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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Neural models in diagnostics of the financial result of housing and utility enterprises by I. P. Kurochkina, I. I. Kalinin, L. A. Mamatova, E. B. Shuvalova

“…Neural networks can have a complex architecture when different  parts of the  neural  network  include  different  numbers  of connections and different neurons.The  article develops  the  ideas  laid  down  by its authors  in [7,  8], where a neural network  of direct propagation and a way of learning with a teacher have already been used. The model, described below, has been modified due to the authors’ desire to improve it, as well as dictated by the specifics of the housing and utility companies: a list of key indicators has been developed that affect not the financial  result, but, consequently,  the financial  condition of companies in this sector of the Russian  economy;  the number  of input factors characterizing the input sample was increased,  each direct factor or group of direct factors was supplemented  with an indirect factor; direct and indirect factors explaining the same processes are combined  into clusters that influence  the  corresponding  neuron;  the  number  of neurons  in  the output layer has been expanded, the number of classes has been increased, the data are classified by means of the neural network in more detail; in the course of the program, it is possible to select the period to which  the input data (month, quarter,  half year,  year) belong. …”
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Adaptive Res-LSTM Attention-based Remaining Useful Lifetime Prognosis of Rolling Bearings by Boubker Najdi, Mohammed Benbrahim, Mohammed Nabil Kabbaj

“…These features are then fed into a Residual Network (ResNet) combined with a temporal attention layer, followed by a Long Short-Term Memory (LSTM) model, referred to as the Adaptive Residual Attention LSTM (ARAL), to assess the Health Indicator (HI) of the bearings. …”
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Large-Language-Model-Enabled Text Semantic Communication Systems by Zhenyi Wang, Li Zou, Shengyun Wei, Kai Li, Feifan Liao, Haibo Mi, Rongxuan Lai

“…Large language models (LLMs) have recently demonstrated state-of-the-art performance in various natural language processing (NLP) tasks, achieving near-human levels in multiple language understanding challenges and aligning closely with the core principles of semantic communication Inspired by LLMs’ advancements in semantic processing, we propose LLM-SC, an innovative LLM-enabled semantic communication system framework which applies LLMs directly to the physical layer coding and decoding for the first time. …”
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Optimal design of a hybrid system composed of coagulation process and multi-stage filtration unit for on-site treatment of greywater in rural area by Zahra Akbari, Fereshteh Nourmohammadi Dehbalaei, Zahra Mohammad Hosseini, Seyed Taghi Omid Naeeni

“…Based on the optimization-simulation model and experimental results, coagulation process followed by a filtration unit consisting of 17 cm of fine sand, 9 cm of medium sand and 34 cm of activated carbon results in the maximum efficiency and can reduce the COD and turbidity of greywater by 90.12% and 99.03%, simultaneously.…”
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Study of the Effect of Regulating Alloying Elements and Optimizing Heat Treatment Processes on the Microstructure Properties of 20MnCr5 Steel Gears by Li Luo, Yong Chen, Fucheng Zhao, Weifeng Hua, Xu Song, Zhengyun Xu, Zhicheng Jia

“…This study provides a guiding model theory and experimental verification for regulating proportions of alloying elements and optimizing the heat treatment process of low-carbon-alloy steel.…”
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An Improved Artificial Neural Network Model for Effective Diabetes Prediction by Muhammad Mazhar Bukhari, Bader Fahad Alkhamees, Saddam Hussain, Abdu Gumaei, Adel Assiri, Syed Sajid Ullah

“…We use different number of neurons in the hidden layer, ranging from 5 to 50, to train the ANN models. …”
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Undergraduate Research on Physics-Informed Graph Attention Networks for COVID-19 Prediction by Yu Liang, Dalei Wu

“…All the learning agents are fabricated in a hierarchical architecture, which enables agents to collaborate with each other in peer-to-peer and cross-layer way. This layered architecture shares the burden of large-scale data processing on machine learning models of all units. …”
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Numerical Analysis of Heat Transfer and Flow Characteristics in Porous Media During Phase-Change Process of Transpiration Cooling for Aerospace Thermal Management by Junhyeon Bae, Jukyoung Shin, Tae Young Kim

