Improving deep convolutional neural networks with mixed maxout units by Hui-zhen ZHAO, Fu-xian LIU, Long-yue LI, Chang LUO

“…The maxout units have the problem of not delivering non-max features， resulting in the insufficient of pooling operation over a subspace that is composed of several linear feature mappings,when they are applied in deep convolutional neural networks.The mixed maxout (mixout) units were proposed to deal with this constrain.Firstly,the exponential probability of the feature mappings getting from different linear transformations was computed.Then,the averaging of a subspace of different feature mappings by the exponential probability was computed.Finally,the output was randomly sampled from the max feature and the mean value by the Bernoulli distribution,leading to the better utilizing of model averaging ability of dropout.The simple models and network in network models was built to evaluate the performance of mixout units.The results show that mixout units based models have better performance.…”
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PARAMETRIC SELF-EXCITATION OF CUTTING DYNAMIC SYSTEM by Vilor Lavrentyevich Zakovorotniy, Pham Thu Huong

“…The problem on stabilizing the toolpath generation relative to the workpiece taking into account the parametric self-excitation is considered. …”
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Enhanced predictive capability for chaotic dynamics by modified quantum reservoir computing by Longhan Wang, Yifan Sun, Xiangdong Zhang

“…In recent years, there has been a growing interest in approaching the problem using both classical and quantum machine learning methods. …”
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«Green» employment: the essence and genesis of the concept by N. A. Nenastev, N. N. Yashalova

“…Two key aspects of the relevant problem are touched upon: the definition of the term under consideration and the main stages of the environmental employment periodization. …”
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Stress Distribution and Transverse Vibration of Flywheel Within Linear Elastic Range by Desejo Filipeson Sozinando, Kgotso Koketso Leema, Vhahangwele Colleen Sigonde, Bernard Xavier Tchomeni, Alfayo Anyika Alugongo

“…The eigenvalues and eigenvectors, which are representative of free vibrational features, were extracted by applying finite element analysis (FEA). …”
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Advanced Prediction of Recurrent Fragility Fractures Using Large Language Models by Mohammad Alshraideh, Arafat Al-Dhaqm, Ahmad Alshammari, Abedalrahman Alshraideh, Bahaaldeen Alshraideh, Bayan Mohamed Al-Fayoumi, Maged Nasser

“…The goal of this analysis is to carry out advanced predictive analytics related to the problem of recurrent fragility fractures concerning several key features about each patient: age, sex, body mass index, physical activities, smoking status, and several others: T-score, along with biomarkers such as Vitamin D3, calcium levels, and the rest. …”
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Exploring Dynamic Hierarchical Fusion for Multi-View Clustering by Zhenshan Chen, Xuran Tian, Lizhen Gao, Gengbin Liao, Yang Shen, Kainan Zheng, Jianglin Fang

“…However, existing approaches often oversimplify the problem by treating the contribution and granularity of information from all views as uniform, neglecting the semantic richness and diversity inherent in different views. …”
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Wind Power Prediction considering Ramping Events Based on Generative Adversarial Network by Qiyue Huang

“…Taking the feature set which integrates similar feature with historical one as the input of GAN, the simulated ramping data are continuously produced through the adversarial training of the generator and discriminator, thus enriching the ramping database. …”
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Classification of offshore wind grid-connected power quality disturbances based on fast S-transform and CPO-optimized convolutional neural network. by Minan Tang, Hongjie Wang, Jiandong Qiu, Zhanglong Tao, Tong Yang

“…Then, the CPO-CNN classification model is used for feature extraction and feature selection of the time-frequency diagrams and classification of multiple power quality disturbances. …”
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High resolution remote sensing image object detection algorithm based on improved YOLOv8 by ZHANG Xia, QIAO Huanyu, CAO Feng

“…Attention-based Intra-scale feature interaction was used. Bi-directional feature pyramid network and semantics and detail infusion module were combined as the algorithm's feature fusion network. …”
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Target Detection and Image Enhancement for Underwater Environment: Research on Improving YOLOv7 by Yang Luo, Wen Feng

“…Aiming at the common low accuracy and efficiency problems in underwater target detection, this paper designs an innovative algorithm based on the YOLOv7 framework. …”
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Rough-and-Refine Model for Scene Graph Generation by Li Junliang, Lv Shirong, Li Wei

“…In the Rough Part, image features are initially extracted using convolutional neural networks and a Transformer encoder. …”
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Moral Obligation: Relational or Second-Personal? by Janis David Schaab

“…The Problem of Obligation is the problem of how to explain the features of moral obligations that distinguish them from other normative phenomena. …”
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Elective surgery: operational forecast and decision-making by N. A. Kuznetsov

“…The article is devoted to operational forecasting and decision-making features in elective surgery. The paper presents the original formula predictive of death based on the study of operational outcomes described five types of predictions. …”
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VASARI-auto: Equitable, efficient, and economical featurisation of glioma MRI by James K. Ruffle, Samia Mohinta, Kelly Pegoretti Baruteau, Rebekah Rajiah, Faith Lee, Sebastian Brandner, Parashkev Nachev, Harpreet Hyare

“…The VASARI MRI feature set is a quantitative system designed to standardise glioma imaging descriptions. …”
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LIU-NET: lightweight Inception U-Net for efficient brain tumor segmentation from multimodal 3D MRI images by Gul e Sehar Shahid, Jameel Ahmad, Chaudary Atif Raza Warraich, Amel Ksibi, Shrooq Alsenan, Arfan Arshad, Rehan Raza, Zaffar Ahmed Shaikh

“…However, effectively handling complex tumor regions requires more comprehensive and advanced strategies to overcome challenges such as computational complexity, the gradient vanishing problem, and variations in size and visual impact. …”
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Using Machine Learning for Recognition of Alzheimer’s Disease Based on Transcription Information by U. A. Vishniakou, Chu Yue Yu

“…The data used in this article is taken from the ADReSS 2020 Challenge program, which contains speech data from patients with Alzhei mer’s disease and healthy people. The problem under study is a binary classification problem. …”
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Developing a seq2seq neural network using visual attention to transform mathematical expressions from images to LaTeX. by P. A. Vyaznikov, I. D. Kotilevets

“…This problem belongs to the Image Captioning type: the neural network scans the image and, based on the extracted features, generates a description in natural language. …”
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基于峭度和小波包能量特征的齿轮箱早期故障诊断及抗噪研究 by 陈水宣, 邹俊, 易际明, 谢丹

“…It is difficult to dectect the gear fault signal in early stage because of weak intensity and strong interference.To solve this problem,a method for incipient fault diagnosis of gears is proposed based on vibration signals using kurtosis,wavelet packet energy features extraction and discriminative weighted probabilistic neural networks.The method uses the advantages of the kurtosis statistics on the impact load feature extraction method in feature extraction and reserves the merit of wavelet packet decomposition in extracting energy characteristics of various frequency bands.Meanwhile,the discriminative weight probabilistic neural network（DWPNN） is introduced to solve the problem of the scene noise pollution.The experimental results show that the method achieves a good identification of incipient faults of gears and has strong robustness against noise disturbance.…”
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A satellite navigation spoofing interference detection method based on LSTM by ZHAO Shen, HUANG Wenna, QIN Yemei, LIAO Yifei, YANG Lingling

“…Facing the problem of satellite navigation spoofing interference detection, a satellite navigation spoofing interference detection method based on LSTM was proposed. …”
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