We theoretically investigate chaotic dynamics in an optomechanical system composed of a whispering-gallery-mode(WGM)microresonator and a *** find that tuning the optical phase using a phase shifter and modifying the c...
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We theoretically investigate chaotic dynamics in an optomechanical system composed of a whispering-gallery-mode(WGM)microresonator and a *** find that tuning the optical phase using a phase shifter and modifying the coupling strength via a unidirectional waveguide(IWG)can induce chaotic *** underlying reason for this phenomenon is that adjusting the phase and coupling strength via the phase shifter and IWG bring the system close to an exceptional point(EP),where field localization dynamically enhances the optomechanical nonlinearity,leading to the generation of chaotic *** addition,due to the sensitivity of chaos to phase in the vicinity of the EP,we propose a theoretical scheme to measure the optical phase perturbations using *** work may offer an alternative approach to chaos generation with current experimental technology and provide theoretical guidance for optical signal processing and chaotic secure communication.
The utilization of digital picture search and retrieval has grown substantially in numerous fields for different purposes during the last decade,owing to the continuing advances in image processing and computer vision...
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The utilization of digital picture search and retrieval has grown substantially in numerous fields for different purposes during the last decade,owing to the continuing advances in image processing and computer vision *** multiple real-life applications,for example,social media,content-based face picture retrieval is a well-invested technique for large-scale databases,where there is a significant necessity for reliable retrieval capabilities enabling quick search in a vast number of *** widely employ faces for recognizing and identifying ***,face recognition through formal or personal pictures is increasingly used in various real-life applications,such as helping crime investigators retrieve matching images from face image databases to identify victims and ***,such face image retrieval becomes more challenging in large-scale databases,where traditional vision-based face analysis requires ample additional storage space than the raw face images already occupied to store extracted lengthy feature vectors and takes much longer to process and match thousands of face *** work mainly contributes to enhancing face image retrieval performance in large-scale databases using hash codes inferred by locality-sensitive hashing(LSH)for facial hard and soft biometrics as(Hard BioHash)and(Soft BioHash),respectively,to be used as a search input for retrieving the top-k matching ***,we propose the multi-biometric score-level fusion of both face hard and soft BioHashes(Hard-Soft BioHash Fusion)for further augmented face image *** experimental outcomes applied on the Labeled Faces in the Wild(LFW)dataset and the related attributes dataset(LFW-attributes),demonstrate that the retrieval performance of the suggested fusion approach(Hard-Soft BioHash Fusion)significantly improved the retrieval performance compared to solely using Hard BioHash or Soft BioHash in isolation,where the suggested method provides an augmented
Autism Spectrum Disorder (ASD) is a complex neurodevelopmental condition that impacts social communication, behavior, and cognitive functions. Early detection of autism is crucial for timely intervention, which can si...
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Pancreatic cancer poses a significant challenge in early detection and treatment due to its malignant nature within the digestive tract. Recent studies, such as those conducted by the Pancreatic Cancer Action Network,...
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The Internet of Things (IoT), which enables seamless connectivity and effective data exchange between physical items and digital systems, has completely changed the way we interact with our surroundings. This study ev...
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Federated learning(FL)is an emerging privacy-preserving distributed computing paradigm,enabling numerous clients to collaboratively train machine learning models without the necessity of transmitting clients’private ...
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Federated learning(FL)is an emerging privacy-preserving distributed computing paradigm,enabling numerous clients to collaboratively train machine learning models without the necessity of transmitting clients’private datasets to the central *** most existing research where the local datasets of clients are assumed to be unchanged over time throughout the whole FL process,our study addresses such scenarios in this paper where clients’datasets need to be updated periodically,and the server can incentivize clients to employ as fresh as possible datasets for local model *** primary objective is to design a client selection strategy to minimize the loss of the global model for FL loss within a constrained *** this end,we introduce the concept of“Age of Information”(AoI)to quantitatively assess the freshness of local datasets and conduct a theoretical analysis of the convergence bound in our AoI-aware FL *** on the convergence bound,we further formulate our problem as a restless multi-armed bandit(RMAB)***,we relax the RMAB problem and apply the Lagrangian Dual approach to decouple it into multiple ***,we propose a Whittle’s Index Based Client Selection(WICS)algorithm to determine the set of selected *** addition,comprehensive simulations substantiate that the proposed algorithm can effectively reduce training loss and enhance the learning accuracy compared with some state-of-the-art methods.
Facial expression recognition is a challenging task when neural network is applied to pattern recognition. Most of the current recognition research is based on single source facial data, which generally has the disadv...
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This work proposes a novel and improved Butterfly Optimization Algorithm (BOA), known as LQBOA, to solve BOA’s inherent limitations. The LQBOA uses Lagrange interpolation and simple quadratic interpolation techniques...
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Among hyperspectral imaging technologies, interferometric spectral imaging is widely used in remote sening due to advantages of large luminous flux and high resolution. However, with complicated mechanism, interferome...
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Among hyperspectral imaging technologies, interferometric spectral imaging is widely used in remote sening due to advantages of large luminous flux and high resolution. However, with complicated mechanism, interferometric imaging faces the impact of multi-stage degradation. Most exsiting interferometric spectrum reconstruction methods are based on tradition model-based framework with multiple steps, showing poor efficiency and restricted performance. Thus, we propose an interferometric spectrum reconstruction method based on degradation synthesis and deep ***, based on imaging mechanism, we proposed an mathematical model of interferometric imaging to analyse the degradation components as noises and trends during imaging. The model consists of three stages, namely instrument degradation, sensing degradation, and signal-independent degradation process. Then, we designed calibration-based method to estimate parameters in the model, of which the results are used for synthesizing realistic dataset for learning-based *** addition, we proposed a dual-stage interferogram spectrum reconstruction framework, which supports pre-training and integration of denoising DNNs. Experiments exhibits the reliability of our degradation model and synthesized data, and the effectiveness of the proposed reconstruction method.
Capacitive pressure sensors (CPSs) have attracted considerable interest due to their high sensitivity, low energy consumption, and potential for miniaturization, making them suitable for applications in automotive sys...
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