Federated and ensemble learning framework with optimized feature selection for heart disease detection by Olfa Hrizi, Karim Gasmi, Abdulrahman Alyami, Adel Alkhalil, Ibrahim Alrashdi, Ali Alqazzaz, Lassaad Ben Ammar, Manel Mrabet, Alameen E.M. Abdalrahman, Samia Yahyaoui

“…Predictive models for early identification of heart disease must be precise and efficient because it is a major worldwide health concern. …”
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Evaluation of Coalbed Methane Content by Using Kernel Extreme Learning Machine and Geophysical Logging Data by Jianhong Guo, Zhansong Zhang, Guangshan Guo, Hang Xiao, Linqi Zhu, Chaomo Zhang, Xiao Tang, Xueqing Zhou, Yanan Zhang, Can Wang

“…Accurate evaluation of coalbed methane (CBM) content plays a momentous role in the identification and efficient development of favorable exploitation blocks of CBM resources, but there are still many technical challenges in the exploration and development of onshore CBM fields. …”
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Verification of the method for classifying the technical state of a turboshaft engine fuel regulator in the space of operational process parameters under factory test conditions by Ihor Ohanian, Sergiy Yepifanov

“…It was determined that the method demonstrates high efficiency in most operational modes; however, its accuracy depends on the degree of correlation between the diagnosed structural parameters and the precision of the mathematical model identification. …”
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Vegetation classification in a subtropical region with Sentinel-2 time series data and deep learning by Ming Zhang, Dengqiu Li, Guiying Li, Dengsheng Lu

“…This research is valuable for us to choose appropriate data structures and efficient deep learning models for vegetation classification.…”
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Integration of UAV Remote Sensing and Machine Learning for Taro Blight Monitoring by Yushuai Wang, Yuxin Chen, Zhou Shu, Shaolong Zhu, Weijun Zhang, Tao Liu, Chengming Sun

“…An unmanned aerial vehicle (UAV) was utilized to capture spectral images of natural taro fields, facilitating the efficient monitoring of taro blight. Field survey data were integrated with these images to develop a model for monitoring taro blight severity. …”
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A Precise Detection Method for Tomato Fruit Ripeness and Picking Points in Complex Environments by Xinfa Wang, Xuan Wen, Yi Li, Chenfan Du, Duokuo Zhang, Chengxiu Sun, Bihua Chen

“…Accurate identification of tomato ripeness and precise detection of picking points is the key to realizing automated picking. …”
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Red Raspberry Maturity Detection Based on Multi-Module Optimized YOLOv11n and Its Application in Field and Greenhouse Environments by Rongxiang Luo, Xue Ding, Jinliang Wang

“…In order to achieve accurate and rapid identification of red raspberry fruits in the complex environments of fields and greenhouses, this study proposes a new red raspberry maturity detection model based on YOLOv11n. …”
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A two-stage deep learning architecture for detection global coastal and offshore submesoscale ocean eddy using SDGSAT-1 multispectral imagery by Linghui Xia, Baoxiang Huang, Ruijiao Li, Ge Chen

“…Correspondingly, SDGSAT-1 multispectral data from November 2021 to December 2022 were carried out to construct two submesoscale eddy datasets for training and testing each stage model. The union validation of multiple metrics demonstrates that the proposed OED model and its stage models achieve state-of-the-art (SOTA) performance, especially in optically complex coastal and offshore waters. …”
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Rice Disease Detection: TLI-YOLO Innovative Approach for Enhanced Detection and Mobile Compatibility by Zhuqi Li, Wangyu Wu, Bingcai Wei, Hao Li, Jingbo Zhan, Songtao Deng, Jian Wang

“…However, existing rice disease identification techniques face many challenges, such as low training efficiency, insufficient model accuracy, incompatibility with mobile devices, and the need for a large number of training datasets. …”
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Research on Gear Surface Damage Recognition Based on Small Sample Deep Learning by Wang Xiaopeng, Hua Hongpeng, Lu Changqing, Peng Kun, Zhong Yuan, Wu Biqiong

“…It is extremely important to improve the efficiency and accuracy of gear surface damage identification. …”
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Application and realization of key technologies in China railway e-ticketing system by Xinghua Shan, Zhiqiang Zhang, Fei Ning, Shida Li, Linlin Dai

“…Design/methodology/approach – Research in key technologies is conducted including synchronization technique in distributed heterogeneous database system, the grid-oriented passenger service record (PSR) data storage model, efficient access to massive PSR data under high concurrency condition, the linkage between face recognition service platforms and various terminals in large scenarios, and two-factor authentication of the e-ticket identification code based on the key and the user identity information. …”
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Beyond amplitude: Phase integration in bird vocalization recognition with MHAResNet by Jiangjian Xie, Zhulin Hao, Chunhe Hu, Changchun Zhang, Junguo Zhang

