Determination of the effect of GA3 applications on plant development, nutrient content change and analysis of root architectural features using ML artificial neural network modelli... by Sari Ömer

“…Performance percentages of ML algorithms were listed as LR > MCC > MLP > J48 > PART > Baggin.…”
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Interoception, cardiac health, and heart failure: The potential for artificial intelligence (AI)—driven diagnosis and treatment by Mahavir Singh, Anmol Babbarwal, Sathnur Pushpakumar, Suresh C. Tyagi

“…In the context of HF, AI algorithms can analyze and interpret complex interoceptive data, providing valuable insights for diagnosis and treatment. …”
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Rough Set Approach toward Data Modelling and User Knowledge for Extracting Insights by Xiaoqun Liao, Shah Nazir, Junxin Shen, Bingliang Shen, Sulaiman Khan

“…The technique has used different rough set algorithms such as K-nearest neighbours (KNN), decision rules (DR), decomposition tree (DT), and local transfer function classifier (LTF-C) for an experimental setup. …”
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Emergency Trajectory Structure for UAVs by Maëva Ongale-Obeyi, Damien Goubinat, Daniel Delahaye, Pierre-Loïc Garoche

“…It is important to note that the algorithms chosen address only a simplified version of the problem. …”
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Early Stroke Prediction Methods for Prevention of Strokes by Mandeep Kaur, Sachin R. Sakhare, Kirti Wanjale, Farzana Akter

“…The cascaded prediction algorithms are time-consuming in producing the results and cannot work on the raw data and without making use of the properties of EEG. …”
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Diagnosis of Cognitive and Mental Disorders: A New Approach Based on Spectral–Spatiotemporal Analysis and Local Graph Structures of Electroencephalogram Signals by Arezoo Sanati Fahandari, Sara Moshiryan, Ateke Goshvarpour

“…Methods: Our investigation will utilize algorithms based on Granger causality and local graph structures to improve classification accuracy. …”
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Decision Tree Ensembles to Predict Coronavirus Disease 2019 Infection: A Comparative Study by Amir Ahmad, Ourooj Safi, Sharaf Malebary, Sami Alesawi, Entisar Alkayal

“…The machine learning algorithms were applied on a Covid-19 dataset based on commonly taken laboratory tests to predict Covid-19 positive cases. …”
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Boruta-grid-search least square support vector machine for NO2 pollution prediction using big data analytics and IoT emission sensors by Habeeb Balogun, Hafiz Alaka, Christian Nnaemeka Egwim

“…Purpose – This paper seeks to assess the performance levels of BA-GS-LSSVM compared to popular standalone algorithms used to build NO2 prediction models. The purpose of this paper is to pre-process a relatively large data of NO2 from Internet of Thing (IoT) sensors with time-corresponding weather and traffic data and to use the data to develop NO2 prediction models using BA-GS-LSSVM and popular standalone algorithms to allow for a fair comparison. …”
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Calibrating Path Choices and Train Capacities for Urban Rail Transit Simulation Models Using Smart Card and Train Movement Data by Baichuan Mo, Zhenliang Ma, Haris N. Koutsopoulos, Jinhua Zhao

“…The calibration is formulated as an optimization problem with a black-box objective function. Seven algorithms from four branches of SBO solving methods are evaluated. …”
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Teaching a neural network modeling socio-economic development of the region by S. V. Romanchukov, O. G. Berestneva, L. A. Petrova

“…At the same time, however, it should be noted that the resources of an individual research team may be (and most likely will be) insufficient to create their own software solution for the implementation of machine learning algorithms from scratch. The use of third-party cloud-based software platforms (primarily IBM and Google infrastructures) allows to bypass the problem of the research team’s lack of expensive material and technical base, however they impose a number of limitations dictated by the requirements of the existing machine learning algorithms and the specific architecture provided platforms This puts the research team in front of the need to prepare the accumulated data set for processing: reducing the dimension, checking the data for compliance with the platform requirements and eliminating potential problem areas: “data leaks”, “learning distortions” and others. …”
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Deep Learning-Based Home Energy Management Incorporating Vehicle-to-Home and Home-to-Vehicle Technologies for Renewable Integration by Marwan Mahmoud, Sami Ben Slama

