A Hybrid Deep Learning Approach for Improved Detection and Prediction of Brain Stroke by Gayatri Thakre, Rohini Raut, Chetan Puri, Prateek Verma

“…Traditional diagnostic procedures, such as manually interpreting clinical images, are time consuming and error prone. This research investigates the use of hybrid deep learning models, such as recurrent neural networks (RNNs), long short-term memory (LSTM), and convolutional neural networks (CNNs), to improve stroke prediction accuracy. …”
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Prediction of Settlement Due to Shield TBM Tunneling Based on Three-Dimensional Numerical Analysis by Ji-Seok Yun, Han-Kyu Yoo, Sung-Pil Hwang, Woo-Seok Kim, Han-Eol Kim

“…Furthermore, the prediction model showed high agreement with the field data, yielding a prediction error of 8.25%. This study emphasizes the applicability of verified numerical modeling for accurately predicting ground settlement in Shield TBM tunneling and provides a reliable approach for settlement prediction under varying construction conditions.…”
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Mill+, an intuitive tool for simulating the milling process: Vibrations, cutting forces and surface quality control by Gorka Urbikain-Pelayo, Daniel Olvera-Trejo, Luis Norberto López de Lacalle, Alex Elías-Zuñiga, Itziar Cabanes

“…Machining is a highly technological manufacturing process for producing high-added value components across various engineering applications ranging from automotive to aerospace and medical devices. …”
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Moisture Evaluation of Oil-Immersed Insulation in Bushings Based on Frequency Domain Spectroscopy and Grey Relational Analysis by Xianhao Fan, Sheng Li, Tengyue Sun, Yiyi Zhang, Jiefeng Liu

“…The results showed that the average relative (absolute error) is less than 14.6% (0.17%). …”
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The Design, Creation, Implementation, and Study of a New Dataset Suitable for Non-Intrusive Load Monitoring by Carlos Rodriguez-Navarro, Francisco Portillo, Francisco G. Montoya, Alfredo Alcayde

“…The proposed approach contributes to a standardized and scalable NILM framework, facilitating real-world applications in energy management and smart grid optimization.…”
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Dairy Chain Safety in the Context of Antibiotic Residues—Current Status of Confirmatory Liquid Chromatography Methods: A Review by Sandra Dluhošová, Klára Bartáková, Lenka Vorlová, Pavlína Navrátilová, Oto Hanuš, Eva Samková

“…To capture the latest developments in the field and the relatively recent aforementioned trends, this review focuses on papers investigating antimicrobial residues in milk that were published between 2015 and 2024, providing an overview of emerging techniques applicable to antibiotic residue detection in milk samples.…”
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CoPhiEditor: The DSL-Based DSE Methodology within the ERC Advanced Grant 885222-GreekSchools by Simone Zenzaro, Angelo Mario Del Grosso, Federico Boschetti, Graziano Ranocchia

“…Furthermore, its extensible and domain-agnostic architecture broadens its applicability across various scholarly editing contexts. …”
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Hybrid Indoor Human Localization System for Addressing the Issue of RSS Variation in Fingerprinting by Mekuanint Agegnehu Bitew, Rong-Shue Hsiao, Hsin-Piao Lin, Ding-Bing Lin

“…Indoor localization is used in many applications like security, healthcare, location based services, and social networking. …”
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Artificial Intelligence-Based Transmission Frequency Prediction in Cable Systems Using Electromagnetic Field Data by Abbas Seif, Hamid Radmanesh, Amir Ahmarinejad, Ahmad Ali Ashrafian

“…This work advances applications in electrical and telecommunications engineering, emphasizing scalable, intelligent solutions for electromagnetic analysis.…”
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Design and Verification of a Massive MIMO Channel Emulator for 5G/6G System Performance Testing by Jianghong Xie, Zhengbo Jiang, Jingxin Liu, Jiacheng Yu, Siheng Luo, Chong Guo, Zhang-Cheng Hao, Wei Hong

“…The emulator demonstrates excellent RF performance, achieving a phase coherence of ±2° and an error vector magnitude (EVM) of 0.65% when utilizing the common LO configuration. …”
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Multivariate Method Based on Raman Spectroscopy for Quantification of Dipyrone in Oral Solutions by Luciana Lopes Guimarães, Letícia Parada Moreira, Bárbara Faria Lourenço, Walber Toma, Renato Amaro Zângaro, Marcos Tadeu Tavares Pacheco, Landulfo Silveira

