Further N-Frame networking dynamics of conscious observer-self agents via a functional contextual interface: predictive coding, double-slit quantum mechanical experiment, and decis... by Darren J. Edwards

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Median interacted pigeon optimization-based hyperparameter tuning of CNN for paddy leaf disease prediction by Jasmy Davies, S. Sivakumari

“…To address the unpredictable synergistic effects of multiple viruses co-infecting rice plants and detect co-infections of various viruses, a novel Dynamic Bayesian Adaptive Aesthetic Learning (DBAAL) is proposed, which highly assists in improving the prediction of viral infections in paddy leaves. …”
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Optimizing 5G resource allocation with attention-based CNN-BiLSTM and squeeze-and-excitation architecture by Anfal Musadaq Rayyis, Mohammad Maftoun, Maryam Khademi, Emrah Arslan, Silvia Gaftandzhieva

“…Furthermore, it attains an R2 score of 0.9964 and an Explained Variance Score (EVS) of 0.9966, confirming its ability to capture key patterns in the dataset.DiscussionCompared to conventional machine learning models and related studies, the proposed framework consistently outperforms existing approaches, highlighting the potential of deep learning in enhancing 5G networks for adaptive resource allocation in wireless systems. …”
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kMoL: an open-source machine and federated learning library for drug discovery by Romeo Cozac, Haris Hasic, Jun Jin Choong, Vincent Richard, Loic Beheshti, Cyrille Froehlich, Takuto Koyama, Shigeyuki Matsumoto, Ryosuke Kojima, Hiroaki Iwata, Aki Hasegawa, Takao Otsuka, Yasushi Okuno

“…Its key features include state-of-the-art model architectures, Bayesian optimization, explainability, and federated learning mechanisms. …”
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A Proactive Complex Event Processing Method for Large-Scale Transportation Internet of Things by Yongheng Wang, Kening Cao

“…Based on a multilayered adaptive dynamic Bayesian model, a Bayesian network structure learning algorithm using search-and-score is proposed to support accurate predictive analytics. …”
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Privacy-Preserving Federated Class-Incremental Learning by Jue Xiao, Xueming Tang, Songfeng Lu

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Triple equivalence for the emergence of biological intelligence by Takuya Isomura

“…Consequently, canonical neural networks can biologically plausibly perform variational Bayesian inferences of external Turing machines. …”
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Hyperspectral Imaging for Non-Destructive Moisture Prediction in Oat Seeds by Peng Zhang, Jiangping Liu

“…Subsequently, a dual-optimized neural network model, termed Bayes-ASFSSA-BP, was developed by incorporating Bayesian optimization and the Adaptive Spiral Flight Sparrow Search Algorithm (ASFSSA). …”
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Intelligent Dynamic Trajectory Planning of UAVs: Addressing Unknown Environments and Intermittent Target Loss by Zhengpeng Yang, Suyu Yan, Chao Ming, Xiaoming Wang

“…Specifically, the system employs a bidirectional Temporal Convolutional Network (TCN) and Gated Recurrent Unit (GRU) network algorithm with an adaptive attention mechanism (BITCN-BIGRU-AAM) to train a model that incorporates the historical motion trajectory features of the target and motion intention the inferred by a Dynamic Bayesian Network (DBN). …”
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An approach to measuring language-specific brain function in developmental language disorder by Caroline Larson, Jason C. Crutcher, Hannah R. Thomas, Michael C. Stevens

“…This methodological study began characterizing language-specific brain function by administering the adaptive semantic matching paradigm during functional magnetic resonance imaging (fMRI) to individuals with DLD and by using a Bayesian analytical approach appropriate for small clinical samples. …”
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Investigation of Artificial Intelligence Techniques for the Management of Cataract Disease: A Systematic Review by Zahra Karbasi, Michaeel Motaghi Niko, Maryam Zahmatkeshan

