelligent Transport system, especially potholes. The dataset included in this study consists of photographs depicting potholes observed on diverse categories of roadways, namely municipal, state, and national highways. The empirical
作者:
Chaudhri, Shiv Nath
Faculty of Engineering & Technology Department of Computer Science and Design Wardha India
Organoid intelligence (OI), the next paradigm of intelligence, draws inspiration from the biological learning of organs. On the other hand, artificial intelligence (AI) draws its inspiration only from the cognitive pr...
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This study investigates the effectiveness of Retrieval-based Voice Conversion (RVC) in detecting AI-generated Arabic speech across diverse linguistic contexts. The primary research questions address whether the RVC mo...
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In the past few years, with the increase in population and health concerns, there has been a need for efficient health monitoring solutions that can help patients monitor their health consistently to be aware of any h...
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Music recommendation systems are essential due to the vast amount of music available on streaming platforms,which can overwhelm users trying to find new tracks that match their *** systems analyze users’emotional res...
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Music recommendation systems are essential due to the vast amount of music available on streaming platforms,which can overwhelm users trying to find new tracks that match their *** systems analyze users’emotional responses,listening habits,and personal preferences to provide personalized suggestions.A significant challenge they face is the“cold start”problem,where new users have no past interactions to guide *** improve user experience,these systems aimto effectively recommendmusic even to such users by considering their listening behavior and music *** paper introduces a novel music recommendation system that combines order clustering and a convolutional neural network,utilizing user comments and rankings as ***,the system organizes users into clusters based on semantic similarity,followed by the utilization of their rating similarities as input for the convolutional neural *** network then predicts ratings for unreviewed music by ***,the system analyses user music listening behaviour and music *** popularity can help to address cold start users as ***,the proposed method recommends unreviewed music based on predicted high rankings and popularity,taking into account each user’s music listening *** proposed method combines predicted high rankings and popularity by first selecting popular unreviewedmusic that themodel predicts to have the highest ratings for each *** these,the most popular tracks are prioritized,defined by metrics such as frequency of listening across *** number of recommended tracks is aligned with each user’s typical listening *** experimental findings demonstrate that the new method outperformed other classification techniques and prior recommendation systems,yielding a mean absolute error(MAE)rate and rootmean square error(RMSE)rate of approximately 0.0017,a hit rate of 82.45%,an average normalized discounted cumulative gain
Smart contracts have received increasing attention in recent years for their potential to enable decentralized and automated transactions in various fields, including finance, supply chain management, and real estate....
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As modern communication technology advances apace,the digital communication signals identification plays an important role in cognitive radio networks,the communication monitoring and management *** has become a promi...
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As modern communication technology advances apace,the digital communication signals identification plays an important role in cognitive radio networks,the communication monitoring and management *** has become a promising solution to this problem due to its powerful modeling capability,which has become a consensus in academia and ***,because of the data-dependence and inexplicability of AI models and the openness of electromagnetic space,the physical layer digital communication signals identification model is threatened by adversarial *** examples pose a common threat to AI models,where well-designed and slight perturbations added to input data can cause wrong ***,the security of AI models for the digital communication signals identification is the premise of its efficient and credible *** this paper,we first launch adversarial attacks on the end-to-end AI model for automatic modulation classifi-cation,and then we explain and present three defense mechanisms based on the adversarial *** we present more detailed adversarial indicators to evaluate attack and defense ***,a demonstration verification system is developed to show that the adversarial attack is a real threat to the digital communication signals identification model,which should be paid more attention in future research.
Pandemics like COVID-19 often cause dramatic losses of human lives and societal impacts, urging efficient and effective contact tracing, especially in indoor venues where the risk of infection is higher. In this work,...
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