Weather Classification in West Java using Ensemble Learning on Meteorological Data by Cynthia Nur Azzahra, Yulison Herry Chrisnanto, Gunawan Abdillah

“…Weather data from the Indonesian Meteorological, Climatological, and Geophysical Agency (BMKG) for December 2024 was used and processed through transformation, normalization, and outlier handling. …”
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Detection of Agricultural Terraces Platforms Using Machine Learning from Orthophotos and LiDAR-Based Digital Terrain Model: A Case Study in Roya Valley of Southeast France by Michael Vincent Tubog, Karine Emsellem, Stephane Bouissou

“…This study aimed to develop a semi-automatic method for detecting and mapping terraced areas using LiDAR and orthophoto data from French repositories, processed with GIS and analyzed through a Support Vector Machine (SVM) classification algorithm. …”
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Mapping the landscape of Artificial intelligence for serious games in Health: An enhanced meta review by Xiya Tao, Nicolás Sáenz-Lechón, Martina Eckert

“…This paper presents an enhanced meta-review of artificial intelligence (AI) applications in serious games (SGs) for health, focusing on adaptation, personalisation, and real-time data processing to improve rehabilitation outcomes. A systematic review methodology, following PRISMA-ScR guidelines, was employed to analyse studies from 2017 to 2025, identifying the AI algorithms most frequently used to personalise gaming experiences, improve patient engagement, and increase treatment efficacy. …”
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A Unified Denoising Framework for Restoring the LiDAR Point Cloud Geometry of Reflective Targets by Tianpeng Xie, Jingguo Zhu, Chunxiao Wang, Feng Li, Zhe Meng

“…These challenges present substantial obstacles to point cloud processing and its applications. In this paper, we propose a Unified Denoising Framework (UDF) aimed at removing noise and restoring the geometry of reflective targets. …”
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Integration and evaluation of magnetic stimulation in physiology setups. by Malte T Ahlers, Christoph T Block, Michael Winklhofer, Martin Greschner

“…Further, studies with immediate gene expression markers have identified putative brain regions involved in magnetic information processing. In contrast, very little is known about the physiology of the magnetic sense and how the magnetic field is neuronally encoded. …”
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A User-Centric Smart Library System: IoT-Driven Environmental Monitoring and ML-Based Optimization with Future Fog–Cloud Architecture by Sarkan Mammadov, Enver Kucukkulahli

“…Environmental factors—including air quality, sound, temperature, humidity, and lighting—were monitored using microcontrollers and image processing. User feedback was collected via surveys and incorporated into models trained using Logistic Regression, Decision Trees, Random Forest, Support Vector Machine (SVM), K-Nearest Neighbors (KNNs), Extreme Gradient Boosting (XGBoost), and Naive Bayes. …”
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A novel spectral transformation technique based on special functions for improved chest X-ray image classification. by Abeer Aljohani

“…All our simulation is performed in computation softwares, Matlab and Python. The image pre processing and spectral moments generation is performed in Matlab and the implementation of the classifiers is performed with python. …”
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Intelligent policy framework: Natural resource conservation, knowledge and big data analytics by Nina Xiao, Xianhe Qu

“…Although shortcomings remain in data processing and policy prediction accuracy, the methods proposed in this study offer new ideas and tools for addressing these issues.…”
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A Lightweight Deep Learning Model for Profiled SCA Based on Random Convolution Kernels by Yu Ou, Yongzhuang Wei, René Rodríguez-Aldama, Fengrong Zhang

“…In this article, a DL-SCA model is proposed by introducing a non-trained DL technique called random convolutional kernels, which allows us to extract the features of leakage like using a transformer model. The model is then processed by a classifier with an attention mechanism, which finally outputs the probability vector for the candidate keys. …”
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Machine learning framework to estimate ridership loss in public transport during external crises: case study of bus network in Stockholm by Mahsa Movaghar, Erik Jenelius, David Hunter

“…Abstract Recent technologies for recording and storing data, as well as advancements in data processing techniques, have opened up novel possibilities for urban planners to design a more optimal public transport network. …”
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Transgenic plants as a model for studying еpigenetic regulation of gene expression by T. V. Marenkova, E. V. Deineko

“…They are copied into long dsRNAs and are processed by DICER into siRNAs. siRNAs are then methylated and loaded into the effector complex, whose main component is a protein of the Argonaute family. …”
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Target Tactical Intention Recognition in Multiaircraft Cooperative Air Combat by Meng Guanglei, Zhao Runnan, Wang Biao, Zhou Mingzhe, Wang Yu, Liang Xiao