“…This study conducts numerical analyses of coupled processes of heat transfer, flow, and phase change in transpiration cooling using a Two-Phase Mixture Model. …”
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New method of text representation model based on neural network by Shui-fei ZENG, Xiao-yan ZHANG, Xiao-feng DU, Tian-bo LU

“…Method of text representation model was proposed to extract word-embedding from text feature.Firstly,the word-embedding of the dual word-embedding list based on dictionary index and the corresponding part of speech index was created.Then,feature vectors was obtained further from these extracted word-embeddings by using Bi-LSTM recurrent neural network.Finally,the sentence vectors were processed by mean-pooling layer and text categorization was classified by softmax layer.The training effects and extraction performance of the combination model of Bi-LSTM and double word-embedding neural network were verified.The experimental results show that this model not only performs well in dealing with the high-quality text feature vector and the expression sequence,but also significantly outperforms other three kinds of neural networks,which includes LSTM,LSTM+context window and Bi-LSTM.…”
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Probabilistic regression for autonomous terrain relative navigation via multi-modal feature learning by Ickbum Kim, Sandeep Singh

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Compressed CNN Plant Leaf Ｒecognition Model Fused with Bayesian by YAN Ming, ZHU Liang-kuan, JING Wei-peng

“…Aiming at the problem that there are many parameters in the process of plant leaf recognition and it is easy to produce over-fitting，in order to reduce the cost of storage and calculation，this paper proposes a plant leaf recognition convolutional neural network model based on Bayesian fusion. …”
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Refining Graduation Classification Accuracy with Synergistic Deep Learning Models by Son Nguyen Thi Kim, Quynh Nguyen Huu, Minh Bui Tuan

“…The integration of Adaptive Layer Normalization (AdaLN) in the Transformer also helps stabilize the learning process and minimize overfitting. …”
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Welding Image Data Augmentation Method Based on LRGAN Model by Ying Wang, Zhe Dai, Qiang Zhang, Zihao Han

“…First, a five-layer spectral normalization neural network was designed as the discriminator of the model. …”
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Advances in Experimentation and Numerical Modeling of Aluminum and Copper Ultrasonic Welding by Zhe Li, Shiying Wu, Huan Li

“…For Al/Cu joints, advancements in understanding the microstructure evolution, joint performance, and finite element modeling of the welding process have been systematically reviewed and summarized. …”
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The Establishment of a High-Moisture Corn Ear Model Based on the Discrete Element Method and the Calibration of Bonding Parameters by Chunrong Li, Zhounan Liu, Ligang Geng, Tianyue Xu, Weizhi Feng, Min Liu, Da Qiao, Yang Wang, Jingli Wang

“…Establishing an accurate high-moisture corn ear fragmentation model using the Discrete Element Method is crucial for studying the processing and fragmentation of high-moisture corn ears. …”
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Modeling of chronic generalized periodontitis in laboratory animals (literature review) by O. V. Kopchak, N. S. Marchenko, Ya. V. Yanishevska

“…Microscopically, this was manifested in the heterogeneity of the epithelial layer, the thickening of individual layers, the detachment of the epithelial lining of the mucosa. …”
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Modelling wire-arc-additive manufacturing for joining by forming applications by Viegas João M. A., Rosado Pedro M. S., Sampaio Rui F. V., Pragana João P. M., Bragança Ivo M. F., Silva Carlos M. A., Martins Paulo A. F.

“…The investigation employed finite element modelling to address material nonlinearities caused by heating and cooling cycles during the layer-by-layer material deposition process and accounted for the interchangeable boundary conditions caused by the newly activated mesh elements triggered by the moving heat source and the geometric nonlinearities resulting from thermal-induced distortions during material deposition and unclamping. …”
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Modeling the Impact of Fabrication Variabilities on the Performance of Silicon Avalanche Photodetectors by David Liu, Luca F. Errico, Matteo G. C. Alasio, Mike Zhu, Enrico Bellotti

“…The focus of this work is placed on the performance of CMOS-compatible lateral transport separate-absorber-multiplier APDs (SAM APDs) fabricated on an SOI layer. The FBMC material models are validated against experimental data for carrier velocities and impact ionization coefficients, in addition to the reported APD performance of a germanium-on-silicon (Ge-on-Si) separate-absorber-charge-multiplier APD (SACM APD). …”
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