Application of machine learning algorithms for predicting the life-long physiological effects of zinc oxide Micro/Nano particles on Carum copticum by Maryam Mazaheri-Tirani, Soleyman Dayani, Majid Iranpour Mobarakeh

“…In this study, nine ML algorithms [Support-Vector Regression (SVR), Linear, Bagging, Stochastic Gradient Descent (SGD), Gaussian Process, Random Sample Consensus (RANSAC), Partial Least Squares (PLS), Kernel Ridge, and Random Forest] were applied to evaluate their efficiency in predicting the effects of zinc oxide nanoparticles (ZnO NPs: 0.5, 1, 5, 25, and 125 µM) and microparticles (ZnO MPs: 1, 5, 25, and 125 µM) on Carum copticum. …”
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Genetic algorithm optimization of ensemble learning approach for improved land cover and land use mapping: Application to Talassemtane National Park by Ali Azedou, Aouatif Amine, Isaya Kisekka, Said Lahssini

“…This study proposes a Genetic Algorithm (GA) optimization method for ensemble classification to improve LCLU classification accuracy while maintaining computational efficiency. …”
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Exploration of the Ignition Delay Time of RP-3 Fuel Using the Artificial Bee Colony Algorithm in a Machine Learning Framework by Wenbo Liu, Zhirui Liu, Hongan Ma

“…Ignition delay time (IDT) is a critical parameter for evaluating the autoignition characteristics of aviation fuels. …”
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Assessment of Spectral Computed Tomography Image Quality and Detection of Lesions in the Liver Based on Image Reconstruction Algorithms and Virtual Tube Voltage by Areej Hamami, Mohammad Aljamal, Nora Almuqbil, Mohammad Al-Harbi, Zuhal Y. Hamd

“…<b>Objectives</b>: This study evaluated improvements in image quality achieved using various virtual tube voltages and reconstruction algorithms for diagnosing common liver diseases with spectral CT. …”
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Study on privacy preserving encrypted traffic detection by Xinyu ZHANG, Bingsheng ZHANG, Quanrun MENG, Kui REN

“…Existing encrypted traffic detection technologies lack privacy protection for data and models, which will violate the privacy preserving regulations and increase the security risk of privacy leakage.A privacy-preserving encrypted traffic detection system was proposed.It promoted the privacy of the encrypted traffic detection model by combining the gradient boosting decision tree (GBDT) algorithm with differential privacy.The privacy-protected encrypted traffic detection system was designed and implemented.The performance and the efficiency of proposed system using the CICIDS2017 dataset were evaluated, which contained the malicious traffic of the DDoS attack and the port scan.The results show that when the privacy budget value is set to 1, the system accuracy rates are 91.7% and 92.4% respectively.The training and the prediction of our model is efficient.The training time of proposed model is 5.16 s and 5.59 s, that is only 2-3 times of GBDT algorithm.The prediction time is close to the GBDT algorithm.…”
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Performance evaluation of primary user and secondary user based on CSMA protocol in CRSN by Ying LIU, Li ZHENG, Yuansong LI

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Performance evaluation of primary user and secondary user based on CSMA protocol in CRSN by Ying LIU, Li ZHENG, Yuansong LI

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EVALUATION OF MACHINE LEARNING MODELS FOR BORON PREDICTION IN ANDISOL SOILS OF NARIÑO-COLOMBIA by David Álvarez Sánchez, Xilena López Estrella, Eduar Manso Ordoñez, Laura López Rivera, Jeison Rodriguez Valenzuela

“…To explore the application of ML tools for the prediction of Boron levels in Andisols soils of Nariño has been explored and identifying the most efficient algorithm. Methodology. A total of 1,067 soil samples collected in various fields of five municipalities in the southern subregion of the department were used, where the supervised learning models, Random Forest (RF), K-Nearest Neighbors (K-NN), Support Vector Machine (SVM) and Naive Bayes (NB) were evaluated. …”
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SAHAANN: A NOVEL EVOLUTIONARY ARTIFICIAL NEURAL NETWORK FOR IMPROVED FINANCIAL TIME SERIES FORECASTING by Abdul Khadeer, Vanaparthi Kiranmai, B. Suvarnamukhi, Ayaz Mohiuddin, Balika Mahesh, P M Suresh, J Arthy, Sasikumar A N, Sudersan Behera, Mohd Ayaz Uddin

