Classifying Power Quality Issues in Railway Electrification Systems Using a Nonsubsampled Contourlet Transform Approach by Pampa Sinha, Kaushik Paul, I. M. Elzein, Mohamed Metwally Mahmoud, Ali M. El‐Rifaie, Wulfran Fendzi Mbasso, Ahmed M. Ewais

“…The results validate the NSCT‐MCA framework's capability to reliably detect and distinguish PQ disturbances under noisy and fluctuating railway conditions, reinforcing its suitability for real‐time deployment in modern electrification infrastructures.…”
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A prospective pharmacovigilance study in the infectious diseases unit of a tertiary care hospital by Berna Karaismailoglu, Nese Saltoglu, Ilker Inanc Balkan, Bilgul Mete, Fehmi Tabak, Recep Ozturk

“…Causality was evaluated by the Naranjo algorithm, severity was determined using the Hartwig classification, and preventability was assessed using the Schumock and Thornton scale. …”
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Estimated Disease Progression Trajectory of White Matter Disruption in Unilateral Temporal Lobe Epilepsy: A Data-Driven Machine Learning Approach by Daichi Sone, Noriko Sato, Yoko Shigemoto, Iman Beheshti, Yukio Kimura, Hiroshi Matsuda

“…Results: The SuStaIn algorithm identified a single subtype model in which the initial damage occurs in the ipsilateral uncinate fasciculus (UF), followed by damage in the forceps, superior longitudinal fasciculus (SLF), and anterior thalamic radiation (ATR). …”
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M-NIG: mobile network information gain for EEG-based epileptic seizure prediction by Yuting Meng, Yi Liu, Guanglei Wang, Huipeng Song, Yiyu Zhang, Jianbo Lu, Peiluan Li, Xu Ma

“…In this paper, we present the mobile network information gain (M-NIG) method by transforming floating time series datasets into stable network information gain, which reduces the impact of data noise, thereby improving the robustness and effectiveness of the algorithm. The method not only efficiently predicts seizures but also detects their DNB channels. …”
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Predicting the outcome of psychological treatments for borderline personality disorder and posttraumatic stress disorder: a machine learning approach to predict long-term outcome o... by Jakob Blaß, Benjamin Iffland, Philipp Herzog, Tim Kaiser, Thomas Elbert, Carolin Steuwe

“…A cross-validated genetic algorithm was used to detect baseline predictors of change in PTSD symptoms.Results: In the NET group higher education, more baseline PTSD symptoms, more traumatic experiences, fewer baseline BPD symptoms, and not taking antipsychotic medication predicted better treatment outcome. …”
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Monitoring Gypsiferous Soils by Leveraging Advanced Spaceborne Hyperspectral Imagery via Spectral Indices and a Machine Learning Approach by Najmeh Rasooli, Saham Mirzaei, Stefano Pignatti

“…PRISMA, with SVR (R² ≥ 0.83), and EnMAP, with PLSR (R² ≥ 0.85), demonstrated that hyperspectral satellites proved reliable in detecting gypsum content, yielding results comparable to ASD with detailed algorithms.…”
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Explainable light-weight deep learning pipeline for improved drought stress identification by Aswini Kumar Patra, Aswini Kumar Patra, Lingaraj Sahoo

“…Comparative analysis of existing state-of-the-art object detection algorithms reveals the superiority of our approach in achieving higher precision and accuracy. …”
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Mapping and interpreting spatio-temporal trends in vegetation restoration following mining disturbances in large-scale surface coal mining areas by Yaling Xu, Yaling Xu, Guozhu Yang, Yicong Zhang, Junting Guo, Chengye Zhang

“…The results show that the DBEST has an accuracy of 0.90 in detecting vegetation destruction and 0.78 in detecting restoration. …”
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Capabilities of breast sonotomography (automated breast volume sonography) in the evaluation of the glandular structure of the breast in the context of its cancer risk by V. E. Gazhonova, M. P. Efremova, E. M. Bachurina, E. M. Khlyustina, S. B. Potkin

