A network theoretic method for the basic reproductive number for infectious diseases by Anna Sisk, Nina Fefferman

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Enhancing Pest Detection: Assessing Tuta absoluta (Lepidoptera: Gelechiidae) Damage Intensity in Field Images through Advanced Machine Learning by Edwin Lewıs, Atilla Erdinç, Yavuz Selim Şahin, Alperen Kaan Bütüner, Hilal Erdoğan

“…Consequently, the early detection of T. absoluta damage intensity on leaves using machine learning or artificial intelligence-based algorithms is crucial for effective pest control. In this ground-breaking study, the galleries generated by T. absoluta were examined via field images using the Decision Trees (DTs) algorithm, a machine learning method. …”
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Predicting Live Weight for Female Rabbits of Meat Crosses From Body Measurements Using LightGBM, XGBoost and Support Vector Machine Algorithms by Hasan Önder, Cem Tirink, Taras Yakubets, Andriy Getya, Mykhalio Matvieiev, Ruslan Kononenko, Uğur Şen, Çağri Özgür Özkan, Tolga Tolun, Fahrettin Kaya

“…A highly efficient gradient‐boosting decision tree (LightGBM), eXtreme gradient‐boosting (XGBoost) and support vector machine (SVM) algorithms were evaluated and compared to the prediction of BW. …”
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AI-Driven Predictive Maintenance for Workforce and Service Optimization in the Automotive Sector by Şenda Yıldırım, Ahmet Deniz Yücekaya, Mustafa Hekimoğlu, Meltem Ucal, Mehmet Nafiz Aydin, İrem Kalafat

“…Additionally, this predictive approach supports workforce planning and scheduling within after-sales service centers, aligning with AI-driven labor optimization frameworks such as those explored in the AI4LABOUR project. Four algorithms in machine learning—Decision Tree, Random Forest, LightGBM (LGBM), and Extreme Gradient Boosting (XGBoost)—were assessed for their forecasting capabilities. …”
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Developing a Model to Predict the Effectiveness of Vaccination on Mortality Caused by COVID-19 by Malihe Niksirat, Javad Tayyebi, Seyedeh Fatemeh Javadi, Adrian Marius Deaconu

“…The Coronavirus Disease 2019 (COVID-19) pandemic highlighted the urgent need for effective vaccination strategies to control the virus’s spread and reduce mortality. …”
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DDoSNet: Detection and prediction of DDoS attacks from realistic multidimensional dataset in IoT network environment by Goda Srinivasa Rao, P. Santosh Kumar Patra, V.A. Narayana, Avala Raji Reddy, G.N.V. Vibhav Reddy, D. Eshwar

“…Following this, feature selection uses the African Buffalo Optimization with Decision Tree (ABO-DT) method. This nature-inspired metaheuristic algorithm imitates the behaviour of African buffalos to determine which traits are the most important. …”
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The Application of Machine Learning Algorithms to Predict HIV Testing in Repeated Adult Population–Based Surveys in South Africa: Protocol for a Multiwave Cross-Sectional Analysis... by Musa Jaiteh, Edith Phalane, Yegnanew A Shiferaw, Refilwe Nancy Phaswana-Mafuya

“…Further investigation is needed to bridge this knowledge gap and inform evidence-based interventions to improve HIV testing. …”
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Integrating Quantum Computing into De Novo Metabolite Identification by Li-An Tsai, Estelle Nuckels, Yingfeng Wang

“…However, this strategy is time-consuming and cannot meet the need for high-throughput metabolite identification. …”
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Application of machine learning algorithms to model predictors of informed contraceptive choice among reproductive age women in six high fertility rate sub Sahara Africa countries by Mequannent Sharew Melaku, Lamrot Yohannes, Berhanu Sharew, Mintesnot Hawaz Derseh, Eliyas Addisu Taye

“…The LGBM classifier outperformed among machine learning algorithms and achieved 73% accuracy and an AUC of 0.80. …”
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Extraction of exact symbolic stationary probability formulas for Markov chains in finite space with application to production lines. part II: unveiling accurate formulas for very s... by Konstantinos S. Boulas, Georgios D. Dounias, Chrissoleon T. Papadopoulos

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Hard‐state Protocol Independent Multicast—Source‐Specific Multicast (HPIM‐SSM) by Ana Catarina Grilo, Pedro Oliveira, Rui Valadas

