A multimodal model in the prediction of the delivery mode using data from a digital twin-empowered labor monitoring system by Jieyun Bai, Xue Kang, Weishan Wang, Ziduo Yang, Weiguang Ou, Yuxin Huang, Yaosheng Lu

“…Conclusion The findings of this study suggest that the developed multimodal model is a promising tool for predicting delivery mode and provides a comprehensive approach to intrapartum maternal and fetal health monitoring. The integration of multi-source data, including real-time information, holds potential for further improving the algorithm's predictive accuracy as the volume of analyzed data increases. …”
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Design and optimization of an open personalized human-computer interaction system for New Year Painting based on the learner's model by Zaozao Guo, Muhamad Firdaus Ramli, Wenpeng Zhang

“…Firstly, the attention mechanism based long and short term memory network is used to mine the emotion from the course review text of learners, and the association rule algorithm and ID3 algorithm are used to initialize and dynamically update the text. …”
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A radiomics-clinical predictive model for difficult laparoscopic cholecystectomy based on preoperative CT imaging: a retrospective single center study by Rui-Tao Sun, Chang-Lei Li, Yu-Min Jiang, Ao-Yun Hao, Kui Liu, Kun Li, Bin Tan, Xiao-Nan Yang, Jiu-Fa Cui, Wen-Ye Bai, Wei-Yu Hu, Jing-Yu Cao, Chao Qu

“…A combination of radiomic and clinical features was selected using the Boruta-LASSO algorithm. Predictive models were constructed using six machine learning algorithms and validated, with model performance evaluated based on the AUC, accuracy, Brier score, and DCA to identify the optimal model. …”
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Dynamical behavior analysis and control of time-varying lifting system based on fuzzy adaptive back-stepping controller by Wang Lei, Cao Guohua

“…Thirdly, based on Lyapunov function, the asymptotic stability of the system under the proposed control algorithm is verified. Finally, compared with proportion–integration–differentiation (PID) back-stepping controller, the efficiency of the proposed controller is proven by applying excitation with different frequency and uncertain parameters, and the adaptability and robustness are illustrated to validate under mixed frequency disturbance by simulation compared with PID back-stepping controller. …”
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Uncovering latent biological function associations through gene set embeddings by Yuhang Huang, Fan Zhong, Lei Liu

“…In this study, we extend beyond conventional bipartite models by integrating attribute-driven knowledge from the Molecular Signatures Database (MSigDB) using the node2vec algorithm. …”
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GAT-Enhanced YOLOv8_L with Dilated Encoder for Multi-Scale Space Object Detection by Haifeng Zhang, Han Ai, Donglin Xue, Zeyu He, Haoran Zhu, Delian Liu, Jianzhong Cao, Chao Mei

“…Traditional YOLO-series algorithms encounter challenges such as poor robustness in small object detection and significant interference from complex backgrounds. …”
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Recognition of MI-EEG signals using extended-LSR-based inductive transfer learning by Zhibin Jiang, Zhibin Jiang, Keli Hu, Keli Hu, Jia Qu, Zekang Bian, Zekang Bian, Donghua Yu, Donghua Yu, Jie Zhou, Jie Zhou

“…To address this challenge, an effective strategy is to integrate transfer learning into the construction of intelligent models, allowing knowledge to be transferred from the source domain to enhance the performance of models trained in the target domain. …”
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Forecasting Tunnel-Induced Ground Settlement: A Hybrid Deep Learning Approach and Traditional Statistical Techniques With Sensor Data by Syed Mujtaba Hussaine, Linlong Mu, Yimin Lu, Syed Sajid Hussain

“…Additionally, the statistical Autoregressive Integrated Moving Average (ARIMA)/Seasonal ARIMA (SARIMA) models were enhanced through seasonality removal, automated model selection using the auto_arima algorithm, and parameter fine-tuning via grid search to improve their predictive accuracy. …”
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Deciding on the Regularity of a Planar Coons Map by Maharavo Randrianarivony, Guido Brunnett

“…We consider the construction of a regular map from the unit square to a general four-sided domain, a problem that arises in several applications, e.g., in the numerical solution of integral equations or when dealing with trimmed surfaces in CAD. …”
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From Social to Academic: Associations and Predictions Between Different Types of Peer Relationships and Academic Performance Among College Students by Jiadong Tian, Jiali Lin, Dagang Li

“…In addition, with the construction of the graph model and the integration of time-series information, the prediction accuracy of the dynamic graph convolution method improved compared to other methods. …”
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Radiomics in glioma: emerging trends and challenges by Zihan Wang, Lei Wang, Yinyan Wang

