Microstructure and properties of joint of Al/Cu welded by resistance element welding with an auxiliary gasket of Ni by Dongsheng Cui, Jing Wang, Ranfeng Qiu, Hongxin Shi, Lipeng Yan

“…The grains in Al2Cu layer exhibit random crystal orientations. With the increase of welding current and the extension of welding time, the tensile shear load of the Al/Cu joint increased first and then decreased. …”
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Using geostatistical methods for evaluating organic matter reserves in fallow soils by K.G. Giniyatullin, S.S. Ryazanov, E.V. Smirnova, L.I. Latypova, L.Yu. Ryzhikh

“…In the samples taken layer by layer (every 5 cm) from the old arable horizon of fallow light gray forest soils, the content of organic matter and the bulk density were determined in order to calculate humus reserves. …”
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Named Entity Recognition Method Based on Multi-Feature Fusion by Weidong Huang, Xinhang Yu

“…The model also leverages multi-head attention for feature fusion, and the final results are decoded using a Conditional Random Field (CRF) layer. The model achieves an F1 score of 86.8383% on a collected dataset of online reviews containing eight entity categories. …”
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Spatial distribution of microplastics in Mollisols of the farmland in Northeast China: the role of field management and plastic sources by Pengke Yan, Shaoliang Zhang, Hao Xing, Sihua Yan, Xiaoguang Niu, Jiuqi Wang, Qiang Fu, Muhammad Aurangzeib

“…The abundance of MPs was higher in the 20–30 cm soil layer near the irrigation wells than in the 0–20 cm soil layer, and the spatial distribution of MPs was random in both layers. …”
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MeloDI: An Internet of Things Architecture to Evaluate Melon Quality by Means of Machine Learning Using Sensors Data and Drone Images by Angel Luis Perales Gomez, Juan Jesus Losada del Olmo, Pedro E. Lopez-de-Teruel, Alberto Ruiz, Felix J. Garcia Clemente, Andres Conesa Bueno

“…The edge layer is responsible for sending the data from sensors to the cloud layer, receiving the corrective actions from the cloud layer, and enforcing them. …”
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Feature Recognition of Human Motion Behavior Based on Depth Sequence Analysis by Guangyong Zhao

“…Here, we proposed the concept of random batch projection operators. This basically uses as much sublimitation information as possible to improve projection accuracy by randomly selecting several subdependencies as projections defined during projection. …”
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A Novel Authentication Management for the Data Security of Smart Grid by Imtiaz Parvez, Maryamossadat Aghili, Hugo Riggs, Aditya Sundararajan, Arif I. Sarwat, Anurag K. Srivastava

“…In this setting, one server handles the data encryption between the meter and control center/central database, and the other server administers the random sequence of data transmission. The second layer monitors and verifies exchanged data packets among smart meters. …”
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Recognition of field-grown tobacco plant type characteristics based on three-dimensional point cloud and ensemble learning by JIA Aobo, DONG Tianhao, ZHANG Yan, ZHU Binglin, SUN Yanguo, WU Yuanhua, SHI Yi, MA Yuntao, GUO Yan

“…According to the plant type characteristic indexes commonly used, ten phenotypic parameters such as plant height, top width, bottom width, and maximum width of leaf layer were automatically extracted based on the 3D point cloud of tobacco plant, and the calculation accuracy was evaluated based on the plant height and maximum width of leaf layer measured manually in situ in the field. …”
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Soil Organic Carbon Prediction and Mapping in Morocco Using PRISMA Hyperspectral Imagery and Meta-Learner Model by Yassine Bouslihim, Abdelkrim Bouasria, Budiman Minasny, Fabio Castaldi, Andree Mentho Nenkam, Ali El Battay, Abdelghani Chehbouni

“…The framework employs a two-layer structure of prediction models. The first layer consists of Random Forest (RF), Support Vector Regression (SVR), and Partial Least Squares Regression (PLSR). …”
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Cheating Detection in Online Exams Using Deep Learning and Machine Learning by Bahaddin Erdem, Murat Karabatak

“…In the regression analysis conducted within the scope of Scenario-1, the model we proposed to detect “cheating” behavior, which is one of the unethical learner behaviors, was found to be a 5-layer DNN model with a test performance success of 80.9%. …”
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Effects of Bedding Geometry and Cementation Strength on Shale Tensile Strength Based on Discrete Element Method by Jiong Wang, Yang Wang, Liu Yang, Tianquan Chang, Qingping Jiang

