Medical Image Segmentation Algorithm Based on Optimized Convolutional Neural Network-Adaptive Dropout Depth Calculation by Feng-Ping An, Jun-e Liu

“…At the same time, to solve the generalizability problem of the deep learning model, an adaptive distribution function is designed according to the position of the hidden layer, and then the activation probability of each layer of neurons is set. …”
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Indefinite Kernel Network with lq-Norm Regularization by Zhongfeng Qu, Hongwei Sun

“…The framework under investigation is different from classical kernel learning. Positive semidefiniteness is not required by the kernel function. …”
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Adults’ locus educanti. The example of science and technology parks by Marcin Rojek

“…Adult learning experiences can happen anywhere. Everywhere does not mean "anywhere", but rather "somewhere", that is in places conducive to education, although not originally intended for this function. …”
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Multi-protective effects of wheat embryo globulin on D-gal-induced aging mice by Aimei Liaoa, Xing Lyu, Jiarui Ma, Yinchen Hou, Ming Hui, Na Liu, Yi Zhao, Yixiang Cui, Jihong Huang

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Temporal ablation of the ciliary protein IFT88 alters normal brainwave patterns by Matthew R. Strobel, Yuxin Zhou, Liyan Qiu, Aldebaran M. Hofer, Xuanmao Chen

“…And additionally, inducible IFT88 KO mice had altered sleep architecture and attenuated phase-amplitude coupling, a process that underlies learning and memory formation. These results highlight the growing significance of primary cilia for healthy neural function in the adult brain.…”
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Mi-DETR: For Mitosis Detection From Breast Histopathology Images an Improved DETR by Fatma Betul Kara Ardac, Pakize Erdogmus

“…Additionally, a more stable model has been obtained by using the CIoU loss function instead of the L1+GIoU loss function used in the DETR model. …”
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FSE-RBFNN-Based AILC of Finite Time Complete Tracking for a Class of Time-Varying NPNL Systems with Initial State Errors by Chunli Zhang, Lei Yan, Yangjie Gao

“…Addressing the difficulty of nonlinear parameterization terms in system models, a new function approximator (FSE-RBFNN) which is combined with radial basis function neural network (RBFNN) and Fourier series expansion (FSE) is introduced to model each time-varying nonlinear parameterization function. …”
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SOMO-m Optimization Algorithm with Multiple Winners by Wei Wu, Atlas Khan

“…In particular, Su and Zhao proposes in (2009) an SOM-based optimization (SOMO) algorithm in order to find a wining neuron, through a competitive learning process, that stands for the minimum of an objective function. …”
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Binocular coordination of saccades: development, aging and cerebral substrate by Zoë Kapoula, Marine Vernet, Qing Yang, Maria Pia Bucci

“…The origin of binocular coordination of saccades (central, peripheral) and the role of learning remain controversial (Hering vs Helmholtz). …”
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Design and Construction of Multimedia Smart English Teaching Platform Based on RBF Algorithm by Qianbo Li

“…Through teaching and learning, the students can become the main entity in the English teaching, which can stimulate their enthusiasm and form a good awareness for English learning. …”
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Advanced Differential E-Module: Integrating Case-Based and Visual Exploration by Bertu Rianto Takaendengan, Agusyarif Rezka Nuha, Taulia Damayanti, Asriadi, Miftahul Janna, Fitriana Anggraini

“… One of the main challenges in learning advanced calculus is students' difficulty understanding complex concepts and visualizing function graphs, especially in learning partial derivatives. …”
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Management of Physical Education Facilities and Infrastructure by Citra Dewi, Desrio Windoro, Dwi Naomi Pura

“…Second, the provision of learning facilities is carried out by prioritizing function (utility), which refers to the facility's usefulness—related to the real needs of the school. …”
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Towards solving NLP tasks with optimal transport loss by Rishabh Bhardwaj, Tushar Vaidya, Soujanya Poria

“…Such functions play a vital role in machine learning algorithms as they steer the learning process. …”
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Comparing cognitive impairment using MACFIMS in patients with multiple sclerosis and healthy controls: a systematic review and meta-analysis by Amirreza Nasirzadeh, Mohammad Mohammadi, Melika Arab Bafrani, Aynaz Mohammadi, Hossein Bakhtiari-Dovvombaygi

“…Abstract Background Multiple sclerosis (MS) is a chronic autoimmune disorder affecting the central nervous system, leading to a range of symptoms that impact physical, psychiatric, and cognitive functions. Cognitive dysfunction is prevalent among patients with MS (pwMS), affecting at least 65% of patients, and includes deficits in processing speed, attention, learning, memory, and executive function. …”
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Adaptive Compensatory Neurophysiological Biomarkers of Motor Recovery Post-Stroke: Electroencephalography and Transcranial Magnetic Stimulation Insights from the DEFINE Cohort Stud... by Guilherme J. M. Lacerda, Fernanda M. Q. Silva, Kevin Pacheco-Barrios, Linamara Rizzo Battistella, Felipe Fregni

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Convergence of an Online Split-Complex Gradient Algorithm for Complex-Valued Neural Networks by Huisheng Zhang, Dongpo Xu, Zhiping Wang

“…We choose an adaptive learning rate during the training procedure. Under certain conditions, by firstly showing the monotonicity of the error function, it is proved that the gradient of the error function tends to zero and the weight sequence tends to a fixed point. …”
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An Image Segmentation by BFV and TLBO by Mohammad Heidari

“…Afterward, the LPI can be adjusted based on fitness function, namely, the evaluation standards of image quality. …”
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Intelligent Microfluidics Research on Relative Permeability Measurement and Prediction of Two-Phase Flow in Micropores by Hongqing Song, Changchun Liu, Junming Lao, Jiulong Wang, Shuyi Du, Mingxu Yu

“…On the other hand, tanh() activation function performed 40% more accurate than the sigmoid() activation function.…”
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MSSA: multi-stage semantic-aware neural network for binary code similarity detection by Bangrui Wan, Jianjun Zhou, Ying Wang, Feng Chen, Ying Qian

“…Current state-of-the-art approaches are based on Transformer, which require substantial computation resources. Learning-based approaches remains room for optimization in learning the deeper semantics of binary code. …”
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A Smoothing Interval Neural Network by Dakun Yang, Wei Wu

“…In this paper, a smoothing interval neural network is proposed to prevent the weights oscillation during the learning procedure. Here, by smoothing we mean that, in a neighborhood of the origin, we replace the absolute values of the weights by a smooth function of the weights in the hidden layer and output layer. …”
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