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A SAC-Bi-RRT Two-Layer Real-Time Motion Planning Approach for Robot Assembly Tasks in Unstructured Environments by Qinglei Zhang, Siyao Hu, Jianguo Duan, Jiyun Qin, Ying Zhou

“…Due to the uncertainty and complexity of the assembly process, the trajectory planning of a robot needs to consider the real-time obstacle avoidance problem when it completes the assembly in the unstructured workspace. …”
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Study protocol for a pragmatic randomised controlled trial in Belgian primary care and hospital settings on the effectiveness of an eHealth self-management support programme consis... by Josefien van Olmen, An De Groef, Nele Devoogdt, Lore Dams, Bart Morlion, Mira Meeus, G Lorimer Moseley, Louise K Wiles, Peter Hibbert, Patrick Neven, Ines Nevelsteen, Steffen Fieuws, Geert Crombez, Michel Mertens, Ceren Gursen, Wiebren Tjalma, Lander Willem, Lauren C Heathcote, Mark Catley, Anna Vogelzang, Marthe Van Overbeke, Emma Tack, Sophie Van Dijck, Annick L De Paepe, Rani Vanhoudt, Davina Wildemeersch, Femke De Backere

“…This delivery mode is believed to reduce barriers to pain self-management by providing timely, safe and cost-effective assistance addressing the biopsychosocial needs of patients. Utilising a chatbot format, the eHealth programme delivers pain science education and promotes physical activity (PA), personalised through decision-tree-based algorithms to support pain self-management. …”
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Applications of Multi-Robotic Arms to Assist Agricultural Production: A Review by Xiaojian Gai, Chang Xu, Yajia Liu, Qingchun Feng, Shubo Wang

“…This paper summarizes the key technologies used in current research, including heuristic algorithms, fast search rapidly exploring random trees, reinforcement learning algorithms, etc., and focuses on reviewing the present applications of cutting-edge reinforcement learning algorithms in agricultural robotic arms. …”
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Machine Learning Predictive Models for Survival in Patients with Brain Stroke by Solmaz Norouzi, Samira Ahmadi, Shayeste Alinia, Farshid Farzipoor, Azadeh Shahsavari, Ebrahim Hajizadeh, Mohammad Asghari Jafarabadi

“…Background: This study aims to harness the predictive power of machine learning (ML) algorithms for accurately predicting mortality and survival outcomes in brain stroke (BS) patients. …”
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Enhancing Privacy in IoT Networks: A Comparative Analysis of Classification and Defense Methods by Ahmet Emre Ergun, Ozgu Can, Murat Kantarcioglu

“…Additionally, the Decision Tree (DT), Random Forest (RF), k-Nearest Neighbors (kNN), and GRU classification algorithms are also evaluated and compared with the XGBoost and LSTM classifiers for the proposed attack model. …”
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Traffic Classification in Software-Defined Networking Using Genetic Programming Tools by Spiridoula V. Margariti, Ioannis G. Tsoulos, Evangelia Kiousi, Eleftherios Stergiou

“…We apply a series of classifiers, such as MLP (BFGS), FC2 (RBF), FC2 (MLP), Decision Tree, SVM, and GENCLASS, and evaluate their performance in terms of accuracy, detection rate, and precision. …”
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Efficient Fault Diagnosis of Elevator Cabin Door Drives Using Machine Learning with Data Reduction for Reliable Transmission by Jakub Gęca, Dariusz Czerwiński, Bartosz Drzymała, Krzysztof Kolano

“…Existing solutions in the literature include methods such as spectral analysis of system vibrations, motor current signature analysis, fishbone diagrams, fault trees, multi-agent systems, image recognition, and machine learning techniques. …”
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Measurement of spatial heterogeneity in street restorative perceptions and street refinement design by Yalun Lei, Qingqing Li, Jingwen Tian, Jia Hu, Jixiang Jiang

“…Using the random forest (RF) algorithm and restorative component scales (RCS), we assessed residents’ perceptions of street restoration in Shanghai’s Huangpu District. …”
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A Novel LSTM Architecture for Automatic Modulation Recognition: Comparative Analysis With Conventional Machine Learning and RNN-Based Approaches by Sam Ansari, Soliman Mahmoud, Sohaib Majzoub, Eqab Almajali, Anwar Jarndal, Talal Bonny

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