Artificial intelligence driven mental health diagnosis based on physiological signals by P.R. Naregalkar, A.A. Shinde, M.V. Patil

“…The machine learning algorithms, like Decision tree and kernel support vector machine, are employed for dope classification tasks. …”
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Transparent memory tests with even repeating addresses for storage devices by V. N. Yarmolik, I. M. Mrozek, V. A. Levantsevich, D. V. Demenkovets

“…The basis of new metrics is the distance D(A(j), pA) determined by the difference between the indices of repeated addresses A(j) in the sequence pA. …”
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Development and validation of survival prediction tools in early and late onset colorectal cancer patients by Wanling Li, Jinshan Liu, Yuntong Lan, Dongling Yu, Bingqiang Zhang

“…This study successfully developed online calculators using machine learning algorithms to predict 1- to 8-year survival probabilities for EOCRC and LOCRC patients under various treatment strategies.…”
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Advancement of Artificial Intelligence in Cost Estimation for Project Management Success: A Systematic Review of Machine Learning, Deep Learning, Regression, and Hybrid Models by Md. Mahfuzul Islam Shamim, Abu Bakar bin Abdul Hamid, Tadiwa Elisha Nyamasvisva, Najmus Saqib Bin Rafi

“…Hybrid models combine the strengths of different algorithms, achieving 80–90% accuracy on average, and are particularly effective in complex, multi-faceted projects. …”
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Curvilinear relationship between life's crucial 9 and metabolic syndrome in U.S. adults: a cross-sectional study by Bo Wang, Chunqi Jiang, Pingping Yu, Zhen Nie, Ning Wang, Xin Zhang, Xin Zhang

“…To pinpoint inflection points, we integrated recursive partitioning algorithms with a two-stage linear regression model. …”
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M3S-GRPred: a novel ensemble learning approach for the interpretable prediction of glucocorticoid receptor antagonists using a multi-step stacking strategy by Nalini Schaduangrat, Hathaichanok Chuntakaruk, Thanyada Rungrotmongkol, Pakpoom Mookdarsanit, Watshara Shoombuatong

“…Using these balanced subsets, we explored and evaluated heterogeneous base-classifiers trained with a variety of SMILES-based feature descriptors coupled with popular ML algorithms. …”
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Smart grid stability prediction using Adaptive Aquila Optimizer and ensemble stacked BiLSTM by Safwan Mahmood Al-Selwi, Mohd Fadzil Hassan, Said Jadid Abdulkadir, Mohammed Gamal Ragab, Alawi Alqushaibi, Ebrahim Hamid Sumiea

“…The results show profound potential with accuracy, precision, recall, and F1-score rates of 99.55%, surpassing both traditional ML algorithms and state-of-the-art approaches.…”
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A Data-Driven Approach for Predicting Remaining Useful Life of Semiconductor Devices Based on Machine Learning and Synthetic Data Generation: A Review and Case Study on SiC MOSFETs by Yarens J. Yarenscruz, Fernando Castano, Alberto Villalonga, Madhav Mishra, Rodolfo E. Haber

“…The proposed approach was evaluated on a silicon carbide metal-oxide-semiconductor field-effect transistor dataset. …”
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Biochemical disturbances in schizophrenia — a «window of opportunity» by T. V. Zhilyaeva, A. S. Piatoikina, E. D. Kasyanov, G. V. Rukavishnikov, I. V. Semennov, O. V. Kostina, A. S. Blagonravova, G. E. Mazo

“…Materials and methods: in the blood serum of 125 patients with schizophrenia and 95 healthy volunteers the levels of folate and cobalamin (B12) (chemiluminescent immunoassay on microparticles), homocysteine (HC, enzymatic analysis), tetrahydrobiopterin (BH4, competitive enzyme immunoassay, ELISA), reduced glutathione (GSH, spectrophotometry with Ellman’s reagent), interleukin-6 (IL-6, ELISA based on a three-stage «sandwich version») and C-reactive protein (CRP, immunoturbodimetric method) were evaluated.   Results: In patients with schizophrenia the level of all studied serum biochemical markers, except for B12, was significantly different compared to healthy volunteers. …”
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Comparison of Surface Current Measurement Between Compact and Square-Array Ocean Radar by Yu-Hsuan Huang, Chia-Yan Cheng

“…In Taiwan, the Taiwan Ocean Research Institute (TORI) has established a data quality management mechanism based on international standards for data filtering, noise reduction, and outlier detection, improving the accuracy and stability of radar-derived velocity measurements.To eliminate the effects caused by different center frequencies between MABT and KNTN, this study used the same algorithms and parameter settings as much as possible in all steps, from Doppler spectra processing to radial velocity calculation, ensuring the comparability of the data. …”
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Strategy for Optimizing Vitamin B12 Production in <i>Pseudomonas putida</i> KT2440 Using Metabolic Modeling by Thomaz Satuye Prieto-de Lima, Keilor Rojas-Jimenez, Christopher Vaglio

