Joint fusion of sequences and structures of drugs and targets for identifying targets based on intra and inter cross-attention mechanisms by Xin Zeng, Guang-Peng Su, Wen-Feng Du, Bei Jiang, Yi Li, Zi-Zhong Yang

“…Furthermore, MM-IDTarget incorporates the physicochemical features of drug and target, utilizing fully connected networks to predict drug-target interactions (DTI). …”
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Real-Time Monitoring and Simulation of Multi-User Electricity Metering Anomaly Data Based on Distributed System by Kai Liu, Xuchao Jia, Junlong Wang, Xun Ma, Jiadong Li

“…The framework facilitates the extraction of features from multi-source data, generated by users’ electricity consumption behavior, via VAE, while LSTM conducts a meticulous time-series analysis of these features to enable high-precision anomaly detection in complex datasets. …”
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Formalization for Subsequent Computer Processing of Kara Sea Coastline Data by Daria Bogatova, Stanislav Ogorodov

“…By continually refining neural network models with these datasets, we can improve our understanding of the complex interactions between natural factors and shoreline evolution, ultimately aiding in developing effective coastal management strategies.…”
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Deep Learning Image Compression Method Based On Efficient Channel-Time Attention Module by Xiu Ji, Xiao Yang, Zheyu Yue, Hongliu Yang, Boyang Zheng

“…Notably, evaluations on the STN PLAD dataset show that ETAM better preserves fine-grained details and textures, even under high compression ratios, resulting in reconstructions that closely resemble the original images.These findings underscore the practical potential of the ETAM method for efficient, high-quality image compression in real-world applications such as transmission line monitoring under constrained network conditions.…”
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Automated extraction and summarization of wind disaster data using deep learning models, with extended applications to seismic events by Huy Pham, Monica Arul

“…The performance of the framework is assessed using reconnaissance reports published by the Structural Extreme Events Reconnaissance (StEER), part of the Natural Hazards Engineering Research Infrastructure (NHERI) network. Particularly, the initial evaluation is conducted with the 2022 Hurricane Ian report. …”
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Day-Ahead Energy Price Forecasting with Machine Learning: Role of Endogenous Predictors by Chibuike Chiedozie Ibebuchi

“…Hourly DAEP data from the California Independent System Operator (January 2017 to July 2023) were integrated with exogenous and engineered endogenous features. A custom rolling window cross-validation, with 24 h validation blocks sliding daily across 2372 folds, evaluates an Extreme Gradient Boosting (XGBoost) model’s performance under diverse market conditions, achieving a median mean absolute error of 6.26 USD/MWh and root mean squared error of 8.27 USD/MWh, with variability reflecting market volatility. …”
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Research on the Prediction of the Operational Risk Field of Intelligent Vehicles Based on Dual Multiline LiDAR by Ruibin Zhang, Yingshi Guo, Chang Wang, Yang Zhou, Yunze Long

“…The real-time point cloud information is used to obtain the time-sequence bird’s-eye view and range image. The improved VGG19 network model is used to extract the time-sequence high-level abstract combined features in the multiview scene. …”
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Contrastive learning-driven framework for neuron morphology classification by Yikang Jiang, Hao Tian, Quanbing Zhang

“…To address this, we propose PRT-net, a network architecture specifically designed for neuron morphology classification. …”
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PatentGrapher: A PLM-GNNs Hybrid Model for Comprehensive Patent Plagiarism Detection Across Full Claim Texts by Yongluo Shen, Zexi Lin

“…To overcome the limitations of existing models in handling the extended textual features of patent claim documents, this research presents the PatentGraph model, which integrates Pretrained Language Model (PLM) with Graph Neural Networks (GNNs). …”
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Artificial intelligence medical image-aided diagnosis system for risk assessment of adjacent segment degeneration after lumbar fusion surgery by Bin Dai, Xinyu Liang, Yan Dai, Xintian Ding

“…Then, the similarity matrix is weighted to achieve the complementarity of multi-modal information, and the stability of feature extraction is improved through the residual network structure. …”
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Optimized CNN-Bi-LSTM–Based BCI System for Imagined Speech Recognition Using FOA-DWT by Meenakshi Bisla, Radhey Shyam Anand

