A Review of Gas Flow and Its Mathematical Models in Shale Gas Reservoirs by Bo-ning Zhang, Xiao-gang Li, Yu-long Zhao, Cheng Chang, Jian Zheng

“…The gas transport mechanisms in shale gas reservoirs are complicated, due to the multiple types of pores with complex pore structure and special process of gas accumulation and transport. Although there have been many attempts to come up with a suitable and practical mathematical model to characterize the shale gas flow process, no unified model has yet been accepted by academia. …”
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Label-Efficient Fine-Tuning for Remote Sensing Imagery Segmentation with Diffusion Models by Yiyun Luo, Jinnian Wang, Jean Sequeira, Xiankun Yang, Dakang Wang, Jiabin Liu, Grekou Yao, Sébastien Mavromatis

“…To address these challenges, we introduce Denoising Diffusion Probabilistic Models (DDPMs) as a generative pre-training approach for semantic features extraction in remote sensing imagery. …”
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Construction of Legal Knowledge Graph Based on Knowledge-Enhanced Large Language Models by Jun Li, Lu Qian, Peifeng Liu, Taoxiong Liu

“…Taking the automated construction of the Chinese legal knowledge graph (CLKG) as a case scenario, this paper presents a joint knowledge enhancement model (JKEM), where prior knowledge is embedded into a large language model (LLM), and the LLM is fine-tuned through the prefix of the prior knowledge data. …”
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HybNet: A hybrid deep models for medicinal plant species identification by B.R. Pushpa, S. Jyothsna, S. Lasya

“…The third model incorporates MobileNetV2 with the Squeeze and Excitation (SE) layers for the classification tasks. …”
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Disc Degeneration in Direct Injury or Instability Models Share Common Metabolic Pathways by Matthew Goodwin

“…Methodology: Four models of disc degeneration were studied: (i) lumbar disc poke, (ii) tail disc poke, (iii) spinal instability, and (iv) sham. …”
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Development of a Multi‐Scale Meteorological Large‐Eddy Simulation Model for Urban Thermal Environmental Studies: The “City‐LES” Model Version 2.0 by Hiroyuki Kusaka, Ryosaku Ikeda, Takuto Sato, Satoru Iizuka, Taisuke Boku

“…Noteworthy features of this model include: (a) the calculation of long‐ and short‐wave radiations in three dimensions, incorporating multiple reflections within urban canopy layers using the radiosity method, and accounting for building and tree shadows in the simulations; (b) the provision of various heat stress indices (Universal Thermal Climate Index, Wet Bulb Globe Temperature, MRT, THI); (c) the assessment of the efficacy of heat stress mitigation measures such as dry‐mist spraying, roadside trees, cool pavements, and green/cool roofs strategies; (d) the capability to run on supercomputers, with the code parallelized in a three‐dimensional manner, and the model can also run on a graphics processing unit cluster. …”
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Advancing Skin Disease Diagnosis: A Multimodal Approach Utilizing Telegram Api Token Chatbot for Text and Image Analysis in Skin Disease Classification by Modigari Narendra, T. S. Harshini, L. Jani Anbarasi

“…This study aims to develop a skin disease classification system using a multimodal approach, integrating ensemble methodology using DenseNet169 – Resnet50 ensemble Transfer learning models, and Natural Language Processing (NLP) within a Telegram chatbot interface. …”
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Extracting Optimal Number of Features for Machine Learning Models in Multilayer IoT Attacks by Badeea Al Sukhni, Soumya K. Manna, Jugal M. Dave, Leishi Zhang

“…Additionally, the complete reliance on automated processes without integrating human expertise in feature selection and weighting processes may affect the reliability of detection models. …”
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Histomorphometric and Microscopic Assessment of Gastric Mucosa in Guinea pig and White Rat Models by Omar Younis Altaet, Ali Ahmed Hasan, Shahad Amer Rajab, Alaa Maan Jebur

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A Conceptual Framework for a Latest Information-Maintaining Method Using Retrieval-Augmented Generation and a Large Language Model in Smart Manufacturing: Theoretical Approach and... by Hangseo Choi, Jongpil Jeong

“…The proposed framework design uses a data stream processing layer, a data integration layer, and a continuous learning layer as core components; in particular, the knowledge integration layer provides a mechanism for the efficient processing of real-time data and continuous learning. …”
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TIM-FEM-ML synthetic technology for longitudinal optimization of tunnel excavated in the interlayered rock mass by Hui Li, Weizhong Chen, Xiaoyun Shu, Xianjun Tan, Qun Sui

