Enhanced Multi-UAV Path Planning in Complex Environments With Voronoi-Based Obstacle Modelling and Q-Learning by Wenjia Su, Min Gao, Xinbao Gao, Zhaolong Xuan

“…Leveraging the improved Q-learning algorithm for single UAVs, the Q-table is iteratively refined for a fleet of UAVs, with dynamic modifications based on the waypoints chosen by each UAV. …”
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A Finite Element Mesh Aggregating Approach to Multiple-Source Reconstruction in Bioluminescence Tomography by Jingjing Yu, Fang Liu, L. C. Jiao, Shuyuan Yang, Xiaowei He

“…With the proposed strategy integrated in the regularization-based reconstruction process, reconstruction algorithms need no a priori knowledge of source number; even more importantly, they can automatically reconstruct multiple sources that differ greatly in density or power.…”
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Study of Magnetohydrodynamic Pulsatile Blood Flow through an Inclined Porous Cylindrical Tube with Generalized Time-Nonlocal Shear Stress by Nehad Ali Shah, A. Al-Zubaidi, S. Saleem

“…For the semianalytical solution, the inverse Laplace transform is found by means of Stehfest’s and Tzou’s algorithms. The numerical calculations were performed by using Mathcad software. …”
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Hunting the Pertinency of Bloom Filter in Computer Networking and Beyond: A Survey by Ripon Patgiri, Sabuzima Nayak, Samir Kumar Borgohain

“…Bloom filter poses (i) high adaptability, (ii) low memory space overhead as compared to hashing algorithms, (iii) high scalability, and (iv) high performance. …”
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Bent Femoral Nail Removal Technique: An Illustrative Case Report by T Revanth, Giriraj Harshavardhan

“…In the literature, several extraction techniques and algorithms are available for the removal of such implants. …”
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An Update of Medical Nutrition Therapy in Gestational Diabetes Mellitus by Flavia Cristina Vasile, Agnesa Preda, Adela Gabriela Ștefan, Mihaela Ionela Vladu, Mircea-Cătălin Forțofoiu, Diana Clenciu, Ioan Ovidiu Gheorghe, Maria Forțofoiu, Maria Moța

“…Different health organizations proposed different algorithms for the screening, diagnosis, and management of GDM. …”
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A Low Noise, Low Power Phase-Locked Loop, Using Optimization Methods by Noushin Ghaderi, Hamid Reza Erfani-jazi, Mehdi Mohseni-Mirabadi

“…A novel bulk driven Wilson charge pump circuit, whose performance is enhanced by some optimization algorithms, is also introduced to get high output swing and high current matching. …”
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Robust Command Filtered Adaptive Backstepping Control for a Quadrotor Aircraft by Yicheng Liu, Junhui Ma, Haiyan Tu

“…Different from most of the existing control algorithms, the proposed method does not adopt the dual-loop scheme in which the design is divided into position control and attitude control. …”
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A Comparison of Metaheuristic Techniques for Solving Optimal Sitting and Sizing Problems of Capacitor Banks to Reduce the Power Loss in Radial Distribution System by Tongfei Lei, Saleem Riaz, Hira Raziq, Munira Batool, Feng Pan, Jianfeng Wang

“…In this paper, several metaheuristic techniques such as particle swarm optimization (PSO), Harmony search, Bat, Cuckoo, and Grey-wolf (GW) algorithms are employed to find the size of capacitor banks. …”
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Long Short-Term Memory Recurrent Neural Network for Predicting the Return of Rate Underframe the Fama-French 5 Factor by Bui Thanh Khoa, Tran Trong Huynh

“…This contribution encourages investors and hedge fund managers to use the LSTM-RNN algorithm to boost forecasting efficiency.…”
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Research on the Relationship between Human Resource Management Activities and Enterprise Performance Based on the Supervised Learning Model by Chan Sun, Xiaojuan Li

“…Experimental results on recruitment data demonstrate that the algorithm in this paper has a high check-all rate, check-accuracy rate, and F1. …”
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Simulation Study on Clustering Approaches for Short-Term Electricity Forecasting by Krzysztof Gajowniczek, Tomasz Ząbkowski

