Dose sensitivity of MAGIC-f polymer gel using different MRI sequences by Nícollas Gonçalves Cavedini, Ricardo Meurer Papaléo, Nícolas Borges Jobim, Phelipi Nunes Schuck, Fabrício Nery Garrafiel, Elisa Magno Nunes de Oliveira, Marcelo Menna Barreto Schwarcke, Alex Cristóvão Holanda de Oliveira, Paulo Rauli Rafeson Vasconcelos Caribé, Ana Maria Marques da Silva

“…In the first batch, doses of 0, 2, 4, 6, 8, 10, 20, and 40 Gy were planned. …”
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A Deep Learning Approach for Diabetic Retinopathy Classification Using Retinal Images by Rathod-Jadhav Kavita, Pande Aparna

“…This included a folding layer with batch normalization and dropouts to improve characteristic extraction, simultaneously reducing overhang. …”
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Deep learning based gasket fault detection: a CNN approach by S. Arumai Shiney, R. Seetharaman, V. J. Sharmila, S. Prathiba

“…The system consists of two sets of convolution layers, followed by two sets of batch normalization layer, two sets of RELU layer, max pooling layer and finally fully connected layer for classification of gasket images. …”
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Intelligent Fault Severity Detection of Rotating Machines Based on VMD-WVD and Parameter-Optimized DBN by Ning Jia, Yao Cheng, Youyuan Tian, Feiyu Yang

“…DBN’s learning rate and batch size are both tuned globally by SSA, which has a significant influence on network error. …”
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Fault diagnosis of ZDJ7 railway point machine based on improved DCNN and SVDD classification by Zengshu Shi, Yiman Du, Xinwen Yao

“…First, the depthwise separable convolution in the Xception structure is used to optimize the extraction of fault features. Second, the adaptive batch normalization processing (AdaBN) is performed to improve the noise immunity. …”
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Trimetallic Fe-Zn-Mn (Oxy)Hydroxide-Enhanced Coffee Biochar for Simultaneous Phosphate and Ammonium Recovery and Recycling by Diana Guaya, Jhuliana Campoverde, Camilo Piedra, Alexis Debut

“…This study presents a novel adsorbent synthesized from spent coffee grounds biochar (CB) chemically modified with Mn²⁺/Zn²⁺/Fe³⁺ (oxy)hydroxide nanoparticles (CB–M) for simultaneous removal of phosphate and ammonium. Batch adsorption experiments using both synthetic solution and municipal wastewater were conducted to evaluate the material’s adsorption performance and practical applicability. …”
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Biomethane Production from Untreated and Treated Brewery’s Spent Grain: Feasibility of Anaerobic Digestion After Pretreatments According to Biogas Yield and Energy Efficiency by Jessica Di Mario, Alberto Maria Gambelli, Giovanni Gigliotti

“…Biogas was produced in lab-scale batch reactors and the quantity of biogas produced was measured via the volumetric method. …”
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Preparation of Ammonium Phosphotungstate Composite Loaded with Silica-calcium Alginate Hybrid Material and Its Adsorption Performance for Cs+ by DIAO Xinya1, 2, FAN Ye1, 2, HAO Lecun1, 2, ZHAO Xin1, 2, JIN Qiang1, 2, , CHEN Zongyuan1, 2, GUO Zhijun1, 2

“…The separation and extraction of radioactive cesium is of great significance for the safe disposal of high-level liquid waste (HLLW). …”

 Antimicrobial peptide production with Corynebacterium glutamicum on lignocellulosic side streams by Daniel Waldschitz, Mark-Richard Neudert, Jakob Kitzmüller, Jae Hwi Bong, Yannick Bus, Eva Maria Karner, Peter Sinner, Oliver Spadiut

“…Induced batch, fed batch, and extended batch process modes were compared for highest pediocin PA-1 production. …”
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Autochthonous Starter Effect on Microbiological, Physicochemical Characteristics, and Fatty Acids Content of Moroccan Goat’s Milk Cheese During Ripening by Said Zantar, Yousra Zantar, Mohamed Benicha, Amin Laglaoui, Ouiam EL GALIOU, Mounir Hassani Zerrouk

“…Four types of cheese were made from pasteurized goat's milk (batch A: control cheese prepared without the addition of ferment, batch B: made with a commercial ferment, batch C: L. lactis subs. …”
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VdaBSC: A Novel Vulnerability Detection Approach for Blockchain Smart Contract by Dynamic Analysis by Rexford Nii Ayitey Sosu, Jinfu Chen, Edward Kwadwo Boahen, Zikang Zhang