“…Due to the fact that standardprojection STG scans can be compared, during mammography the procedure of STG must hold a firm place in the examination algorithm of the breast in women with its X-ray dense structure.…”
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Radiological Semiotics of Different Types of Nontuberculous Pulmonary Mycobacterioses by R. B. Amansakhedov, L. I. Dmitrieva, T. G. Smirnova, A. D. Egorova, A. E. Ergeshov

“…Slowly growing types of NTPM were detected in 62 (60.8 %) patients, and rapidly growing NTPM – in 40 (39.2 %). …”
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Combining miRNA concentrations and optimized machine-learning techniques: An effort for the tomato storage quality assessment in the agriculture 4.0 framework by Seyed Mohammad Samadi, Keyvan Asefpour Vakilian, Seyed Mohamad Javidan

“…However, the RF, with hyperparameters optimized by the genetic algorithm, was able to improve the R2 values of the prediction of storage temperature and period to 0.96 and 0.89. …”
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Modeling the Relationship Between Radon Anomalies and Seismic Activity Using Artificial Neural Networks and Statistical Methods by Kostadin Yotov, Emil Hadzhikolev, Stanka Hadzhikoleva

“…The paper presents an approach for detecting anomalies in radon concentration in seismically active areas. …”
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Distributed RL-Based Resource Allocation and Task Offloading for Vehicular Edge of Things Computing by Ghada Afifi, Bassem Mokhtar

“…Furthermore, we conduct hardware-based field test experiments to verify the effectiveness of our proposed algorithm to satisfy the stringent real-time latency requirements for various vehicular applications. …”
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Application of Naive Bayes and Forward Chaining Methods in a Web-Based Expert System for Stunting Diagnosis in Toddlers by Ayu Fadilah, Raissa Amanda Putri

“…This method is a probability-based algorithm that is used to classify the possibility of a condition based on existing symptoms. …”
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Joint Optimization of the 3D Model and 6D Pose for Monocular Pose Estimation by Liangchao Guo, Lin Chen, Qiufu Wang, Zhuo Zhang, Xiaoliang Sun

“…The 2D landmarks are detected in the input image by a trained neural network. …”
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Investigation of the ecology of winter plankton of Lake Baikal using complex instrumental methods by E. Yu. Naumova, T. P. Rzhepka, M. M. Makarov, A. S. Olshukov, K. M. Kucher, M. Z. Magomedova, E. S. Troitskaya

“…The obtained field data will make it possible to further improve the pattern recognition algorithm in the software of the holographic installation for the specific conditions of Lake Baikal. …”
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Analyzing the Impact of Binaural Beats on Anxiety Levels by a New Method Based on Denoised Harmonic Subtraction and Transient Temporal Feature Extraction by Devika Rankhambe, Bharati Sanjay Ainapure, Bhargav Appasani, Avireni Srinivasulu, Nicu Bizon

“…Next, an Intrinsic Harmonic Subtraction Network is employed, utilizing the Attentive Weighted Least Mean Square (AW-LMS) algorithm to capture nonlinear summation and resonant coupling effects, effectively eliminating the misinterpretation of brain rhythms. …”
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Improving Fall Classification Accuracy of Multi-Input Models Using Three-Axis Accelerometer and Heart Rate Variability Data by Seunghui Kim, Jae Eun Ko, Seungbin Baek, Daechang Kim, Sungmin Kim

“…To solve this problem, a fall prevention algorithm using an acceleration sensor has been developed, and research is being conducted to enable continuous monitoring using a Holter electrocardiograph. …”
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Peran Artificial Intelligence terhadap Praktik Greenwashing dalam Sustainability Report: Systematic Literature Review by Abim Wafirli, Provita Wijayanti, Lisa Kartikasari, Muhammad Ja'far Shodiq

“…Although AI is promising, challenges remain, such as algorithm ethics and infrastructure readiness.…”
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Multidimensional proteomics analysis of amniotic fluid to provide insight into the mechanisms of idiopathic preterm birth. by Irina A Buhimschi, Guomao Zhao, Victor A Rosenberg, Sonya Abdel-Razeq, Stephen Thung, Catalin S Buhimschi

“…Inflammation and/or bleeding proteomic patterns were detected in 32% (92/286) of the SELDI tracings. In the remaining tracings, a hierarchical algorithm was applied based on descriptors quantifying similarity/dissimilarity among proteomic fingerprints. …”
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