“…This review discusses the application, emerging trends, and challenges associated with using radiomics in glioma. Integrating deep learning algorithms enhances various radiomics components, including image normalization, region of interest segmentation, feature extraction, feature selection, and model construction and can potentially improve model accuracy and performance. …”
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CRYPTO-RESISTANT METHODS AND RANDOM NUMBER GENERATORS IN INTERNET OF THINGS (IOT) DEVICES by Petro Klimushyn, Tetiana Solianyk, Oleksandr Mozhaiev, Yurii Gnusov, Oleksandr Manzhai, Vitaliy Svitlychny

“…The analysis of technologies and circuit solutions allowed to draw the following conclusions: protection of IoT solutions includes: security of IoT network nodes and their connection to the cloud using secure protocols, ensuring confidentiality, authenticity and integrity of IoT data by cryptographic methods, attack analysis and network cryptographic stability; the initial basis for the protection of IoT solutions is the true randomness of the formed RNG sequences and used in algorithms for cryptographic transformation of information to protect it; feature of IoT devices is their heterogeneity and geographical distribution, limited computing resources and power supply, small size; The most effective (reduce power consumption and increase the generation rate) for use in IoT devices are RNG exclusively on a digital basis, which implements a three-stage process: the initial digital circuit, normalizer and random number flow generator; Autonomous Boolean networks (ABN) allow to create RNG with unique characteristics: the received numbers are really random, high speed – the number can be received in one measure, the minimum power consumption, miniature, high (up to 3 GHz) throughput of Boolean chaos; a promising area of ABN development is the use of optical logic valves for the construction of optical ABN with a bandwidth of up to 14 GHz; the classification of known classes of RNG attacks includes: direct cryptanalytic attacks, attacks based on input data, attacks based on the disclosure of the internal state of RNG, correlation attacks and special attacks; statistical test packages to evaluate RNG sequences have some limitations or shortcomings and do not replace cryptanalysis; Comparison of cryptoaccelerators with cryptographic transformation software shows their significant advantages: for AES block encryption algorithm, speeds increase by 10-20 times in 8/16-bit cryptoaccelerators and 150 times in 32-bit, growth hashing of SHA-256 in 32-bit cryptoaccelerators more than 100 times, and for the NMAS algorithm - up to 500 times. …”
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Developing a Local Neurofuzzy Model for Short-Term Wind Power Forecasting by E. Faghihnia, S. Salahshour, A. Ahmadian, N. Senu

“…Large scale integration of wind generation capacity into power systems introduces operational challenges due to wind power uncertainty and variability. …”
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Reading the Signs”: Aspects of Perception of a Game Polycode Text in Space of a Modern City by T. A. Gridina, N. I. Konovalova

“…The universality of the generation of game texts of any semiotic nature on the basis of an operational technique that creates the effects of associative deducibility and associative integration is substantiated. The novelty of the study is related to the description of the algorithm for creating and deciphering a game polycode text of this type, identifying the factors and strategies for reading it by the addressee. …”
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Improved High-Order Difference Scheme for the Conservation of Mass and Energy in the Two-Dimensional Spatial Fractional Schrödinger Equation by Junhong Tian, Hengfei Ding

“…Combined with the composite Simpson’s formula for numerical integration, which ensures high precision in approximating integrals, and a fourth-order numerical differential formula for discretizing the Riesz derivative, we construct a highly effective finite difference scheme. …”
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From platform provider to big-data-enabled financier: Industrial upgrading in China’s hog sector by Yuxing Zhang

“…The process constructs a feedback-loop system that embeds farming operations within the platform ecosystem, making them susceptible to data-driven, algorithm-aided control. …”
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Text classification model based on GNN and attention mechanism by ZENG Shuifei, MENG Yao, LIU Jing

“…Firstly, an inductive learning of graph neural network model was constructed, and dynamic embedding the unknown neighboring node was implemented by using an aggregation function to enhance the model’s generalization ability. …”
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One of the approaches to the organization of the modern educational process by A. G. Savenko, Yu. A. Skudnyakov

“…A visual and mathematical model, an diagram of information and educational system, an algorithm for the rotation of trainees are presented. …”
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MIDAS: A Data Aggregation Scheduling Scheme for Variable Aggregation Rate WSNs by Jun Long, An He, Jinhuan Zhang, Hao Zhang

“…The proposed MIDAS scheme integrates two core phases, namely, data aggregation set construction and aggregation set based scheduling algorithm. …”
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Application of data twinning based on deep time series model in smart city traffic flow prediction by Li Gao

“…The system construction starts from physical layer data acquisition, deals with missing data through smoothing and interpolation, and applies the GM(1,1) model to construct a digital twin layer for preliminary prediction. …”
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