“…We were able to see how the results of training the ANN model with different metaheuristics, such as the genetic algorithm (GA), particle swarm optimization (PSO), differential evolution (DE), fireworks algorithm (FWA), and chemical reaction optimization (CRO). …”
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Evaluation of the effectiveness of defense measures during radiological risk assessment in gynecological brachytherapy by C. C. Dominguez, A. Torres, R. Alfonso

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Fine-Grained Classification of Pressure Ulcers and Incontinence-Associated Dermatitis Using Multimodal Deep Learning: Algorithm Development and Validation Study by Alexander Brehmer, Constantin Seibold, Jan Egger, Khalid Majjouti, Michaela Tapp-Herrenbrück, Hannah Pinnekamp, Vanessa Priester, Michael Aleithe, Uli Fischer, Bernadette Hosters, Jens Kleesiek

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Integration of ground-based and remote sensing data with deep learning algorithms for mapping habitats in Natura 2000 protected oak forests by Lucia Čahojová, Ivan Jarolímek, Barbora Klímová, Michal Kollár, Michaela Michalková, Karol Mikula, Aneta A. Ožvat, Denisa Slabejová, Mária Šibíková

“…A dataset was selected for the training of a deep learning algorithm called the Natural Numerical Network on the basis of the analysis results. …”
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The dosimetric impacts of ct-based deep learning autocontouring algorithm for prostate cancer radiotherapy planning dosimetric accuracy of DirectORGANS by Serap Çatlı Dinç, Aybala Nur Üçgül, Hüseyin Bora, Ertuğrul Şentürk

“…Abstract Purpose In study, we aimed to dosimetrically evaluate the usability of a new generation autocontouring algorithm (DirectORGANS) that automatically identifies organs and contours them directly in the computed tomography (CT) simulator before creating prostate radiotherapy plans. …”
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A cross-chain model for warehouse receipts in port supply chain based on notary mechanism and ShangMi cryptographic algorithms by Yangbo Chen, Wei Ou, Mengxue Pang, Jianqiang Ma, Qiuling Yue, Wenbao Han

“…The proposed system employs a layered data structure for warehouse receipts and uses differentiated encryption strategies. These features enable flexible data sharing while ensuring the protection of sensitive information. …”
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Formulation and evaluation of ocean dynamics problems as optimization problems for quantum annealing machines. by Takuro Matsuta, Ryo Furue

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Raman and FT-IR Spectroscopy Coupled with Machine Learning for the Discrimination of Different Vegetable Crop Seed Varieties by Stefan M. Kolašinac, Marko Mladenović, Ilinka Pećinar, Ivan Šoštarić, Viktor Nedović, Vladimir Miladinović, Zora P. Dajić Stevanović

“…The aim of this research is to investigate the potential of Raman and FT-IR spectroscopy as well as mathematical linear and non-linear models as a tool for the discrimination of different seed varieties of paprika, tomato, and lettuce species. …”
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Performance evaluation of perceptible impulsive noise detection methods based on auditory models by Arda Özdoğru, František Rund, Karel Fliegel

“…Evaluation criteria of the algorithms included the hit rate, false alarm rate, $$A'$$ A ′ , and computational time. …”
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Do comprehensive deep learning algorithms suffer from hidden stratification? A retrospective study on pneumothorax detection in chest radiography by Luke Oakden-Rayner, Catherine M Jones, John Lambert, Jarrel Seah, Cyril Tang, Quinlan D Buchlak, Michael Robert Milne, Xavier Holt, Hassan Ahmad, Nazanin Esmaili, Peter Brotchie

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Restrictive intraoperative fluid optimisation algorithm improves outcomes in patients undergoing pancreaticoduodenectomy: A prospective multicentre randomized controlled trial. by Laurence Weinberg, Damian Ianno, Leonid Churilov, Ian Chao, Nick Scurrah, Clive Rachbuch, Jonathan Banting, Vijaragavan Muralidharan, David Story, Rinaldo Bellomo, Chris Christophi, Mehrdad Nikfarjam

“…We aimed to evaluate perioperative outcomes in patients undergoing pancreaticoduodenectomy with or without a cardiac output goal directed therapy (GDT) algorithm. …”
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Development of a prognostic model for breast cancer patients based on intratumoral tumor-infiltrating lymphocytes using machine learning algorithms by Xinyi Wu, Chun Li

“…Results Our study constructed a pioneering prognostic model based on iTIL-centric signature via a machine learning framework that evaluated 101 algorithm combinations. This model revealed significant differences in the immune landscape among stratified patient cohorts, and demonstrated robust predictive capabilities across multiple datasets. …”
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