An Improved Stochastic Configuration Networks With Compact Structure and Parameter Adaptation by Sanyi Li, Hongyu Guan, Peng Liu, Weichao Yue, Qian Wang

“…Stochastic Configuration Networks (SCNs) perform well in machine learning and data mining tasks in complex data environments. …”
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The first geospatial dataset of irrigated fields (2020–2024) in Vojvodina (Serbia) by Mirjana Radulović, Miljana Marković, Sanja Brdar, Ioannis Athanasiadis, Gordan Mimić

“…This study’s goal is to give accessibility to our dataset which further can be explored and used for building or fine-tuning machine learning and deep learning models for the automatic detection of irrigated fields using satellite imagery.…”
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Disorder-induced enhancement of lithium-ion transport in solid-state electrolytes by Zhimin Chen, Tao Du, N. M. Anoop Krishnan, Yuanzheng Yue, Morten M. Smedskjaer

“…We further establish bridges between dynamical characteristics, local structural features, and atomic rearrangements by applying a machine learning-based structure fingerprint termed “softness”. …”
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An Improved Deep Belief Network IDS on IoT-Based Network for Traffic Systems by Rayeesa Malik, Yashwant Singh, Zakir Ahmad Sheikh, Pooja Anand, Pradeep Kumar Singh, Tewabe Chekole Workneh

“…Hence, there is a need to use an intelligent mechanism based on machine learning (ML) and deep learning (DL), to detect attacks. …”
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Predictors of evacuation behavior: dataset on respondents’ route choice and web interaction by Dajana Snopková, Martin Tancoš, Lukáš Herman, Vojtěch Juřík

“…It supports the development of models to predict human behavior in emergencies using machine learning and predictive modeling and is accessible for both academic and commercial use.…”
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Toward cultural interpretability: A linguistic anthropological framework for describing and evaluating large language models by Graham M Jones, Shai Satran, Arvind Satyanarayan

“…This article proposes a new integration of linguistic anthropology and machine learning (ML) around convergent interests in both the underpinnings of language and making language technologies more socially responsible. …”
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A Low-Power General Matrix Multiplication Accelerator with Sparse Weight-and-Output Stationary Dataflow by Peng Liu, Yu Wang

“…General matrix multiplication (GEMM) in machine learning involves massive computation and data movement, which restricts its deployment on resource-constrained devices. …”
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A New Type of Eye Movement Model Based on Recurrent Neural Networks for Simulating the Gaze Behavior of Human Reading by Xiaoming Wang, Xinbo Zhao, Jinchang Ren

“…Experimental results are then presented to demonstrate that the proposed model can achieve similar prediction accuracy while requiring fewer features than current machine learning models.…”
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A hybrid Genetic Algorithm and Fuzzy Logic approach to ergonomic design of workstations in metal casting operations by Intan Berlianty, Irwan Soejanto, Indun Titisariwati, Favian Ersanta Andhika Putra, Wahyu Tri Utami, Mohamad Kamil Insani

“…Future research could further enhance the system by incorporating machine learning for improved predictive capabilities and expanded optimization of ergonomic parameters.…”
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A multi-dimensional decision framework based on the XGBoost algorithm and the constrained parametric approach by Xinxin Wang, BingBing Zhang, Zeshui Xu, Ming Li, Marinko Skare

“…Under the framework, XGBoost algorithm, one of the machine learning methods, is conducted to capture the importance of attributes by using the historical data, and further calculate the attribute weights. …”
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A Survey on Sensor Selection and Placement for Connected and Automated Mobility by Mehmet Kiraz, Fikret Sivrikaya, Sahin Albayrak

“…The findings of this article also highlight numerous challenges in creating a universal framework, the lack of application of novel machine learning methods, and the complexity of modeling multi-sensor settings.…”
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An improved spatially downscaled solar-induced chlorophyll fluorescence dataset from the TROPOMI product by Siyuan Chen, Liangyun Liu, Lichun Sui, Xinjie Liu, Yan Ma

“…Compared with a machine learning (ML) SIF product and OSIF, TroDSIF can better reproduce the OSIF signals with higher R2, lower root mean square error (RMSE), and nearly zero residuals at different latitudes. …”
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Comparative analysis of regression algorithms for drug response prediction using GDSC dataset by Soojung Ha, Juho Park, Kyuri Jo

“…Prediction of drug response is recently being performed using machine learning technology. However, high-throughput sequencing data produces thousands of features per patient. …”
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Towards automated recipe genre classification using semi-supervised learning. by Nazmus Sakib, G M Shahariar, Md Mohsinul Kabir, Md Kamrul Hasan, Hasan Mahmud

“…Furthermore, we have demonstrated traditional machine learning, deep learning and pre-trained language models to classify the recipes into their corresponding genre and achieved an overall accuracy of 98.6%. …”
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A Comprehensive Review of Dropout Prediction Methods Based on Multivariate Analysed Features of MOOC Platforms by Saad Alghamdi, Ben Soh, Alice Li

“…This review also discusses the use of advanced models based on machine learning, deep learning, and meta-heuristics approaches to improve course completion rates, optimise learning outcomes, and provide personalised educational experiences.…”
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A New Air Quality Prediction Framework for Airports Developed with a Hybrid Supervised Learning Method by Yong Tian, Weifang Huang, Bojia Ye, Minhao Yang

“…This article proposes a new framework with a combination of the standard assessment procedure and machine learning methods for fast and accurate prediction of air quality in airports. …”
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A Trusted Federated Learning Method Based on Consortium Blockchain by Xiaojun Yin, Xijun Wu, Xinming Zhang

“…Federated learning (FL) has gained significant attention in distributed machine learning due to its ability to protect data privacy while enabling model training across decentralized data sources. …”
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Intelligent and Smart Irrigation System Using Edge Computing and IoT by M. Safdar Munir, Imran Sarwar Bajwa, Amna Ashraf, Waheed Anwar, Rubina Rashid

“…The decision from the ontology and the sensor values collectively become the source of the final decision which is the result of a machine learning algorithm (KNN). Moreover, an edge server is introduced between the main IoT server and the GSM module. …”
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Identifying industrial buildings as a spatial resource for sustainable urban regeneration in high-density post-industrial metropolitan in Asia by Miao Sun, Tan Qin, Yuanxiao Kuang, Jianchang Lv

“…This paper develops a machine learning method for identifying industrial buildings from satellite aerial images. …”
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Towards cross-platform interoperability for machine-assisted text annotation by Richard Eckart de Castilho, Nancy Ide, Jin-Dong Kim, Jan-Christoph Klie, Keith Suderman

“…This methodology requires the ability to freely combine resources from different document repositories, access a wide array of NLP tools that automatically annotate corpora for various linguistic phenomena, and use a sophisticated annotation editor that enables interactive manual annotation coupled with on-the-fly machine learning. We consider three independently developed platforms, each of which utilizes a different model for representing annotations over text, and each of which performs a different role in the process.…”
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