Potato precision planter metering system based on improved YOLOv5n-ByteTrack by Cisen Xiao, Changlin Song, Junmin Li, Min Liao, Yongfan Pu, Kun Du

“…The experimental results indicate that: 1) The improved YOLOv5n model exhibits a 56.8% reduction in parameters, a 56.1% decrease in giga floating point operations per second (GFLOPs), a 51.4% reduction in model size, and a 37.0% reduction in Embedded Device Inference Time compared to the YOLOv5n model. …”
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Consumer Happiness in the Purchase of Electric Vehicles: a Fuzzy Logic Model by Fernando Lámbarry-Vilchis, Aboud Barsekh Onji, Leticia Refugio Chavarría López, Paola Judith Maldonado Colín

“…This research was conducted using a fuzzy Delphi method survey targeting a specific consumer group and two fuzzy inference systems: a multi-input single-output FIS model and an FIS Tree employing a hierarchical fuzzy inference structure, which leverages the survey's training data to optimize the models using different machine learning algorithms. The FIS tree model demonstrated superior efficacy in predicting the consumer satisfaction index, achieving an average forecast error of 0.65%. …”
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Removal mechanism and damage evolution of SiCp/Al composites based on FEM-MD model considering 3D random polyhedral particles in orthogonal cutting by Ming Li, Qingguang Li, Xianchao Pan, Jiaqi Wang, Zixuan Wang, Shengzhi Xu, Yunguang Zhou, Lianjie Ma, Tianbiao Yu

“…Experimental validation confirmed the multi-scale model's predictive accuracy for machining-induced surface damage. …”
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Simultaneous replacement of the aortic valve and hip joint in a patient with critical aortic stenosis and femoral neck fracture by S. V. Petrov, A. S. Peleshok, V. L. Ignatenko, O. M. Mutalibov, V. A. Krivopalov, G. G. Khubulava, N. G. Pilyugov

“…Developing the treatment algorithm for a combination of two or more diseases in this category of patients is the main task. …”
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Fatigue Damage Prognosis Method for Main Girders of Cable-Stayed Bridges Based on Wavelet Neural Network by Shan Huang, Rui Chen, Jun Ling, Nan Jin

“…This method integrates WNN with multi-scale finite element modeling to predict fatigue damage progression. First, the theoretical foundation and implementation algorithms of the WNN are elaborated on and applied to forecast the future load environments of cable-stayed bridges. …”
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Improving Balanced Accuracy for Minority Plant Species under Data Imbalance by Ruben Gonzalez-Villanueva, Jose Carranza-Rojas

“…Regardless of the widely known success of deep learning in classification, such models are commonly measured by metrics that do not account for data imbalance, especially in terms of predictions per class, ignoring minority classes. This can be a problem, as minority classes are often the most difficult to predict and collect data for. …”
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Enactivism, Health, AI, and Non-Neurotypical Individuals: Toward Contextualized, Personalized, and Ethically Grounded Interventions by Jordi Vallverdú

“…Drawing on relevant philosophical literature, empirical studies, and cross-disciplinary debates (including the friction and potential synergies between predictive processing and enactivism), we argue that AI solutions grounded in enactivist thinking can more effectively honor user autonomy, acknowledge the embodied nature of neurodiverse cognition, and avoid reductive standardizations. …”
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Educational improvement through machine learning: Strategic models for better PISA scores. by Bilal Baris Alkan, Serafettin Kuzucuk, Şevki Yetkin Odabasi, Leyla Karakuş

“…In this study, in addition to traditional variables such as economic wealth or the number of books read, on which many studies have already been conducted, variables that are thought to influence student achievement and better predict success are identified. Random Forest algorithm was used to identify important variables based on the PISA 2018 data, covering all three domains of science, mathematics and reading. …”
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A prognostic glycolysis-related gene signature in osteosarcoma: implications for metabolic programming, immune microenvironment, and drug response by Naiqiang Zhu, Jingyi Hou, Yu Zhang, Ning Yang, KaiKai Ding, Chengbing Chang, Yanqi Liu, Haipeng Gu, Bin Chen, Xu Wei, Liguo Zhu

“…The prognostic efficacy of this risk signature was assessed via Kaplan–Meier curve analysis and Cox regression, evaluating its independence as a prognostic indicator. Additionally, the predictive potential of the risk model for drug response was evaluated using the “OncoPredict” package. …”
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Advancements in Herpes Zoster Diagnosis, Treatment, and Management: Systematic Review of Artificial Intelligence Applications by Dasheng Wu, Na Liu, Rui Ma, Peilong Wu