“…The designed CNN consists of one-dimensional (1-D) convolutional layers and max pooling layers for familiarizing local associations along with mining hierarchical connections, and the Bi-LSTM network acquires long-term dependencies from the features learned by the former CNN. …”
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Nosocomial meningitis diagnostic test characteristics: a systematic review by David Granton, Joseph Brown, Shannon M. Fernando, Dipayan Chaudhuri, Isaac I. Bogoch, Christine Soong, Marina Englesakis, Bram Rochwerg, Eddy Fan

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Learning Arabic Reading Skills Based on E-Learning Using SIKULI during the Covid-19 Pandemic by Budi Santoso Wibowo, Widiya Yul, Riko Andrian

“…The results showed that there were three steps taken by lecturers in implementing e-Learning-based Arabic reading skills using SIKULI, namely: (1) pre-learning, (2) implementation of learning, and (3) evaluation of learning. Researchers also found several advantages of implementing e-Learning-based Arabic reading skills using SIKULI, namely: (1) assisting the internal quality assurance system (SPMI) through monitoring and evaluation, (2) practical and flexible, (3) providing supporting features and menus. …”
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Benchmark dataset on feeding intensity of the pearl gentian grouper(Epinephelus fuscoguttatus♀×E. lanceolatus♂) by Haijing Qin, Yunchen Tian, Jianing Quan, Xueqi Cong, Qingfei Li, Jinzhu Sui

“…In addition, training on this benchmark dataset proposes an improved feeding intensity evaluation network, which achieves a good balance in prediction accuracy and parameter memory and offers the possibility of subsequent deployment of the model on mobile. …”
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Identifying Research Trends, Active Research Areas and Pivotal Publications with Co-citation Analysis in CiteSpace: A Case Study with Active Matter by Yuening Zhang

“…Recent studies have revealed that research support has been evolving from traditional citation analysis to advanced library services such as research field trend/frontiers analysis and talent evaluation. Using a powerful bibliometric tool CiteSpace and “active matter” as an example, co-citation network analysis illustrates how to identify research trends, active research areas, and intellectual turning point publications. …”
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A Deep Learning-Based Echo Extrapolation Method by Fusing Radar Mosaic and RMAPS-NOW Data by Shanhao Wang, Zhiqun Hu, Fuzeng Wang, Ruiting Liu, Lirong Wang, Jiexin Chen

“…Moreover, the SSIM of the MR-DCGAN models demonstrates a more gradual decline and maintains higher overall values, indicating superior capability in preserving echo structural features. Meanwhile, the comparative experiments demonstrate that the MR-DCGAN (<i>u</i>, <i>v</i> + rh) model outperforms the MR-ConvLSTM (<i>u</i>, <i>v</i> + rh) model in terms of evaluation metrics. …”
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MFF: A Deep Learning Model for Multi-Modal Image Fusion Based on Multiple Filters by Yuequn Wang, Zhengwei Li, Jianli Wang, Leqiang Yang, Bo Dong, Hanfu Zhang, Jie Liu

“…This study proposes a multi-modal image fusion deep network called the MFF network. Compared with traditional image fusion models, the MFF network decomposes high-frequency features more finely. …”
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Technology and practice for efficient development of coalbed methane horizontal wells in high-rank coal of Qinshui Basin by WU Xi

“…Investigations into microstructures, coal body structures, in-situ stresses, and fractures—combined with an evaluation of various geological factors’ impact on production—enabled a multidimensional division of development units to identify the geological features of each unit. …”
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DIGITAL ECOSYSTEMS AS A DRIVER OF BUSINESS LANDSCAPE TRANSFORMATION IN THE MODERN ECONOMY by Ganna Kolomiyets, Vladуslav Korol, Dmуtro Bilіanskiy

“… The article defines the features of the ecosystem business model, reveals the importance and role of digital ecosystems in the evolution of the digital economy and sustainable development. …”
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Combining Supervised and Reinforcement Learning to Build a Generic Defensive Cyber Agent by Muhammad Omer Farooq, Thomas Kunz

“…Our results demonstrate that the proposed framework successfully trains a generic blue agent that can defend against different types of red agents across various network topologies. The framework demonstrates consistently improved performance over a range of existing methods, as validated through extensive empirical evaluation. …”
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