“…Finally, we learn a decision tree model on train samples processed by above two phases to classify different tactical intention. …”
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Gene expression in soft-shell clam (Mya arenaria) transmissible cancer reveals survival mechanisms during host infection and seawater transfer. by Samuel F M Hart, Fiona E S Garrett, Jesse S Kerr, Michael J Metzger

“…We observed upregulation of genes involved with genotoxic stress response, ribosome biogenesis and RNA processing, and downregulation of genes involved in tumor suppression, cell adhesion, and immune response. …”
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Effect of tool angle in nanocutting of single crystal GaN using diamond cutter by Yongqiang WANG, Hao XIA, Zhihang HU, Shuaiyang ZHANG, Shaohui YIN

“…Large-scale MD simulations are meticulously performed to model the nanoscale cutting process of single-crystal GaN using a diamond tool. …”
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Ensemble prediction modeling of flotation recovery based on machine learning by Guichun He, Mengfei Liu, Hongyu Zhao, Kaiqi Huang

“…With the rise of artificial intelligence (AI) in mineral processing, predicting the flotation indexes has attracted significant research attention. …”
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Dual‐Layer‐Per‐Array Operation Using Local Polarization Switching of Ferroelectric Tunnel FETs for Massive Neural Networks by Jae Seung Woo, Chae Lin Jung, Jin Ho Chang, Minjeong Ryu, Woo Young Choi

“…Through local polarization switching (LPS), two distinct synaptic weight sets are stored and processed by utilizing the symmetrical and independent forward and ambipolar current regions within a single FeTFET. …”
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Time series analysis of dengue incidence in Bandung City, Indonesia using a ARIMA model by Agung Sutriyawan, Martini Martini, Dwi Sutiningsih, Farid Agushybana, Nur Endah Wahyuningsih, Victor Eneojo Adamu, Hairil Akbar, Matheus Aba

“…This retrospective observational study examined dengue incidence in Bandung City from 2014 to 2023, secondary data were processed and analysed using Autoregressive Integrated Moving Average (ARIMA) model to forecast dengue incidence. …”
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The Property of the <i>Gaia</i> Celestial Reference Frame 3 (<i>Gaia</i>-CRF3) by Guangyi Liu, Sufen Guo

“…Using the Fibonacci grid, approximately 430,000 uniformly distributed sources were selected from the 5-parameter solution of <i>Gaia</i> DR3. After VSH processing, the rotation vector and glide vector were determined as <inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><mrow><mi mathvariant="bold">R</mi><mo>=</mo><mo>(</mo><mn>10.7</mn><mo>±</mo><mn>3.1</mn><mo>,</mo><mn>2.2</mn><mo>±</mo><mn>2.7</mn><mo>,</mo><mo>−</mo><mn>2.5</mn><mo>±</mo><mn>4.0</mn><mo>)</mo><mspace width="4pt"></mspace></mrow></semantics></math></inline-formula><inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><mi mathvariant="sans-serif">μ</mi></semantics></math></inline-formula>as · year⁻¹ and <inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><mrow><mi mathvariant="bold">G</mi><mo>=</mo><mo>(</mo><mn>0.3</mn><mo>±</mo><mn>3.1</mn><mo>,</mo><mo>−</mo><mn>1.2</mn><mo>±</mo><mn>2.7</mn><mo>,</mo><mo>−</mo><mn>2.5</mn><mo>±</mo><mn>4.0</mn><mo>)</mo><mspace width="4pt"></mspace></mrow></semantics></math></inline-formula><inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><mi mathvariant="sans-serif">μ</mi></semantics></math></inline-formula>as · year⁻¹, respectively. …”
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Computational Techniques for Analysis of Thermal Images of Pigs and Characterization of Heat Stress in the Rearing Environment by Maria de Fátima Araújo Alves, Héliton Pandorfi, Rodrigo Gabriel Ferreira Soares, Gledson Luiz Pontes de Almeida, Taize Calvacante Santana, Marcos Vinícius da Silva

“…The image analysis consisted of its pre-processing, followed by color segmentation to isolate the region of interest and later the extraction of the animal’s surface temperatures, from a developed algorithm and later the recognition of the comfort pattern through machine learning. …”
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Non-Volatile Reconfigurable Optical Digital Diffractive Neural Network Based on Phase Change Material by Qiaomu Hu, Jingyu Zhao, Chu Wu, Rui Zeng, Xiaobing Zhou, Shuang Zheng, Minming Zhang

“…Optical diffractive neural networks have sparked extensive research due to their low power consumption and high-speed capabilities in image processing. Here we propose and design a reconfigurable all-optical diffractive neural network structure with digital non-volatile optical neurons. …”
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