“…In this study, we present a technique that combines real-time runtime batch normalization and data augmentation for data preprocessing, along with n-grams and one-hot encoding for feature extraction of opcode sequence information from the bytecode. …”
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Automated Lobe-Based Airway Labeling by Suicheng Gu, Zhimin Wang, Jill M. Siegfried, David Wilson, William L. Bigbee, Jiantao Pu

“…In order to assess the performance of this approach, we applied it to a dataset consisting of 300 chest CT examinations in a batch manner and asked an image analyst to subjectively examine the labeled results. …”
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Potato Disease and Pest Question Classification Based on Prompt Engineering and Gated Convolution by Wentao Tang, Zelin Hu

“…By interacting with large language models, prompt words are used to generate potato disease and pest question templates and efficiently construct the Potato Pest and Disease Question Classification Dataset (PDPQCD) by batch importing named entities. The GF-CNN combines outputs from convolutional kernels of varying sizes, and after processing with max-pooling and average-pooling, a gating mechanism is employed to regulate the flow of information, thereby optimizing the text feature extraction process. …”
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Fault diagnosis of mining rolling bearings based on Superlet Transform and OD-ConvNeXt-ELA by WU Xinzhong, LUO Kang, TANG Shoufeng, HE Zexu, CHEN Qi

“…Built upon ConvNeXt-T, Batch Normalization (BN) technology was introduced to improve the network's generalization ability. …”
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HoRNS-CNN model: an energy-efficient fully homomorphic residue number system convolutional neural network model for privacy-preserving classification of dyslexia neural-biomarkers by Opeyemi Lateef Usman, Ravie Chandren Muniyandi, Khairuddin Omar, Mazlyfarina Mohamad, Ayoade Akeem Owoade, Morufat Adebola Kareem

“…In the HoRNS-CNN architecture, the ReLU activation functions of deep CNNs were initially trained for stability and later adapted for homomorphic computations using a Taylor polynomial approximation of degree 3 and batch normalization to achieve high accuracy. The findings show that the HoRNS-CNN model effectively manages cipher-image expansion with an asymptotic complexity of $$O\left({n}^{3}\right)$$ O n 3 , offering better performance and faster feature extraction compared to its peers. …”
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Intelligent library shelf management system for open-access environments: A CNN-based approach with enhanced image recognition and disorder detection by Xueqi Zhang

“…The new system adopts an optimized convolutional kernel design to improve the accuracy of feature extraction. It incorporates batch normalization techniques to mitigate the occurrence of overfitting and utilizes multi-scale feature fusion technology to enhance the ability to recognize book images. …”
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Fault Line Selection of Single Phase Grounding Based on Wavelet Packet Full Frequency Analysis and OS-ELM by JI Wen-lu, ZHAO Xiao-long, ZHANG Ming, YANG Hong-lei, WENG Jia-ming

“…Combining batch and successive iterative，and constantly updating the training data and network structure，to achieve quickly fault line selection of single-phase grounding. …”
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MCC: Multi-Cluster Contrastive Semi-Supervised Segmentation Framework for Echocardiogram Videos by Yu-Jen Chen, Shr-Shiun Lin, Yiyu Shi, Tsung-Yi Ho, Xiaowei Xu

“…Leveraging contrastive loss to enhance foreground feature extraction, our method incorporates multi-cluster contrastive loss to utilize multiple annotated ground-truths per batch and an anchor frame selection algorithm to improve segmentation performance. …”
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CAGNet: A Network Combining Multiscale Feature Aggregation and Attention Mechanisms for Intelligent Facial Expression Recognition in Human-Robot Interaction by Dengpan Zhang, Wenwen Ma, Zhihao Shen, Qingping Ma

“…CAGNet employs a deep learning-based hierarchical convolutional architecture, enhancing the extraction of features at multiple scales through stacked convolutional layers. …”
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Prediction model of mitochondrial energy metabolism related genes in idiopathic pulmonary fibrosis and its correlation with immune microenvironment by Linlin Yao, Baoyan Liu, Yong Wang

“…We employed a multistep bioinformatics approach, including data extraction from the Gene Expression Omnibus database, removal of batch effects, and normalization and differential gene expression analyses. …”
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