Robust and Fast Point Cloud Registration for Robot Localization Based on DBSCAN Clustering and Adaptive Segmentation by Haibin Liu, Yanglei Tang, Huanjie Wang

“…It improves the algorithm’s adaptive clustering capabilities. …”
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Rapid Lactic Acid Content Detection in Secondary Fermentation of Maize Silage Using Colorimetric Sensor Array Combined with Hyperspectral Imaging by Xiaoyu Xue, Haiqing Tian, Kai Zhao, Yang Yu, Ziqing Xiao, Chunxiang Zhuo, Jianying Sun

“…Moreover, two optimization algorithms, namely grid search (GS) and crested porcupine optimizer (CPO), were compared to determine their effectiveness in optimizing the parameters of the SVR model. …”
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Bioregionalization analyses with the bioregion R package by Pierre Denelle, Boris Leroy, Maxime Lenormand

“…The recent emergence of global databases, improvements in computational power and the development of clustering algorithms coming from the network theory have led to several major updates of the bioregionalizations of many taxa. …”
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Vegetation growth monitoring based on ground-based visible light images from different views by Yanli Chen, Lu Huang, Cheng Chen, Ying Xie

“…The machine learning algorithm combined with NLM filtering optimization had great advantages in multi-view image segmentation. …”
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Explainable Ensemble Learning Model for Residual Strength Forecasting of Defective Pipelines by Hongbo Liu, Xiangzhao Meng

“…Traditional machine learning algorithms often fail to comprehensively account for the correlative factors influencing the residual strength of defective pipelines, exhibit limited capability in extracting nonlinear features from data, and suffer from insufficient predictive accuracy. …”
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Current approaches to diagnosis, treatment, and monitoring in patients with cryopyrin-associated periodic syndromes (CAPS) by S. O. Salugina, E. S. Fedorov, N. N. Kuzmina

“…Interleukin-1 inhibitors are target agents, by which one can monitor activity and prevent complications. The given algorithm will be able to improve the timely diagnosis of CAPS and to optimize treat-to-target treatment and management in patients.…”
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GRU-based multi-scenario gait authentication for smartphones by Qi JIANG, Ru FENG, Ruijie ZHANG, Jinhua WANG, Ting CHEN, Fushan WEI

“…At present, most of the gait-based smartphone authentication researches focus on a single controlled scenario without considering the impact of multi-scenario changes on the authentication accuracy.The movement direction of the smartphone and the user changes in different scenarios, and the user’s gait data collected by the orientation-sensitive sensor will be biased accordingly.Therefore, it has become an urgent problem to provide a multi-scenario high-accuracy gait authentication method for smartphones.In addition, the selection of the model training algorithm determines the accuracy and efficiency of gait authentication.The current popular authentication model based on long short-term memory (LSTM) network can achieve high authentication accuracy, but it has many training parameters, large memory footprint, and the training efficiency needs to be improved.In order to solve the above problems a multi-scenario gait authentication scheme for smartphones based on Gate Recurrent Unit (GRU) was proposed.The gait signals were preliminarily denoised by wavelet transform, and the looped gait signals were segmented by an adaptive gait cycle segmentation algorithm.In order to meet the authentication requirements of multi-scenario, the coordinate system transformation method was used to perform direction-independent processing on the gait signals, so as to eliminate the influence of the orientation of the smartphone and the movement of the user on the authentication result.Besides, in order to achieve high-accuracy authentication and efficient model training, GRUs with different architectures and various optimization methods were used to train the gait model.The proposed scheme was experimentally analyzed on publicly available datasets PSR and ZJU-GaitAcc.Compared with the related schemes, the proposed scheme improves the authentication accuracy.Compared with the LSTM-based gait authentication model, the training efficiency of the proposed model is improved by about 20%.…”
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The accuracy of image-based individual tree crown detection and delineation across vegetation types by N. Pucino, T. McVicar, S. Levick, A. van Dijk

“…Additionally, the DalPonte ITS algorithm provides the most accurate results, especially in sparsely vegetated areas such as rangelands, which are critical for mapping and monitoring. …”
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Apple Trajectory Prediction in Orchards: A YOLOv8-EK-IPF Approach by Jinxing Niu, Zhengyi Liu, Shuo Wang, Jiaxi Huang, Junlong Zhao