“…Classification tasks (85.2%) dominated AI applications, with neural networks, particularly multilayer perceptron and convolutional neural networks being the most frequently used algorithms. AI applications were analyzed across three domains: (1) diagnosis, where mobile deep neural networks, convolutional neural network ensemble models, and mixed-scale attention-based models have improved diagnostic accuracy and efficiency; (2) treatment, where machine learning models, such as deep autoencoders combined with functional magnetic resonance imaging, electroencephalography, and clinical data, have enhanced treatment outcome predictions; and (3) management, where AI has facilitated case identification, epidemiological research, health care burden assessment, and risk factor exploration for postherpetic neuralgia and other complications. …”
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Application of PSO-Optimized Twin Support Vector Machine in Medium and Long-Term Load Forecasting under the Background of New Normal Economy by Xiang He, Yan Chen, Kai Hu, Lin Wan

“…Moreover, this paper uses the algorithm to debug the filter and studies the accurate prediction of the fine model by the progressive spatial mapping algorithm and the processing of the data by the vector fitting algorithm. …”
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Low-Rank Kernel-Based Semisupervised Discriminant Analysis by Baokai Zu, Kewen Xia, Shuidong Dai, Nelofar Aslam

“…Extensive experiments on public databases show that the proposed LRKSDA dimensionality reduction algorithm can achieve better performance than other related kernel SDA methods.…”
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Development of an Intelligent Method for Target Tracking in Radar Systems at the Initial Stage of Operation Under Intentional Jamming Conditions by Serhii Semenov, Olga Wasiuta, Alla Jammine, Justyna Golec, Magdalena Krupska-Klimczak, Yevhen Tarasenko, Vitalii Voronets, Vitalii Breslavets, Serhii Lvov, Artem Moskalenko

“…The problem lies in the lack of a comprehensive approach to tracking air targets in difficult conditions that is able to dynamically adapt filtering parameters, predict signal reliability, and change the processing mode depending on the level of interference. …”
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Modelling of River-Groundwater Interactions under Rainfall Events Based on a Modified Tank Model by Wen Nie, Yong-chang Liang, Lin Chen, Wei Shao

“…Parameter training of our tank model includes two algorithms: (i) the nonincremental learning algorithm-based model can predict the pore water pressure (PWP) in a slope and river under a 65 mm/hr rainfall event (coarse material) with Nash–Sutcliffe efficiency (NSE) = 0.427 and −0.909 and (ii) the incremental learning algorithm-based model can predict the PWP in a slope and river with NSE = 0.994 and 0.995. …”
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Identifying the Dimensions of Degraded Impact Structures Using Digital Elevation Models: A Proof of Concept for Silicate Planets by Connor J. Anderson, James B. Garvin, Devin R. McClain, Scott S. Sinno, Katherine A. Melocik, Compton J. Tucker

“…Application of these methods to additional impact structures is required to quantify prediction uncertainty before applying this methodology to more recent impact structures with questionable diameters.…”
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The authentication of Yanchi tan lamb based on lipidomic combined with particle swarm optimization-back propagation neural network by Qi Yang, Dequan Zhang, Chongxin Liu, Le Xu, Shaobo Li, Xiaochun Zheng, Li Chen

“…The results showed that particle swarm optimization-back propagation (PSO-BP) neural network had the best prediction effect, with 100 % prediction accuracy in both the training and test sets. …”
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Double array system identification research based on LSTM neural network by Chunhua Gao, Mingyang Wang, Yifei Sima, Zihan Yuan

“…This indicates that the algorithm can accurately reproduce the characteristics of the shaking table itself and shows good performance in time series prediction and data mining. …”
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What Strategy Central Nervous System Uses to Perform a Movement Balanced? Biomechatronical Simulation of Human Lifting by Ali Leylavi Shoushtari

“…The results show that the simulated postures are normal and the predicted motion is performed completely balanced.…”
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Understanding HLA-DQ in renal transplantation: a mini-review by Rajdeep Das, Neil S. Greenspan

“…Traditional serological or low-resolution typing often misclassifies mismatches, leading to inaccuracies in assessing immunogenicity and predicting outcomes. Emerging molecular mismatch algorithms refine immunogenicity assessments by analyzing amino acid differences and structural interactions. …”
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Autoregressive integrated moving average model–based secure data aggregation for wireless sensor networks by Hongtao Song, Shanshan Sui, Qilong Han, Hui Zhang, Zaiqiang Yang

“…We leverage the autoregressive integrated moving average model to predict the data volume in sensor nodes, and update and synchronize the model as needed. …”
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