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  • Multiple Images Steganography of JPEG Images Based on Optimal Payload Distribution
  • Abstract Multiple images steganography refers to hiding secret messages in multiple natural images to minimize the leakage of secret messages during transmission. Currently, the main multiple images steganography algorithms mainly distribute the payloads as sparsely as possible in multiple cover images to improve the detection error rate of stego images. In order to enable the payloads to be accurately and efficiently distributed in each cover image, this paper proposes a multiple images steganography for JPEG images based on optimal payload redistribution. Firstly, the algorithm uses the principle of dynamic programming to redistribute the payloads of the cover images to reduce the…
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  • Topp-Leone Odd Fréchet Generated Family of Distributions with Applications to COVID-19 Data Sets
  • Abstract Recent studies have pointed out the potential of the odd Fréchet family (or class) of continuous distributions in fitting data of all kinds. In this article, we propose an extension of this family through the so-called “Topp-Leone strategy”, aiming to improve its overall flexibility by adding a shape parameter. The main objective is to offer original distributions with modifiable properties, from which adaptive and pliant statistical models can be derived. For the new family, these aspects are illustrated by the means of comprehensive mathematical and numerical results. In particular, we emphasize a special distribution with three parameters based on the…
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  • Research on Trajectory Tracking Method of Redundant Manipulator Based on PSO Algorithm Optimization
  • Abstract Aiming at the problem that the trajectory tracking performance of redundant manipulator corresponding to the target position is difficult to optimize, the trajectory tracking method of redundant manipulator based on PSO algorithm optimization is studied. The kinematic diagram of redundant manipulator is created, to derive the equation of motion trajectory of redundant manipulator end. Pseudo inverse Jacobi matrix is used to solve the problem of manipulator redundancy. Based on the tracking ellipse of redundant manipulator, the tracking shape of redundant manipulator is determined with the overall tracking index as the second index, and the optimization method of tracking index is…
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  •   Views:369       Downloads:173        Download PDF
  • Robust Design Optimization and Improvement by Metamodel
  • Abstract The robust design optimization (RDO) is an effective method to improve product performance with uncertainty factors. The robust optimal solution should be not only satisfied the probabilistic constraints but also less sensitive to the variation of design variables. There are some important issues in RDO, such as how to judge robustness, deal with multi-objective problem and black-box situation. In this paper, two criteria are proposed to judge the deterministic optimal solution whether satisfies robustness requirment. The robustness measure based on maximum entropy is proposed. Weighted sum method is improved to deal with the objective function, and the basic framework of…
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  •   Views:424       Downloads:189        Download PDF
  • A Multi-View Gait Recognition Method Using Deep Convolutional Neural Network and Channel Attention Mechanism
  • Abstract In many existing multi-view gait recognition methods based on images or video sequences, gait sequences are usually used to superimpose and synthesize images and construct energy-like template. However, information may be lost during the process of compositing image and capture EMG signals. Errors and the recognition accuracy may be introduced and affected respectively by some factors such as period detection. To better solve the problems, a multi-view gait recognition method using deep convolutional neural network and channel attention mechanism is proposed. Firstly, the sliding time window method is used to capture EMG signals. Then, the back-propagation learning algorithm is used…
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  •   Views:372       Downloads:167        Download PDF
  • Importance of Features Selection, Attributes Selection, Challenges and Future Directions for Medical Imaging Data: A Review
  • Abstract In the area of pattern recognition and machine learning, features play a key role in prediction. The famous applications of features are medical imaging, image classification, and name a few more. With the exponential growth of information investments in medical data repositories and health service provision, medical institutions are collecting large volumes of data. These data repositories contain details information essential to support medical diagnostic decisions and also improve patient care quality. On the other hand, this growth also made it difficult to comprehend and utilize data for various purposes. The results of imaging data can become biased because of…
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  •   Views:106       Downloads:72        Download PDF
  • An Emotion Analysis Method Using Multi-Channel Convolution Neural Network in Social Networks
  • Abstract As an interdisciplinary comprehensive subject involving multidisciplinary knowledge, emotional analysis has become a hot topic in psychology, health medicine and computer science. It has a high comprehensive and practical application value. Emotion research based on the social network is a relatively new topic in the field of psychology and medical health research. The text emotion analysis of college students also has an important research significance for the emotional state of students at a certain time or a certain period, so as to understand their normal state, abnormal state and the reason of state change from the information they wrote. In…
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  •   Views:84       Downloads:76        Download PDF
  • Least-Square Support Vector Machine and Wavelet Selection for Hearing Loss Identi
  • Abstract Hearing loss (HL) is a kind of common illness, which can significantly reduce the quality of life. For example, HL often results in mishearing, misunderstanding, and communication problems. Therefore, it is necessary to provide early diagnosis and timely treatment for HL. This study investigated the advantages and disadvantages of three classical machine learning methods: multilayer perceptron (MLP), support vector machine (SVM), and least-square support vector machine (LS-SVM) approach and made a further optimization of the LS-SVM model via wavelet entropy. The investigation illustrated that themultilayer perceptron is a shallowneural network,while the least square support vector machine uses hinge loss function…
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  • Effect of Hole Density and Confining Pressure on Mechanical Behavior of Porous Specimens: An Insight from Discrete Element Modeling
  • Abstract Hole-like defects are very common in natural rock or coal mass, and play an important role in the failure and mechanical behaviors of rock or coal mass. In this research, multi-holed coal specimens are constructed numerically and calibrated based on UDEC-GBM models. Then, the strength, deformation and failure behavior of the porous specimens are analyzed, with consideration of hole density (P) and confining pressure (σ3). The simulation results are highly consistent with those available experiment results, and show that the compressive strength decreases exponentially with the increasing hole density. The strength loss is mainly caused by the reduction of cohesion…
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  •   Views:435       Downloads:176        Download PDF
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