“…To address the challenge of accurate apple harvesting by orchard robots, which is hindered by dynamic changes in apple position due to wind interference and branch swaying, this study proposes an optimized prediction algorithm based on an integration of the extended Kalman filter (EKF) and an improved particle filter (IPF), built upon initial apple detection and recognition using YOLOv8. …”
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Boosting skin cancer diagnosis accuracy with ensemble approach by Priya Natha, Sivarama Prasad Tera, Ravikumar Chinthaginjala, Safia Obaidur Rab, C. Venkata Narasimhulu, Tae Hoon Kim

“…Moreover, feature vectors that were optimally produced from image data by a Genetic Algorithm (GA) were given to the ML models. …”
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Physically-constrained evapotranspiration models with machine learning parameterization outperform pure machine learning: Critical role of domain knowledge. by Yeonuk Kim, Monica Garcia, T Andrew Black, Mark S Johnson

“…We found a strong correlation (r = 0.93) between the sensitivity of ET estimates to machine-learned parameters and model error (root-mean-square error; RMSE), indicating that reduced sensitivity minimizes error propagation and improves performance. …”
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Centralized Measurement Level Fusion of GNSS and Inertial Sensors for Robust Positioning and Navigation by Mohamed F. Elkhalea, Hossam Hendy, Ahmed Kamel, Ashraf Abosekeen, Aboelmagd Noureldin

“…The experimental results clearly illustrate the considerable improvements achieved by the recommended tightly coupled (TC) algorithm when integrated with MDDA, in contrast to the loosely coupled (LC) algorithm. …”
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Generalizability of machine learning models for diabetes detection a study with nordic islet transplant and PIMA datasets by Dinesh Chellappan, Harikumar Rajaguru

“…Researchers utilizing a hybrid feature extraction method such as Artificial Bee Colony (ABC) and Particle Swarm Optimization (PSO) followed by metaheuristic feature selection algorithms as Harmonic Search (HS), Dragonfly Algorithm (DFA), Elephant Herding Algorithm (EHA). …”
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Masks-to-Skeleton: Multi-View Mask-Based Tree Skeleton Extraction with 3D Gaussian Splatting by Xinpeng Liu, Kanyu Xu, Risa Shinoda, Hiroaki Santo, Fumio Okura

“…Furthermore, we use a minimum spanning tree (MST) algorithm during the optimization loop to regularize the graph to a tree structure. …”
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A single-snapshot inverse solver for two-species graph model of tau pathology spreading in human Alzheimer’s disease by Zheyu Wen, Ali Ghafouri, George Biros, the Alzheimer’s Disease Neuroimaging Initiative (ADNI)

“…This optimization problem is solved with a projection-based quasi-Newton algorithm. …”
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Development of a machine learning-based surrogate model for friction prediction in textured journal bearings by Yujun Wang, Georg Jacobs, Shuo Zhang, Benjamin Klinghart, Florian König

“…This enhancement is achieved through an architecture design based on cross-validation and further optimization utilizing the genetic algorithm. Eventually, the average prediction accuracy is improved to 98.81% from 95.89%, with the maximum error reduced to 3.25% from 13.17%. …”
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Joint source–channel rate allocation with unequal error protection for space image transmission by Dan Dong, Shaohua Wu, Dongqing Li, Jian Jiao, Chanjuan Ding, Qinyu Zhang

“…This separate design, although simple to be implemented, cannot explore the transmission performance to the most. In this article, we propose a joint source–channel rate allocation framework to improve the space image transmission performance. …”
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Adaptive DBP System with Long-Term Memory for Low-Complexity and High-Robustness Fiber Nonlinearity Mitigation by Mingqing Zuo, Huitong Yang, Yi Liu, Zhengyang Xie, Dong Wang, Shan Cao, Zheng Zheng, Han Li

“…In this paper, an improved A-DBP algorithm with long-term memory (LTM) is proposed, employing root mean square propagation (RMSProp) to achieve low-complexity and high-robustness compensation performances. …”
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Rethinking Exploration and Experience Exploitation in Value-Based Multi-Agent Reinforcement Learning by Anatolii Borzilov, Alexey Skrynnik, Aleksandr Panov

“…We aim to optimize a deep MARL algorithm with minimal modifications to the well-known QMIX approach. …”
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Predictive modeling of hydrogen production and methane conversion from biomass-derived methane using machine learning and optimisation techniques by Adegboyega Bolu Ehinmowo, Bright Ikechukwu Nwaneri, Joseph Oluwatobi Olaide

“…In this study, the integration of various machine learning algorithms with Bayesian optimisation, firefly algorithm, Levenberg-Marquardt, and differential evolution techniques were investigated for hydrogen production via thermocatalytic methane decomposition. …”
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