“…<b>Methods</b>: We curated and modified a genome-scale metabolic model of <i>Pseudomonas putida</i> KT2440 and evaluated different strategies to optimize vitamin B₁₂ production using the knockin and OptGene algorithms from the COBRA Toolbox. …”
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FTIR-Based Microplastic Classification: A Comprehensive Study on Normalization and ML Techniques by Octavio Villegas-Camacho, Iván Francisco-Valencia, Roberto Alejo-Eleuterio, Everardo Efrén Granda-Gutiérrez, Sonia Martínez-Gallegos, Daniel Villanueva-Vásquez

“…Furthermore, the impact of different normalization techniques (Min-Max, Max-Abs, Sum of Squares, and Z-Score) on classification accuracy was evaluated. …”
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Fine-Tuning EEG Channel Utilization for Emotionally Stimulated Biometric Authentication by Chetan Rakshe, Christy Bobby Thomas, Mohanavelu Kalathe, Vanteemar S. Sreeraj, Ganesan Venkatasubramanian, Deepesh Kumar, A. Amalin Prince, Jac Fredo Agastinose Ronickom

“…In this study, we propose a novel pipeline to evaluate electroencephalography (EEG)-based biometric system across different emotional states and optimize critical brain regions using machine learning algorithms. …”
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Characterizing the Inter-Core Qubit Traffic in Large-Scale Quantum Modular Architectures by Sahar Ben Rached, Isaac Lopez Agudo, Santiago Rodrigo, Medina Bandic, Artur Garcia-Saez, Sebastian Feld, Hans van Someren, Eduard Alarcon, Carmen G. Almudever, Sergi Abadal

“…Based on the showcased results, we conclude on the parallelization and scalability of presented algorithms, qualitatively evaluate the resource requirements as we scale circuit sizes, and lay the foundations of application-oriented benchmarking of large-scale multi-core architectures.…”
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Protecting Industrial Control Systems From Shodan Exploitation Through Advanced Traffic Analysis by Sayed Reza Ghazinour Naeini, Alireza Shameli-Sendi, Masoume Jabbarifar

“…Several machine learning algorithms were evaluated, including Random Forest, Support Vector Machine, Logistic Regression, and Gradient Boosting. …”
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Cost-Efficient RSSI-Based Indoor Proximity Positioning, for Large/Complex Museum Exhibition Spaces by Panos I. Philippopoulos, Kostas N. Koutrakis, Efstathios D. Tsafaras, Evangelia G. Papadopoulou, Dimitrios Sigalas, Nikolaos D. Tselikas, Stefanos Ougiaroglou, Costas Vassilakis

“…A total 15 methods/algorithms were evaluated against prediction accuracy across 20 RSSI datasets, incorporating diverse hall cell allocations and visitor movement patterns. …”
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AI’s role in transforming learning environments: a review of collaborative approaches and innovations by Dwi Mariyono, Akmal Nur Alif Hd

“…AI’s ability to enhance learning outcomes is evident, yet concerns around algorithmic bias, data privacy and the digital divide must be addressed to ensure equitable access to AI-powered education worldwide. …”
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Enhanced Spring Wheat Soil Plant Analysis Development (SPAD) Estimation in Hetao Irrigation District: Integrating Leaf Area Index (LAI) Under Variable Irrigation Conditions by Qiang Wu, Dingyi Hou, Min Xie, Qi Gao, Mengyuan Li, Shuiyuan Hao, Chao Cui, Keke Fan, Yu Zhang, Yongping Zhang

“…While integrating canopy structural parameters with spectral data represents a promising solution, systematic investigation of this approach throughout the entire growth cycle of spring wheat under different irrigation regimes remains limited. This study evaluated three machine learning algorithms (Random Forest, Support Vector Regression, and Multi-Layer Perceptron) for SPAD estimation in spring wheat cultivated in the Hetao Irrigation District. …”
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Artificial Intelligence–Aided Diagnosis System for the Detection and Classification of Private-Part Skin Diseases: Decision Analytical Modeling Study by Wei Wang, Xiang Chen, Licong Xu, Kai Huang, Shuang Zhao, Yong Wang

“…Compared with existing advanced algorithms, this system is more accurate in identifying PPSDs. …”
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Climate change will alter Amazonian bumblebees’ distribution, but effects are species-specific by Patrícia Nunes-Silva, André Luis Acosta, Rafael Cabral Borges, Breno Magalhães Freitas, Ricardo Caliari Oliveira, Tereza Cristina Giannini, Vera Lucia Imperatriz-Fonseca

“…An ensemble modeling approach combining five different algorithms was used to predict areas of stability, habitat loss, and potential range expansion.ResultsBy 2060, B. brevivillus is projected to lose 41.6% of its current suitable habitat, with significant reductions in northern and coastal regions. …”
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