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6861
Convolutional neural network model over encrypted data based on functional encryption
Published 2024-03-01“…Currently, homomorphic encryption, secure multi-party computation, and other encryption schemes are used to protect the privacy of sensitive data in outsourced convolutional neural network (CNN) models.However, the computational and communication overhead caused by the above schemes would reduce system efficiency.Based on the low cost of functional encryption, a new convolutional neural network model over encrypted data was constructed using functional encryption.Firstly, two algorithms based on functional encryption were designed, including inner product functional encryption and basic operation functional encryption algorithms to implement basic operations such as inner product, multiplication, and subtraction over encrypted data, reducing computational and communication costs.Secondly, a secure convolutional computation protocol and a secure loss optimization protocol were designed for each of these basic operations, which achieved ciphertext forward propagation in the convolutional layer and ciphertext backward propagation in the output layer.Finally, a secure training and classification method for the model was provided by the above secure protocols in a module-composable way, which could simultaneously protect the confidentiality of user data as well as data labels.Theoretical analysis and experimental results indicate that the proposed model can achieve CNN training and classification over encrypted data while ensuring accuracy and security.…”
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6862
Rolling Force Prediction of Hot Rolling Based on GA-MELM
Published 2019-01-01“…In this paper, a rolling force prediction method based on genetic algorithm (GA), particle swarm optimization algorithm (PSO), and multiple hidden layer extreme learning machine (MELM) is proposed, namely, PSO-GA-MELM algorithm, which takes MELM as the basic model for rolling force prediction. …”
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6863
Distribution Ratio Prediction of Major Components in 30%TBP/kerosene-HNO3 System Based on Machine Learning
Published 2025-06-01“…These models were trained based on different datasets, and their hyper-parameters were optimized using algorithms such as grid search, Bayesian optimization, and K-fold cross-validation. …”
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6864
Robust SAR Change Detection Using Hierarchical Clustering With Adaptive Parameter Tuning
Published 2025-01-01“…The methodology consists of computing a difference image using a logarithmic ratio operator, optimizing clustering parameters, computing high-change probability clusters, and generating a refined change map. …”
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6865
Design a low-noise 5GHz wideband microwave power amplifier using 90nm CMOS technology with area reduction employing an active inductor
Published 2025-07-01“…Lastly, this work illustrates how genetic algorithm optimization has drastically changed LNA design. …”
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6866
A Novel Method for Decoding Any High-Order Hidden Markov Model
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6867
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6868
Training Large Models on Heterogeneous and Geo-Distributed Resource with Constricted Networks
Published 2025-06-01“…To achieve this goal, we formulate the model partitioning problem among heterogeneous hardware and introduce a hierarchical searching algorithm to solve the optimization problem. Besides, a mixed-precision pipeline method is used to reduce the cost of inter-cluster communications. …”
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6869
The Role of Artificial Intelligence (AI) in the Future of Forestry Sector Logistics
Published 2025-06-01“…Methods: This study combines a literature review and case analysis to assess the impact of AI on forestry logistics. Machine Learning algorithms, optimization systems, and monitoring tools based on the Internet of Things (IoT) and computer vision were analyzed to assess impacts in areas such as transportation planning, inventory management, and forest monitoring. …”
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6870
Calcium dynamics in habenular astrocytes regulate active coping within behavioral transitions
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6871
Deep reinforcement learning applications and prospects in industrial scenarios
Published 2025-04-01“…Central to these systems are control algorithms, which enable the automation of operations, optimization of process parameters, and reduction of operational costs. …”
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6872
Statistical mechanics of dynamical system identification
Published 2025-08-01“…To establish this analogy, we define the hyperparameter optimization procedure as a two-level Bayesian inference problem that separates variable selection from coefficient inference and enables the computation of the posterior parameter distribution in closed form. …”
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6873
An Evolutionary Deep Reinforcement Learning-Based Framework for Efficient Anomaly Detection in Smart Power Distribution Grids
Published 2025-05-01“…Statistical <i>t</i>-tests confirm the superiority of DRL-NSABC over other algorithms, while achieving a variance of 0.00014. Moreover, DRL-NSABC demonstrates the fastest convergence, reaching near-optimal accuracy within the first 100 epochs. …”
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6874
Multi task detection method for operating status of belt conveyor based on DR-YOLOM
Published 2025-06-01“…The results show that compared to mainstream single detection algorithms, DR-YOLOM multi task detection algorithm has better comprehensive detection ability, and this algorithm can ensure high target recognition accuracy, segmentation accuracy, and appropriate inference speed with a small number of parameters. …”
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6875
A Novel Minimization Method for Sensor Deployment Via Heuristic 2-Sat Solution
Published 2018-12-01“…Other algorithms like Pseudo-Boolean SAT Solvers can also be used for the minimization purpose. …”
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6876
Local Outlier Detection Method Based on Improved K-means
Published 2024-07-01“…When there is no significant decrease in the cost function value with an increase in the number of cluster centers, the position of the “elbow” is observed to determine the optimal number of clusters. After determining the initial cluster centers and the number of clusters <italic>k</italic>, the dataset is clustered using the K-means clustering algorithm to obtain <italic>k</italic> clusters and their corresponding cluster centers. …”
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6877
An improved deep learning approach for automated detection of multiclass eye diseases
Published 2025-09-01Get full text
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6878
Processing of Polymers Stress Relaxation Curves Using Machine Learning Methods
Published 2023-12-01Get full text
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6879
Weibull-Type Incubation Period and Time of Exposure Using <i>γ</i>-Divergence
Published 2025-03-01Get full text
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6880
Trajectory Tracking Control of a Six-Degree-of-Freedom Manipulator Based on EAVOA-LADRC
Published 2025-01-01“…Therefore, a linear self-imposed perturbation parameter tuning method based on the Enhance African Vulture Optimization Algorithm (EAVOA) is proposed. In order to solve the problem that the AVOA is unbalanced between the exploration stage and the development stage, and is prone to fall into the local optimal solution, the Kent Chaos initialization, Cauchy inverse learning, optimization of the F computation, and introduction of inhibition coefficients are proposed as the improvement strategies. …”
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