“…Commercial formulations had predicted concentrations with a difference below 5.0% compared to the label concentration, indicating the applicability of Raman spectroscopy for quality control in the final product.…”
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Determining Non-Dimensional Group of Parameters Governing the Prediction of Penetration Depth and Holding Capacity of Drag Embedment Anchors Using Linear Regression by Mojtaba Olyasani, Hamed Azimi, Hodjat Shiri

“…Regarding offshore mooring design and geotechnical engineering applications, the proposed LR models offered a practical and efficient approach to estimating DEA performance across various seabed conditions.…”
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First-passage approach to optimizing perturbations for improved training of machine learning models by Sagi Meir, Tommer D Keidar, Shlomi Reuveni, Barak Hirshberg

“…Machine learning models have become indispensable tools in applications across the physical sciences. Their training is often time-consuming, vastly exceeding the inference timescales. …”
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Smart photonic wristband for pulse wave monitoring by Renfei Kuang, Zhuo Wang, Lin Ma, Heng Wang, Qingming Chen, Arnaldo Leal Junior, Santosh Kumar, Xiaoli Li, Carlos Marques, Rui Min

“…Our AI-assisted smart photonic wristband has potential applications for clinical treatment of cardiovascular diseases and home monitoring, paving the way for medical Internet of Things-enabled smart systems.…”
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An all integer-based spiking neural network with dynamic threshold adaptation by Chenglong Zou, Chenglong Zou, Xiaoxin Cui, Shuo Feng, Guang Chen, Yi Zhong, Zhenhui Dai, Yuan Wang

“…It aims to eliminate the spiking synchronization error commonly occurred in many traditional ANN2SNN conversion works. …”
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Quantitative evaluation of increased overpressure from tectonic compression stress and its significance—A case study from the Dabei Gas Field in Kuqa Depression by Gang Wang, Chang-Yu Fan, Zhen-Liang Wang, Hai-Jun Yang, Qing-Kuan Wu

“…This clarifies the stress–strain–pressure coupling process, and provides a quantitative evaluation model with high applicability and accuracy. Applied to the Dabei Gas Field, the results show: (a) IOTCS ranges from 80 to 220 MPa with a 6% relative error compared to aqueous inclusions pressures, indicating high accuracy; (b) IOTCS limits shear fracture development, leading to high fracture density in low fluid pressure zones; and (c) IOTCS increases the driving force for hydrocarbon migration by 1.8 to 2.1 times compared to non-IOTCS conditions.…”
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Model-agnostic meta-learning-based region-adaptive parameter adjustment scheme for influenza forecasting by Jaeuk Moon, Yoona Noh, Sungwoo Park, Eenjun Hwang

“…We also show the robust forecasting accuracy of our scheme and demonstrate its applicability by performing zero-shot COVID-19 forecasting.…”
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A Low-Cost Automated Test Column to Estimate Soil Hydraulic Characteristics in Unsaturated Porous Media by J. Salas-García, J. Garfias, R. Martel, L. Bibiano-Cruz

“…An extension to the applicability of this system could be successfully used in low-budget projects in large-scale field experiments, which may be correlated with resistivity changes.…”
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Determination of sugar in tangerines by fluorescence with an Improved partial least squares (PLS) algorithm by Lei Liu, Chunzhong Li, Haiyi Bian, Ahmed N Abdalla, Hua Yao, Wen Li

“…The result approved validation dataset’s R -square and root-mean-square error were 0.9777 and 0.002992, respectively. These findings open the door to broader applications in the citrus industry and beyond, with the potential for automating the analysis process and improving overall quality control.…”
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Predicting the Onset Date of Cucumber Powdery Mildew Based on Growing Degree Days and Leaf Wetness Duration in Greenhouse Environment by Min Son, Haejun Jeong, Jin-Yong Jung, Jiwon Park, Jiyoon Park, Hoyoung Park, Jonghan Yoon, Se-Hoon Jung, Chun-Bo Sim, Kwang-Hyung Kim, Sook-Young Park

“…As a result, we successfully simulated the symptom onset date with a margin of error of 5.5 days across two validation trials in 2023 and 2024. …”
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