“…The contributions of this paper are threefold: (1) using data from 46 homes in Austin, Texas, the similarity measures from different time series are analyzed; (2) the optimal number of clusters for representing residential electricity use profiles is determined; and (3) an extensive load forecasting study using different segmentation-enhanced forecasting algorithms is undertaken. Finally, from the operator’s perspective, the implications of the results are discussed in terms of the use of clustering methods for grouping electrical load patterns.…”
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Designing and Prototyping of a Battery Management System for Solar Power Plants in Uganda. by Ssembalirwa, Denis

“…Additionally, the system employs intelligent algorithms to autonomously manage the charging and discharging cycles based on the battery’s condition. …”
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Encoding and Decoding of Secret Messages Using Matrices by James, Niwagaba

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Developing a Prototype Machine Learning Model to Predict Quality of Life Measures in People Living With HIV by Mercadal-Orfila G, Serrano López de las Hazas J, Riera-Jaume M, Herrera-Perez S

“…Additionally, the model demonstrated strong reliability in maintaining standardized prediction errors below 0.2 for most instruments, with probabilities of achieving this threshold being 96.43% for WHOQoL HIV Bref and 88.44% for ESTAR, while lower probabilities were observed for TSQM (44%) and WRFQ (51%).Conclusion: The results from our machine learning algorithms are promising for predicting PROMs and PREMs in AIDS settings. …”
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Improving machine learning predictions to estimate fishing effort using vessel's tracking data by J. Samarão, A. Moreno, M.B. Gaspar, M.M. Rufino

“…This information can identify areas with high fishing density, warranting protection of their main fishing grounds against other users (i.e. ocean grabbing), while also signalling potential stock depletion requiring management interventions and preserving the ecosystems from which these fisheries depend on.In this study, we propose a series of steps to enhance the performance of Machine Learning algorithms in estimating fishing effort. We assessed seven supervised ML algorithms, including Logistic Regression, Ridge Classifier, Random Forest Classifier, K-Neighbours, Gradient Boosting Classifier, LinearSVC, Recurrent Neural Networks and XGBoost, using four case studies, from bivalve dredge and octopus pots and traps fisheries.First, in a preliminary statistical analysis between common error measures derived from the confusion matrix was decided to use accuracy, precision, and sensitivity as evaluation criteria. …”
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Enhancing predictive accuracy for urinary tract infections post-pediatric pyeloplasty with explainable AI: an ensemble TabNet approach by Hongyang Wang, Junpeng Ding, Shuochen Wang, Long Li, Jinqiu Song, Dongsheng Bai

“…Feature engineering was initially performed, followed by a comparative analysis of five machine learning algorithms (Logistic Regression, SVM, Random Forest, XGBoost, and LightGBM) and the deep learning TabNet model. …”
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Framework for smartphone-based grape detection and vineyard management using UAV-trained AI by Sergio Vélez, Mar Ariza-Sentís, Mario Triviño, Antonio Carlos Cob-Parro, Miquel Mila, João Valente

“…On one hand, drone, or Unmanned Aerial Vehicles (UAV) imagery combined with deep learning algorithms has revolutionised agriculture by automating plant health classification, disease identification, and fruit detection. …”
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Determining the Factors and Evolutionary Trends of Customer Engagement in Businesses: A Bibliometric Analysis by Reza Abbasi Mobarakabadi, Amir khanlari, Nader Seyyedamiri

“…All analyses were conducted using R programming languages. The algorithms employed included thematic analysis, correspondence analysis, clustering algorithms, and co-occurrence analysis of words.     …”
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Machine learning for predicting severe dengue in Puerto Rico by Zachary J. Madewell, Dania M. Rodriguez, Maile B. Thayer, Vanessa Rivera-Amill, Gabriela Paz-Bailey, Laura E. Adams, Joshua M. Wong

“…Conclusions ML models, especially gradient boosting algorithms, outperformed traditional warning signs in predicting severe dengue. …”
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