“…In addition, a 3DEC numerical simulation was used to simulate the tests, establishing shale specimen particles with random blocks. In the shale disc, uneven parallel bedding and uniform parallel bedding were set up with different loading angles and layer thicknesses to generate simulated stress-displacement curves, and the effect of layering on shale cleavage was analyzed from a mesoscopic perspective. …”
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Boundary Collisions of Slow Atoms with Two-dimensional Hexagonal Structure by A.S. Dolgov, M.S. Cherednichenko

“…Possibility and conditions of realizations of collisions with the second layer atoms omitting first ones are demonstrated.…”
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Prediction of porosity, hardness and surface roughness in additive manufactured AlSi10Mg samples. by Fatma Alamri, Imad Barsoum, Shrinivas Bojanampati, Maher Maalouf

“…This study aims to accurately predict the relative density, surface roughness and hardness of AlSi10Mg samples produced by selective laser melting regarding process parameters such as scan speed, layer thickness, laser power, and hatch distance. …”
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A soil organic carbon mapping method based on transfer learning without the use of exogenous data by Jingfeng Han, Mujie Wu, Yanlong Qi, Xiaoning Li, Xiao Chen, Jing Wang, Jinlong Zhu, Qingliang Li

“…Specifically, when predicting SOC for a given soil layer, the model is first pre-trained on data from all layers and then fine-tuned using data from the target layer. …”
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Classification of Heart Failure Using Machine Learning: A Comparative Study by Bryan Chulde-Fernández, Denisse Enríquez-Ortega, Cesar Guevara, Paulo Navas, Andrés Tirado-Espín, Paulina Vizcaíno-Imacaña, Fernando Villalba-Meneses, Carolina Cadena-Morejon, Diego Almeida-Galarraga, Patricia Acosta-Vargas

“…On the other hand, K-nearest neighbors and MLP (multi-layer perceptron) showed lower accuracy rates. These results confirm the effectiveness of the random forest method in identifying heart failure cases. …”
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Forecasting loan, deferred rate and customer segmentation in banking industry: A computational intelligence approach by Mahtab Vasheghani, Ebrahim Nazari Farokhi, Behrooz Dolatshah

“…This study proposes a novel hybrid model integrating Multi-Layer Perceptron (MLP) neural networks with Self-Adaptive Particle Swarm Optimization (PSO) and Genetic Algorithm (GA) frameworks. …”
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Residual channel attention based sample adaptation few-shot learning for hyperspectral image classification by Yuefeng Zhao, Jingqi Sun, Nannan Hu, Chengmin Zai, Yanwei Han

“…To address above issue, this paper proposes a novel Residual Channel Attention Based Sample Adaptation Few-Shot Learning for Hyperspectral Image Classification(RCASA-FSL) for hyperspectral image classification (HSIC), which can capture and enhance cross-domain dependencies through multi-layer residual connection and random-based feature recalibration. …”
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Automation of image processing through ML algorithms of GRASS GIS using embedded Scikit-Learn library of Python by Polina Lemenkova

“…Supervised learning models of GRASS GIS were tested and compared including the Gaussian Naive Bayes (GaussianNB), Multi-layer Perceptron classifier (MLPClassifier), Support Vector Machines (SVM) Classifier, and Random Forest Classifier (RF). …”
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Hybrid precoding and power allocation for mmWave NOMA systems based on time delay line arrays by Gangcan SUN, Xinli WU, Wanming HAO, Zhengyu ZHU

“…In addition, the random grouping algorithm has the worst performance because there is user interference in NOMA system,and the random grouping will make the user interference in the same cluster increase. …”
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Novel blind audio watermarking algorithm in the hybrid domain by WANG Xiang-yang1, YANG Hong-ying1, NIU Pan-pan1

“…A new robust digital audio watermarking against desynchronization attack using DWT and DCT was proposed.Firstly,the origin digital audio was segmented and then each segment was cut into two sections.Secondly,with the spa-tial watermarking technique,synchronization code was embedded into the first section.Finally,the DWT and DCT were performed on the second section,and then the watermark was embedded into the low frequency components by quantiza-tion.Experiment results show that the proposed watermarking scheme is inaudible and robust against various signal processing such as noise adding,re-sampling,re-quantization,random cropping,MPEG audio layer 3（MP3） compression,time-scale modification,frequency-scale modification.…”
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