Evaluation of Machine Learning Models for Enhancing Sustainability in Additive Manufacturing by Waqar Shehbaz, Qingjin Peng

“…Subsequently, four ML models, Linear Regression, Decision Trees, Random Forest, and Gradient Boosting, are trained and evaluated. Hyperparameter tuning is conducted using the Limited-memory Broyden–Fletcher–Goldfarb–Shanno with Box constraints (L-BFGS-B) algorithm, which demonstrates the superior computational efficiency compared to traditional approaches such as grid and random search. …”
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RECOMMENDED TACTICS FOR THE EVALUATION OF POTENTIALLY MALIGNANT DISORDERS IN THE ORAL CAVITY by S.V. Kolomiiets, K.O. Udaltsova, V.I. Shynkevych

“…Those involve whole series of redirections of the patient among dentists themselves, before referring to the really necessary specialist, and it represents a negative item in the organization. In contrast to the algorithm provided by the Ministry of Healthcare of Ukraine, doing an immediate biopsy in patients with a suspicious oral lesion – or referring a patient to a specialist who can do that – remains the only most important recommendation made by the American Dental Association (ADA) in their updated clinical practice guidelines for the evaluation of potentially malignant disorders in the oral cavity. …”
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An improved multiple adaptive neuro fuzzy inference system based on genetic algorithm for energy management system of island microgrid by Yanming Cheng, Jinqi Zhang, Mahmoud Al Shurafa, Dejun Liu, Yulian Zhao, Chao Ding, Jing Niu

“…For evaluation purpose, a real case study of a day-ahead data is tested and discussed in details. …”
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Optimization of Analog Circuit Parameters Using Bidirectional Long Short-Term Memory Coupled with an Enhanced Whale Optimization Algorithm by Hengfei Yang, Shiyuan Yang, Debiao Meng, Chenghao Hu, Chaosheng Wu, Bo Yang, Peng Nie, Yuan Si, Xiaoyan Su

“…The new algorithm enhances the initial population design and population position update process of the original Whale Optimization Algorithm (WOA), thereby improving both the global search capability and local exploitation ability of the algorithm. …”
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VCNet: Optimized Deep Learning framework with deep feature extraction and genetic algorithm for multiclass rice crop disease detection by Sanam Salman Kazi, Bhakti Palkar, Dhirendra Mishra

“…Further the model goes through two level optimization process where optimal hyperparameters identified through experimentation is given as parameters to genetic algorithm for optimization of VCNet during training. …”
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Interpersonal counselling for adolescent depression delivered by youth mental health workers without core professional training: the ICALM feasibility RCT by Jon Wilson, Viktoria Cestaro, Eirini Charami-Roupa, Timothy Clarke, Aoife Dunne, Brioney Gee, Sharon Jarrett, Thando Katangwe-Chigamba, Andrew Laphan, Susie McIvor, Richard Meiser-Stedman, Jamie Murdoch, Thomas Rhodes, Carys Seeley, Lee Shepstone, David Turner, Paul Wilkinson

“…A health economics component was included to inform the design of the economic evaluation in a future study. A process evaluation examined implementation of the intervention across settings, acceptability and contamination. …”
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Conversion Prediction in Google Search Ads Keyword Selection Using the K-Nearest Neighbor and C4.5 Algorithms by Muhammad Sya'ban Harahap, Alva Hendi Muhammad

“…A comparative experimental approach was employed, with the data split into training (80%) and testing (20%) sets. The analysis revealed that the C4.5 algorithm achieved higher accuracy (85.41%) compared to K-NN (74.86%). …”
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Classification of Anxiety Levels of IGD Patients at RSU Royal Prima Medan Using Support Vector Machine (SVM) Algorithm by Kharisma Gunanta Ginting, Nugroho Prasetyo, Al Vino Gunawan, Magdalena Sihombing, Adli Abdillah Nababan

“…This study aims to develop a patient anxiety level classification model in the ED using the Support Vector Machine (SVM) algorithm with the application of the Synthetic Minority Oversampling Technique (SMOTE) to address the class imbalance issue. …”
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A novel YOLOv11-Driven deep learning algorithm for UAV multispectral oil spill detection in Inland lakes by Yu Zhang, Jian Xing, Weida Chen, Haitao Wang, Bingyu Shi, Yang Song, Xiaoou Huang, Zihan Jiang