“…Machine learning algorithms such as logistic regression, random forest, artificial neural network, decision tree, K1-nearest neighbor, XGBoost, and adaptive boosting also played a role in cataract prediction. …”
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Data-Driven Dynamic Optimization for Hosting Capacity Forecasting in Low-Voltage Grids by Md Tariqul Islam, M. J. Hossain, Md Ahasan Habib

“…The sustainable integration of Distributed Energy Resources (DER) with the next-generation distribution networks requires robust, adaptive, and accurate hosting capacity (HC) forecasting. …”
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Human intergroup coordination in a hierarchical multi-agent sensorimotor task arises from concurrent co-optimization by Gerrit Schmid, Daniel A. Braun

“…In contrast, model-based approaches can be shown to generalize to larger groups and more complex network structures in evolutionary simulations. Our findings highlight the importance of internal models and concurrent co-optimization in facilitating adaptive coordination, offering insights into distributed information processing mechanisms.…”
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Design of an Iterative AI-Driven Latency Prediction and QoS-Aware Task Scheduling in Mobile Edge Computing: A Federated and Reinforcement Learning Process by Sharma Garima, Khare Rashi, Kulkarni Neha, Pagare Sanjay, Tiwari Vanshika

“…The tremendous upsurge of latency-sensitive applications in Mobile Edge Computing (MEC), thus requiring an efficient task scheduler depending on precise and adaptive latency prediction. The traditional latency estimation models predict the latency using either a static or heuristic-based approach whose shortcoming is overlooking the dynamic changes in network conditions, available resources, and task characteristics. …”
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Hybrid Method for Oil Price Prediction Based on Feature Selection and XGBOOST-LSTM by Shucheng Lin, Yue Wang, Haocheng Wei, Xiaoyi Wang, Zhong Wang

“…Third, low-frequency modes are predicted through an Attention Mechanism-based Long and Short-Term Memory Neural Network (AM-LSTM), optimized using Bayesian Optimization and Hyperband (BOHB). …”
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Process Importance Identification for the SPAC System Under Different Water Conditions: A Case Study of Winter Wheat by Lijun Wang, Liangsheng Shi, Jinmin Li

“…To address this gap, this study proposes a process sensitivity analysis method that integrates the Bayesian network with variance-based sensitivity measures. …”
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A Robust Resilience Methodology for Tacking Safety of Hydrogen Refueling Stations by Chao Chen, Zihan Lu, Ruixuan Ge, Yanjun Chen, Xinxin Tan, Li Mo

“…A Dynamic Bayesian Network (DBN)-based methodology is developed to probabilistically assess the resilience of a hydrogen refueling station by incorporating the time course of adaptation and restoration into the analysis of system function. …”
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Leveraging uncertainty in collective opinion dynamics with heterogeneity by Vito Mengers, Mohsen Raoufi, Oliver Brock, Heiko Hamann, Pawel Romanczuk

“…By quantifying and updating the uncertainty using Bayesian inference, we provide a mechanism for each agent to adaptively weigh their individual against social information. …”
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Determining Point of Economic Cattle Milk Production through Machine Learning and Evolutionary Algorithm for Enhancing Food Security by Sonam Bhardwaj, Ayon Tarafdar, Manoj Baghel, Triveni Dutt, Gyanendra Kumar Gaur

“…Three distinct artificial neural network (ANN) algorithms, namely, Levenberg–Marquardt (LM), Bayesian regularization (BR), and gradient descent momentum with adaptive learning rate backpropagation (GDX) were used to train the ANN infrastructure for determining milk production and investment based on body weight and AFC as input variables. …”
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Harnessing Machine Learning for Predictive Analysis of Crop Resistance to Extreme Weather Conditions by Pan Susovan Kumar, Shivaj Ghorpade Bipin

“…Adaptive decision making strategies are developed using deep Q-Networks (DQN) which enable adaptivity with respect to changes in environment conditions. …”
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