Detecting schizophrenia, bipolar disorder, psychosis vulnerability and major depressive disorder from 5 minutes of online-collected speech by Julianna Olah, Win Lee Edwin Wong, Atta-ul Raheem Rana Chaudhry, Omar Mena, Sunny X. Tang

“…Our study aimed to (1) identify an optimal assessment approach for the online and remote collection of speech, in the context of assessing the psychosis spectrum and evaluate whether a fully automated, speech-based machine learning (ML) pipeline can discriminate among different conditions on the schizophrenia-bipolar spectrum (SSD-BD-SPE), help-seeking comparison subjects (MDD), and healthy controls (HC) at varying layers of analysis and diagnostic complexity. …”
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Analysis of Energy Consumption in a Federated Learning-Based Zero-Touch Network by Urooj Yousuf Khan, Musharaf Ali Talpur, Umme Laila, Samar Raza Talpur

“…A pivotal point in Zero-Touch Networks is the selection of an optimal machine-learning algorithm. One such algorithm is Federated learning which relies on local updates of a global model. …”
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Design and Implementation of Local Threshold Segmentation Based on FPGA by Shangshang Gao, Yuanyuan Wang, Zhaofeng Chen, Feng Zhou, Rugang Wang, Naihong Guo

“…In the process of the development of image processing technology, image segmentation is a very important image processing technology in the field of machine vision, pedestrian detection, medical imaging, and so on. …”
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A Comparative Study of Image Representation for Roller Bearing Fault Diagnosis Using Pretrained Networks by M. Arun Balaji, S. Naveen Venkatesh, V. Sugumaran, K. I. Ramachandran

“…The findings highlight the importance of selecting and optimizing deep learning models for a specific maintenance application and contribute valuable insights for researchers and practitioners in reliability engineering.…”
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Calculating Rock Joint Frequency in TBM Excavation Through Binocular Vision and Segmentation Techniques by Jingwei Xu, Haochen Sun, Hongmei Wang, Yaxu Wang, Yan Zhu, Peng Jiang

“…In tunnel boring machine (TBM) construction, the strength and integrity of the surrounding rock are pivotal factors affecting operational safety and efficiency. …”
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Mid-Infrared Spectroscopy for Coffee Variety Identification: Comparison of Pattern Recognition Methods by Chu Zhang, Chang Wang, Fei Liu, Yong He

“…These methods were classified as highly effective methods (soft independent modelling of class analogy, support vector machine, back propagation neural network, radial basis function neural network, extreme learning machine, and relevance vector machine), methods of medium effectiveness (partial least squares-discrimination analysis, K nearest neighbors, and random forest), and methods of low effectiveness (Naive Bayes classifier) according to the classification accuracy for coffee variety identification.…”
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Enhancing maize above-ground biomass estimation through multispectral, digital and LiDAR fusion on UAV platforms by Ziheng Feng, Zheqing Yang, Liunan Suo, Ke Wu, Zhiyao Ma, Haiyan Zhang, Jianzhao Duan, Wei Feng

“…The influence of SL on soil water dynamics, nutrient transport, and dry matter accumulation patterns was systematically analyzed. Finally, a machine learning (ML) model for maize AGB estimation with multimodal data fusion was constructed using Partial Least Squares (PLSR), Support Vector Machine (SVM), and Random Forest (RF). …”
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Basketball teaching methods based on 3D-Convolutional neural network by Chao Huang, Xian Wu

“…The study optimized the single-shot multibox detector algorithm by introducing the focal loss function and other means. …”
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A novel adversarial deep TSK fuzzy classifier with its inverse-free fast training by Limin Mao, Hangming Shi, Yongxin Chou, Jinliang Cong, Mingli Lu, Zekang Bian, Suhang Gu

“…However, conventional deep learning is a fully deterministic model that has difficulty reducing data uncertainty while shedding no light on model transparency. …”
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Routization Problem Complicated by the Dependence of Costs Functions and «Current» Restrictions From the Tasks List by A. G Chentsov, A. A. Chentsov

“…The used algorithm is realized on a personal computer; the results of its application are illustrated by the modelling examples.…”
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Online Prediction of Milling Inner Hole Roundness Error Based on Accurate SSEM Value Extraction by Zhenbang Hu, Gedong Jiang, Xuesong Mei, Xialun Yun, Yun Zhang

