Cost optimization model for multi-cloud network based on Kubernetes by Ming GAO, Ming LIU, Yangting CHEN, Weiming WANG

“…The cloud-native scheduling system, represented by Kubernetes, is widely used by cloud tenants in a multi-cloud environment.The problem of network observation becomes more and more serious, especially the cost of network traffic across cloud and region.In Kubernetes, the eBPF technology was introduced to collect the network data features of kernel state of operating system to solve the network observation problem, and then the network data features were modeled as QAP, a combination of heuristic and stochastic optimization was used to obtain the best near optimal solution in a real-time computing scenario.This model is superior to the Kubernetes native scheduler in the cost optimization of network resources, which is based on the scheduling strategy of computing resources only, and increases the complexity of scheduling links in a controllable range, effectively reduces the cost of network resources in a multi-cloud area deployment environment.…”
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One-stage uncertain linear optimization by Zeinab Zarea, Alireza Ghaffari-Hadigheh Ghaffari-Hadigheh

“…Uncertainty is one of the intrinsic features of natural phenomenon and optimization is not an exception. …”
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Robustness, Exploitable Relations and History: Assessing Varitel Semantics as a Hybrid Theory of Representation by Nicolás Sebastián Sánchez

“…I will conclude that internal problems beset Shea’s theory of representation. …”
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Enhancing classification efficiency in capsule networks through windowed routing: tackling gradient vanishing, dynamic routing, and computational complexity challenges by Gangqi Chen, Zhaoyong Mao, Junge Shen, Dongdong Hou

“…This prevents saturation and mitigates the gradient vanishing problem. In addition, a novel gradient-friendly network structure is developed to facilitate the extraction of complex features with deeper networks. …”
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An Approach using Skeleton-based Representations and Neural Networks for Yoga Pose Recognition by Nguyen Hai Thanh, Truong Nguyen Nhat, Pham Linh Thuy Thi, Pham Ngoc Huynh

“…Amid a rapidly developing era, people can inevitably have problems with stress, depression, pressure, or difficulty sleeping due to frequent overthinking. …”
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Data-Driven Proactive Early Warning of Grid Congestion Probability Based on Multiple Time Scales by Haobo Fu, Ruizhuo Wang, Bingxu Zhai, Yuanzhuo Li, Pengyuan Li, Rui Zhang, Haoyuan He, Siyang Liao

“…First, a multi-stage joint optimization feature selection model is constructed to capture the 12 feature sets that are most conducive to grid congestion warning from the massive grid history data containing 622 features. …”
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Features associated with the development of non-motor manifestations in Parkinson's disease Factores asociados con el desarrollo de complicaciones no motoras en la enfermedad de Pa... by Carlos Juri, Paola Viviani, Pedro Chaná

“…In conclusion, this study shows that the features related to the PD progression appear as the main risk factors associated with NMM.…”
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Novel hybrid data-driven modeling based on feature space reconstruction and multihead self-attention gated recurrent unit: applied to PM2.5 concentrations prediction by Xiaoxin Yue, Yulong Bai, Qinghe Yu, Lin Ding, Wei Song, Wenhui Liu, Huhu Ren, Qi Song

“…Abstract In response to the problem of neglecting the periodic and global characteristics of sequence data when predicting PM2.5 concentrations via machine learning models, a PM2.5 concentrations prediction model based on feature space reconstruction and multihead self-attention gated recurrent unit (FSR-MSAGRU) is proposed in this study. …”
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Development of a conceptual approach to the construction of a mathematical model of the optimal signal sequence by V. M. Samus

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Human motion state recognition based on smart phone built-in sensor by Xiaoling YIN, Xiaojiang CHEN, Qishou XIA, Juan HE, Pengyan ZHANG, Feng CHEN