“…A UAV was deployed to acquire 623 multispectral images from oil spill sites in the Daqing oilfield, forming a comprehensive dataset for model training and evaluation. Experimental results show that, compared to the baseline YOLOv11 model, YOLO-ADHF-SimAM achieves a 1.8% improvement in detection accuracy, a 6% increase in recall, a 3.3% boost in mAP@50, and a 2% enhancement in mAP@50–95. …”
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Improving Systematic Review Updates With Natural Language Processing Through Abstract Component Classification and Selection: Algorithm Development and Validation by Tatsuki Hasegawa, Hayato Kizaki, Keisho Ikegami, Shungo Imai, Yuki Yanagisawa, Shuntaro Yada, Eiji Aramaki, Satoko Hori

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Predicting indoor temperature of solar green house by machine learning algorithms: A comparative analysis and a practical approach by Wenhe Liu, Tao Han, Cong Wang, Feng Zhang, Zhanyang Xu

“…GRU, by virtue of its more concise gating mechanism (featuring only update gates and reset gates), not only ensured high precision but also significantly improved training efficiency compared to LSTM. This research not only compared the performance of different machine learning algorithms in solar greenhouse temperature prediction but also explored the applicability of each algorithm across various prediction horizons. …”
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Study on risk factors of impaired fasting glucose and development of a prediction model based on Extreme Gradient Boosting algorithm by Qiyuan Cui, Jianhong Pu, Wei Li, Yun Zheng, Jiaxi Lin, Lu Liu, Peng Xue, Jinzhou Zhu, Mingqing He

“…Feature selection, parameter optimization, and model construction were performed in the training set, while the validation set was used to evaluate the predictive performance of the models. …”
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Silent speech recognition using visual cascading fusion of tongue-lip movements based on pre-trained and fine-tuned model by Chongchong Yu, Xuening Wang, Zhaopeng Qian

“…Besides, the pre-trained and fine-tuned frameworks based on Visual-HuBERT using masked technology are used to address the overfitting problems of model due to a lack of training data. …”
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Tablet-based sensorimotor home-training system for amnestic mild cognitive impairments in the elderly: design of a randomised clinical trial by Robin Bekrater-Bodmann, Annette Löffler, Stefano Silvoni, Lutz Frölich, Lucrezia Hausner, Simon Desch, Dieter Kleinböhl, Herta Flor

“…Both trainings consist of an adaptive algorithm, and will last 3 months each. …”
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RehabHand—A New Physical Rehabilitation Training Dataset: Construction and Benchmark Performances of the Relevant Hand Tasks by Sinh Huy Nguyen, Hoang Bach Nguyen, Thi Thu Hong Le, Chi Thanh Nguyen, Thi Thanh Huyen Nguyen, Quynh Tho Chu, Thi Lan Le, Thanh Hai Tran, Hai Vu

“…These labeled datasets are utilized to evaluate three primary tasks related to evaluating physical hand functions: including one- and two-stage neuronal networks for hand detection and identifying left or right patient’s hand; hand tracking with SORT and DeepSORT algorithms. …”
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Optimizing Traffic Speed Prediction Using a Multi-Objective Genetic Algorithm-Enhanced RNN for Intelligent Transportation Systems by C. Swetha Priya, F. Sagayaraj Francis

“…Nevertheless, these hybrid models often require significant storage space, contain numerous learnable parameters, and involve extensive training, validation, and testing times. To address these challenges, we propose a novel methodology that combines a genetic algorithm (GA) with Random Forest Cross-Validation (RF-CV) to evaluate input features and select the most relevant subset. …”
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Genetic programming-based algorithms application in modeling the compressive strength of steel fiber-reinforced concrete exposed to elevated temperatures by Mohsin Ali, Li Chen, Qadir Bux Alias Imran Latif Qureshi, Deema Mohammed Alsekait, Adil Khan, Kiran Arif, Muhammad Luqman, Diaa Salama Abd Elminaam, Amir Hamza, Majid Khan

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A gradient-descent-like learning-based framework in surrogate-assisted evolutionary algorithms for expensive many-objective optimization by Chaoyi Sun, Bo Zhang, Hai Sun, Rui Feng

“…To implement the proposed framework, three representative SAEAs are embedded into the GDL-SAEA. Experimental evaluations on multiobjective benchmarks and real-world problems with up to 10 objectives reveal that GDL-SAEA outperforms seven state-of-the-art and classic algorithms.…”
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SwinLightGAN a study of low-light image enhancement algorithms using depth residuals and transformer techniques by Min He, Rugang Wang, Mingyang Zhang, Feiyang Lv, Yuanyuan Wang, Feng Zhou, Xuesheng Bian

“…Abstract Contemporary algorithms for enhancing images in low-light conditions prioritize improving brightness and contrast but often neglect improving image details. …”
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A New Approach Combining RSA and ElGamal Algorithms: Advancements in Encryption and Digital Signatures Using Gaussian Integers by Yahia Awad, Douaa Jomaa, Yousuf Alkhezi, Ramiz Hindi

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