“…For online prediction of the workpiece roundness error (WRE) during machining, a predictive model based on correlation analysis and a proportional method is proposed according to the spindle synchronous error motion (SSEM) by three-probe method testing. …”
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UHVDC Transmission Line Fault Identification Method Based on Generalized Regression Neural Network by XIE Jia, LIU Feng, KE Yanguo, YIN Zhen, RUAN Wei, YAO Jinming

“…Secondly, the chaos quantum particle swarm optimization (CQPSO) algorithm is used to optimize the parameters of the generalized regression neural network, form an ideal network model based on the principle of the lowest fitness function, and better learn the fault characteristics of the ultra-high voltage DC transmission line. …”
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Estimating Winter Wheat Canopy Chlorophyll Content Through the Integration of Unmanned Aerial Vehicle Spectral and Textural Insights by Huiling Miao, Rui Zhang, Zhenghua Song, Qingrui Chang

“…Finally, the optimal model was utilized for spatial mapping. The results provided the following indications: (1) Red-edge vegetation indices (RIs) and TIs were key to estimating RCCC. …”
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Comparative analysis of sugarcane harvesters: Effects on waste management across varieties and field ages by Hadi Saadi, Mahmoud Ghasemi-Nejad-Raeini, Molood Behnia, Nima Shahbazi, Ali Kaab, Ashkan Jalilian

“…The results indicate a clear relationship between harvester type and waste production, with the H-8000 model consistently resulting in less waste than the H-7000 model. …”
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Extraction of typical oyster pile columns in the Maowei Sea, Beibu Gulf, based on unmanned aerial vehicle laser point cloud orthophotos by Jinze Du, Jinze Du, Meiqin Huang, Zhenjun Kang, Zhenjun Kang, Zhenjun Kang, Yichao Tian, Yichao Tian, Yichao Tian, Jin Tao, Jin Tao, Qiang Zhang, Qiang Zhang, Yutong Xie, Yutong Xie, Yutong Xie, Jinying Mo, Jinying Mo, LiYan Huang, LiYan Huang, Yusheng Feng, Yusheng Feng

“…The results demonstrate that: 1) By comparing three machine learning models and integrating the LiDAR point cloud oyster pile column height model (OPCHM) into the S3 scenario, the convolutional neural network (CNN) attains an impressive overall classification accuracy (OA) of 96.54% and a Kappa coefficient of 0.9593, significantly enhancing and optimizing the CNN’s predictive accuracy for classification tasks; 2) In comparison with conventional machine learning algorithms, deep learning exhibits remarkable feature extraction capability.…”
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Deep Learning Hybrid Architecture Based on Vision Transformer for Phase Analysis of Moiré Fringes by Dajie Yu, Junbo Liu, Chuan Jin, Yuyang Li, Kairui Zhang, Ji Zhou

“…Additionally, the model has been optimized in structure to more efficiently extract phase information from complex Moiré fringe patterns. …”
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Mechanical Behaviors of Electrostatic Microbeams with Nonideal Supports by Yunxia Chang, Qichang Zhang, Wei Wang, Jianxin Han

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THE EXPERIMRNTAL RESEARCH ON SINGLE POINT INCREMENTAL FORMING U-SHAPED METAL BELLOWS by HOU XiaoLi, LI Yan, SHI Xun, YANG MingShun, YUAN QiLong

“…The reliability of the optimization results is verified by simulation and experimental results. …”
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Simulation studies of a high-repetition-rate electron-driven surface muon beamline at SHINE by Fangchao Liu, Yusuke Takeuchi, Si Chen, Siyuan Chen, Kim Siang Khaw, Meng Lyu, Ziwen Pan, Dong Wang, Jiangtao Wang, Liang Wang, Wenzhen Xu

“…This high-repetition-rate pulsed muon beam, with its ideal time structure, represents a unique and pioneering effort once constructed. It serves as a model for building cost-effective muon sources at existing electron machines with GeV electron energies. …”
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Contribution to the research of Anthropometric measurements and comparison of body proportions in the student population in Bangladesh by Md Eanamul Haque Nizam, Emeritus Darko Ujevic, Ayub Nabi Khan

“…The model demonstrated superior performance, achieving an R2 score of 0.647 where the mean squared error value is 18.62, surpassing both linear regression and random forest models. …”
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