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THE RELATIONSHIP BETWEEN MANAGEMENT OF FLOATING CAPITAL AND PERFORMANCE OF THE COMPANY by V. V. Nazarova, S. P. Glebov

“…In order to simulate the relationship between the management of the floating capital and the company’s performance, the authors used the panel regression method to improve the efficiency of the estimates. In order to obtain applied conclusions, the authors built models with fixed and random effects and used cluster standard errors to reduce the impact of data autocorrelation. …”
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Classification of edible vegetable oils based on three-dimensional fluorescence spectroscopy and ISSA-SVM by ZHANG Jing, QI Guohong, CHEN Jingzhao, CAO Xiaoli, LI Lili

“…ObjectiveTo improve the classification accuracy of edible vegetable oils, an identification model based on three-dimensional fluorescence spectroscopy and ISSA-SVM was established.MethodsCombining the feature information of three-dimensional fluorescence spectroscopy, an improved sparrow search algorithm was used to optimize the parameters of the SVM model, constructing an edible vegetable oil identification method that integrates the characteristics of three-dimensional fluorescence spectroscopy information and the ISSA-SVM model.ResultsCompared with the SVM model, GA-SVM model, PSO-SVM model, and SSA-SVM model, the classification accuracy of the ISSA-SVM model for edible vegetable oils reached 100%.ConclusionThe ISSA-SVM model has higher convergence efficiency, system stability, and the ability to avoid local optimal solutions, which can effectively cope with complex and variable sample classification tasks.…”
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Enhancing mosquito classification through self-supervised learning by Ratana Charoenpanyakul, Veerayuth Kittichai, Songpol Eiamsamang, Patchara Sriwichai, Natchapon Pinetsuksai, Kaung Myat Naing, Teerawat Tongloy, Siridech Boonsang, Santhad Chuwongin

“…This study introduces a self-supervised learning-based image classification model using the Bootstrap Your Own Latent (BYOL) algorithm, designed to enhance mosquito species identification efficiently. …”
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Finger Knuckle Print classification: Leveraging vision Mamba for low complexity and high accuracy by Chiron Bang, Ali Salem Altaher, Ahmed Altaher, Hawraa Moamin, Thamer Alshammari, Basmh Alkanjr, Hasan Altaher, Mohammed G. Al-Jassani, Hanqi Zhuang

“…ViM achieved an impressive accuracy of 99.1%, outperforming other models such as AlexNet (96.2%), SCNN (98.3%), and EfficientNet (98.0%), highlighting its superior capability in FKP classification. …”
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A Damage Classification Approach for Structural Health Monitoring Using Machine Learning by Diego Tibaduiza, Miguel Ángel Torres-Arredondo, Jaime Vitola, Maribel Anaya, Francesc Pozo

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Research Framework and Anticipated Results of Key Technologies for Distributed Certificate-less Network Identity Systems by ZHANG Xiaosong, CAO Sheng, LU Tianbo, YANG Kun, GUI Xun, XIE Guotao, NIU Weina

“…Lastly, in large-scale distributed IoT identity authentication applications and validation, a lightweight public key identification model based on national cryptographic standards was designed, achieving breakthroughs in GBA protocol integration and AI-driven certificate-less authentication, with evaluation tools developed to simulate IoT networks with at least 300 nodes.Conclusions and ProspectsThis research aims to address challenges such as the design of authentication architectures, efficient key management, acceleration of access processes, and parallel execution of contracts, ensuring functionalities such as data allocation on demand and anonymous identity verification, while guaranteeing user privacy, security, and supporting dynamic collaborative computing for massive terminals. …”
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DeepBiteNet: A Lightweight Ensemble Framework for Multiclass Bug Bite Classification Using Image-Based Deep Learning by Doston Khasanov, Halimjon Khujamatov, Muksimova Shakhnoza, Mirjamol Abdullaev, Temur Toshtemirov, Shahzoda Anarova, Cheolwon Lee, Heung-Seok Jeon

“…Our model aggregates three semantically diverse convolutional neural networks—DenseNet121, EfficientNet-B0, and MobileNetV3-Small—using a stacked meta-classifier designed to aggregate their predicted outcomes into an integrated, discriminatively strong output. …”
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Case Report: Cognitive Behavioral Therapy Of A Patient With Pathological Gambling by S. Olga Guriz, Aslı Ekinci, M. Hakan Türkçapar

“…Rational Emotive Behavior Therapy seems to be efficient in the treatment of pathological gambling especially in coping with emotional problems and feeling of discomfort through making up a holistic cognitive, emotional, and behavioral model. …”
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