“…Neural network-based Q-learning algorithms optimize the scheduling of household appliances and the management of energy storage systems, including batteries, to maximize energy efficiency. …”
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Prediction of the remaining useful life of a milling machine using machine learning by Abbas Al-Refaie, Majd Al-atrash, Natalija Lepkova

“…A web application for maintenance was finally developed with several ML algorithms at the evaluation stage. Maintenance engineers can utilize the developed smart web application to monitor the machine's health state and predict failure occurrence. …”
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Efficient Hyperspectral Video Reconstruction via Dual-Channel DMD Encoding by Mingming Ma, Yi Niu, Dahua Gao, Fu Li, Guangming Shi

“…Hyperspectral video acquisition requires a precise balance between spectral and temporal resolution, often achieved through compressive sampling using two-dimensional detectors and spectral reconstruction algorithms. However, the reliance on spatial light modulators for coding reduces optical efficiency, while complex recovery algorithms hinder real-time reconstruction. …”
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Research Progress and Prospects of Key Navigation Technologies for Facility Agricultural Robots by HE Yong, HUANG Zhenyu, YANG Ningyuan, LI Xiyao, WANG Yuwei, FENG Xuping

“…Advanced sensor technologies and algorithms have been proposed to enhance robots' adaptability and decision-making capabilities in dynamic environments. …”
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Playing hide and seek with primates: A comparative study of Theory of Mind by Aurore San‑Galli, Marie Devaine, Cinzia Trapanese, Shelly Masi, Sébastien Bouret, Jean Daunizeau

“…In fact, the location of the food was chosen by learning algorithms, some of which endowed with artificial ToM. …”
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Future of artificial intelligence for the diagnosis and treatment of retinal diseases by E.A. Katalevskaya, D.Yu. Katalevskiy, M.I. Tyurikov, I.A. Velieva, A.V. Bol’shunov

“…This paper reviews the use of AI algorithms for diagnosing and treating retinal disorders. …”
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Multilocus Sequence Typing for Interpreting Blood Isolates of Staphylococcus epidermidis by Prannda Sharma, Ashley E. Satorius, Marika R. Raff, Adriana Rivera, Duane W. Newton, John G. Younger

“…Three machine learning algorithms (classification regression tree, support vector machine, and nearest neighbor) were employed. …”
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Expectation maximization—vector approximate message passing based generalized linear model for channel estimation in intelligent reflecting surface-assisted millimeter multi-user m... by Shoukath Ali K, Sajan P Philip, Arfat Ahmad Khan, Leeban Moses, Korhan Cengiz, Sedat Akleylek, Nikola Ivković

“…Numerical results unveil that the proposed Its EM-VAMP-GLM is much more robust to the existing OMP, GAMP and EM-LAMP algorithms.…”
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Peptide-Based Vaccinology: Experimental and Computational Approaches to Target Hypervariable Viruses through the Fine Characterization of Protective Epitopes Recognized by Monoclon... by Matteo Castelli, Francesca Cappelletti, Roberta Antonia Diotti, Giuseppe Sautto, Elena Criscuolo, Matteo Dal Peraro, Nicola Clementi

“…Thus, in the last decade many epitope predictive algorithms have been developed. These algorithms are continually evolving, and their use to address the empirical research is widely increasing. …”
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New Benchmarking Methodology and Programming Model for Big Data Processing by Anton Kos, Sašo Tomažič, Jakob Salom, Nemanja Trifunovic, Mateo Valero, Veljko Milutinovic

“…In our view, the next step of data flow computing development should be a move from specialized to more general algorithms and applications.…”
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