“…To solve problems of low accuracy and fewer types of human motion state recognized by current smart phones,a method to do hierarchical recognition by using acceleration sensors and gravity sensors was proposed.Firstly,linear acceleration in inertial coordinate system and independent of phone direction was calculated by using the relation between acceleration and gravity acceleration.Secondly,according to the span of human motion frequency and linear acceleration vector,positions of peak and trough of footsteps were determined.Finally,feature vector of linear acceleration in time domain was extracted and human motion states were recognized hierarchically by using hierarchical support vector machine (H-SVM).The experiment shows the method can recognize six usual human motion states,while accuracy rate up to 93.37%.…”
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Development of algorithms and software for classification of nucleotide sequences by V. R. Zakirava, D. A. Syrakvash, S. V. Hileuski, P. V. Nazarov, M. M. Yatskou

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Human motion state recognition based on smart phone built-in sensor by Xiaoling YIN, Xiaojiang CHEN, Qishou XIA, Juan HE, Pengyan ZHANG, Feng CHEN

“…To solve problems of low accuracy and fewer types of human motion state recognized by current smart phones,a method to do hierarchical recognition by using acceleration sensors and gravity sensors was proposed.Firstly,linear acceleration in inertial coordinate system and independent of phone direction was calculated by using the relation between acceleration and gravity acceleration.Secondly,according to the span of human motion frequency and linear acceleration vector,positions of peak and trough of footsteps were determined.Finally,feature vector of linear acceleration in time domain was extracted and human motion states were recognized hierarchically by using hierarchical support vector machine (H-SVM).The experiment shows the method can recognize six usual human motion states,while accuracy rate up to 93.37%.…”
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Assessment of efficiency of local anesthesia for teeth extracting with use of mental anesthesia by S. Malamed and anesthesia of intraosseal part of the mental nerve from the point...

“…Nowadays pain and anesthesia problems in dentistry are still actual. More than 40 techniques of local anesthesia on the mandible known today don't solve that problem, especially in the lateral part of the mandible. …”
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The abnormal traffic detection scheme based on PCA and SSH by Zhenhui Wang, Dezhi Han, Ming Li, Han Liu, Mingming Cui

“…At the same time, PCSS also combines feature fusion and SSH to enhance the feature extraction of unclear features data, and effectively improve the detection speed and accuracy. …”
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Experimental assessment of the informativity of signs in the analysis of 2d images of bone objects in forensic examination. by A. A. Doudkin, A. A. Voronov, V. V. Ganchenko, E. E. Marushko, L. P. Podenok, A. V. Inyutin

“…The analysis carried out on basis of information content estimation to select the features that are most suitable for solving the problem of bone fractures classification. …”
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Application of SIFT operator with binocular vision fusion in Building engineering measurement by Li Chune, Deng Rui

“…Therefore, a scale invariant feature transformation engineering measurement method integrating binocular vision is proposed. …”
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Kidney Diseases Classification using Hybrid Transfer-Learning DenseNet201-Based and Random Forest Classifier by Abdalbasit Mohammed Qadir, Dana Faiq Abd

“…In this study, a hybrid technique is used by utilizing both pre-train models for feature extraction and classification using machine learning algorithms for the task of kidney disease image diagnosis. …”
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FAHPBEP: A Fuzzy Analytic Hierarchy Process Framework in Text Classification by Razieh Asgarnezhad, Sayed Monadjemi, MohammadReza Soltanaghaei

“…First, features of user's opinions are extracted based on three methods: (1) Backward Feature Selection; (2) High Correlation Filter; and (3) Low Variance Filter. …”
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3D Object Detection Based on Graph Network Fusion Sampling Strategy by LI Wenju, CHEN Zhilin, QU Jiantao, CUI Liu, CHU Wanghui, GAO Hui

“…Secondly, the K-NN algorithm is used to construct the graph of the sampled point cloud, and sub-image sampling is introduced to solve the problem of over-smooth graph convolution. Finally, the features of graph nodes are updated through feature interaction to improve the feature extraction ability of the network, thereby improving the target detection effect. …”
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Recognition of Cordyceps Based on Machine Vision and Deep Learning by Zihao Xia, Aimin Sun, Hangdong Hou, Qingfeng Song, Hongli Yang, Liyong Ma, Fang Dong

“…MRFPN is used to solve the problem of weak features. In N-CSPDarknet53, the Da-Conv module is proposed to address the background and color interference problems in shallow feature maps. …”
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