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Chinese Sequence Labeling Based on Stack Pre-training Model by LIU Yu-peng, LI Guo-dong

“…Sequence labeling is an important task in natural language processing. In this paper, according to the relevance of tasks, we use stacking pretraining model to extract features, segment words, and name entity recognition/chunk tagging.Through in-depth research on the internal structure of BERT, while ensuring the accuracy of the original model, the Bidirectional Encoder Representation from Transformers （BERT） is optimized, which reduces the complexity and the time cost of the model in the training and prediction process.In the upper layer structure, compared with the traditional long-short-term memory network (LSTM), this paper uses a two-layer bidirectional LSTM structure, the bottom layer uses a bidirectional long-short-term memory network (Bi-LSTM) for word segmentation, and the top layer is used for sequence labeling tasks.On the New Semi-Conditional Random Field (NSCRF), the traditional semi-Markov Conditional Random Field (Semi-CRF) and Conditional Random Field (CRF) are combined while considering the segmentation.The labeling of words improves accuracy in training and decoding. …”
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Construction exploration and application prospect of the large model in mining industry by Haijun WANG

“…This paper deeply analyzes the challenges of high R&D investment cost, difficulty in collecting high-quality data, and high difficulty in multimodal data fusion technology in the application of large model technology in the coal industry, and summarizes in detail the construction path and phased results achieved by SolStone Mine Large Model to cope with the above challenges from six aspects: infrastructure layer, data resource layer, algorithm model layer, application service layer, security and trustworthiness and testing layer, and industry ecological layer, and finally looks forward to the production and technological changes brought by the development of large model technology to the coal industry. …”
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Earthwork Network Architecture (ENA): Research for Earthwork Quantity Estimation Method Improvement with Large Language Model by Taewook Kang, Kyubyung Kang

“…This study introduces the Earthwork Network Architecture (ENA), a novel deep learning framework that incorporates Large Language Models (LLMs), Multi-Layer Perceptron (MLP), Long Short-Term Memory (LSTM) networks, and Transformers to automate and enhance the accuracy of earthwork quantity estimation. …”
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Automated vacuum drying kinetics, thermodynamics, and economic analysis of sage leaves by Nabil Eldesokey Mansour, Khaled A. Metwally, Aml Abubakr Tantawy, Ahmed Elbeltagi, Ali Salem, Ahmed Z. Dewidar, Abdelaziz M. Okasha, Moustapha Eid Moustapha, Abdallah Elshawadfy Elwakeel

“…The Page model was identified as the most suitable for describing the thin-layer drying behavior. …”
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Unsupervised intrusion detection model based on temporal convolutional network by LIAO Jinju, DING Jiawei, FENG Guanghui

“…Most existing intrusion detection models rely on long short-term memory (LSTM) networks to consider time-dependencies among data. …”
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Study on the effects of initial ice layer and temperature distribution on the redistribution of D2 fuel layer in a cryogenic target by Yina Yao, Guanhua Chen, Wei Lin, Kai Wang, Hui Zhang, Fei Dai

“…The effects of the temperature boundary and the initial ice layer distribution on the coupled process are investigated. …”
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JAX‐CanVeg: A Differentiable Land Surface Model by Peishi Jiang, Patrick Kidger, Toshiyuki Bandai, Dennis Baldocchi, Heping Liu, Yi Xiao, Qianyu Zhang, Carlos Tianxin Wang, Carl Steefel, Xingyuan Chen

“…Differentiable modeling provides a new opportunity to capture these complex interactions by seamlessly hybridizing process‐based models with deep neural networks (DNNs), benefiting both worlds, that is, the physical interpretation of process‐based models and the learning power of DNNs. …”
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Neural network based AI model for lung health assessment by Umaisa Hassan, Amit Singhal, Gunjan Gupta

“…The NN architecture consists of three fully connected layers and an output layer for classification. Our proposed approach attains 100% accuracy, specificity, and sensitivity, performing consistently well across all four datasets, which highlights the model’s strong generalizability. …”
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Feature-adaptive anomaly detection model for onion inspection system by Ziwei Song, Prawit Buayai, Koji Makino, Xiaoyang Mao

“…The VBIM introduces a new feature-adaptive anomaly detection method, which optimizes feature layer weights in a student-teacher anomaly detection model. …”
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