Optimal control strategy based on artificial intelligence applied to a continuous dark fermentation reactor for energy recovery from organic wastes by Kelly Joel Gurubel Tun, Elizabeth León-Becerril, Octavio García-Depraect

“…Machine learning (ML) and optimization methods are used to model the nonlinear process and then, a neural predictive control (NPC) strategy to drive the system to its optimal operating order under varying influent conditions is developed. …”
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Comparison of YOLOv5 for Classifying Mangrove Leaf Species using CNN-Based by Anindita Septiarini, Rita Diana, Rahmat Kamara, Novianti Puspitasari, Anton Prafanto

“…The three variants have various processing times and numbers of layers. This study uses mangrove leaf images with a total image dataset of 400 images consisting of 4 types of mangrove plants: Avicennia alba, Bruguiera gymnorhiza, Rhizopora apiculata, and Sonneratia alba. …”
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Rice Leaf Disease Image Enhancement Based on Improved CycleGAN by YAN Congkuan, ZHU Dequan, MENG Fankai, YANG Yuqing, TANG Qixing, ZHANG Aifang, LIAO Juan

“…This adjustment also helped to reduce visual artifacts and excessive smoothing, while concurrently improving the stability of the model during the training process. To comprehensively evaluate the quality of the rice disease images generated by the proposed model and to assess its impact on disease recognition performance, both subjective and objective evaluation metrics were utilized. …”
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Enhancing Lidar-Based 3D Classification Through an Improved Deep Learning Framework With Residual Connections by Shih-Lin Lin, Jun-Yi Wu

“…Although the increased network complexity and added layers lead to longer training times, the robust performance justifies the computational cost. …”
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Transformer-Based Vulnerability Detection in IoT Firmware Binaries Using Opcode Sequences by M. Nandish, Jalesh Kumar, H. G. Mohan, M. V. Manoj Kumar

“…Initially, firmware binaries are disassembled to extract opcode sequences, which are then tokenized and encoded as inputs to the proposed DeBERTa model. The model processes instruction opcode sequences and generates meaningful embeddings, which are utilized for classification tasks. …”
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Collaborative Filtering Recommendation-Based Random Negative Sampling and Graph Attention by Weiqiang Li, Xianghui Li, Xiaowen Liu, Xinhuan Chen, Ming Ma

“…On the other hand, during the model’s loss optimization process, sample imbalance is prone to occur. …”
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Forecasting loan, deferred rate and customer segmentation in banking industry: A computational intelligence approach by Mahtab Vasheghani, Ebrahim Nazari Farokhi, Behrooz Dolatshah

“…This study proposes a novel hybrid model integrating Multi-Layer Perceptron (MLP) neural networks with Self-Adaptive Particle Swarm Optimization (PSO) and Genetic Algorithm (GA) frameworks. …”
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Early diagenesis in anoxic sediments of the Gulf of Gdańsk (southern Baltic Sea): Implications for porewater chemistry and benthic flux of carbonate alkalinity by Katarzyna Łukawska-Matuszewska, Maciej Dwornik

“…According to recent modeling studies, anaerobic processes in sediments are an important internal source of alkalinity in the Baltic Sea. …”
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Risk management of emergency situations caused by flooding of built‐up mountain areas by E. V. Arefyeva, I. Yu. Oltyan, Yu. I. Prus

“…In such territories, the watered soil preserves the cultural layer, which determines the need for flexible regulation of the groundwater regime. …”
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Efficient adsorptive removal of hazardous congo red dye using Ce-BTC@microcrystalline cellulose composite by Mostafa A. Sayed, Reda M. Abdelhameed, Ibrahim H. A. Badr, Ali M. Abdel-Aziz

“…The adsorption kinetics followed a pseudo-second-order model (R2 = 0.988), and both intraparticle and boundary layer diffusion influenced the rate-limiting step of the adsorption process. …”
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Plastic to apparel: an analysis of sustainable purchasing intention using a machine learning ensemble by Carmella Andrea L. Cabrera, Ardvin Kester S. Ong, John Francis T. Diaz, Maela Madel L. Cahigas, Ma. Janice J. Gumasing

“…Data preprocessing using feature selection and correlation analysis was conducted to validate the available data, performed data cleaning process, and data aggregation. Several iterative processes were employed to generate the optimum classification model—obtaining a 92% accuracy for RFC and 91% for ANN at 150 epochs under 30 hidden layer nodes. …”
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Deep Learned Feature Technique for Human Action Recognition in the Military using Neural Network Classifier by Adeola O Kolawole, Martins E Irhebhude, Philip O Odion

“…This method used the VGG16 model to automatically extract deep learned features at the max-pooling layer and the input presented to neural network classifier for classification into the various classes of human actions achieving 90% recognition accuracy which is at training time of 104.91secs. …”
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Optimizing surface quality in PMEDM using SiC powder material by combined solution response surface methodology – Adaptive neuro fuzzy inference system by Huu Phan Nguyen, Shirguppikar Shailesh, Ganachari Vaibhav, Muthuramalingam Thangaraj, Trong Ly Nguyen

“…The research results showed that the influence of process parameters on SR was indicated by Analysis of Variance technique, and the calculation model of SR was determined with high accuracy. …”
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Tuberculosis detection with customized CNN and oversampling techniques: a deep learning approach by B. H. Shekar, Shazia Mannan

“…Grad-CAM has been applied to interpret the decision-making process of the models and correctly identify the regions of interest. …”
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An embedded KPI-based advisory framework for monitoring and diagnosis of soft sensor degradation by Muhammad Shahid, Haslinda Zabiri, Syed Ali Ammar Taqvi

“…Four embedded KPIs (Hotelling's T², Squared Prediction Error (SPE), R² recovery, and detection ratio) evaluate faults as short or prolonged process faults. A second layer examines the consistency of T² or SPE across windows to determine if the fault is process-related or model-related. …”
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PCB-Based Dual-Polarized Liquid Crystal Reflectarray With High Aperture Efficiency and Bridge-Shaped Biasing Topology for 2D Scanning by Hogyeom Kim, Byeongju Moon, Seungwoo Bang, Seongwoog Oh, Jungsuek Oh

“…The influence of the biasing layer is analyzed in detail using an equivalent circuit model for TE and TM modes. …”
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Discrete Element Analysis of Grouting Reinforcement and Slurry Diffusion in Overburden Strata by Pengfei Guo, Weiquan Zhao, Yahui Ma, Huiling Gen

“…Research on the grouting reinforcement mechanism of overburden is constrained by the concealed and heterogeneous nature of geotechnical media, posing dual challenges in theoretical analysis and process visualization. Based on discrete element numerical simulations and laboratory tests, an analytical model for grouting reinforcement in overburden layers is developed, revealing the influence of grouting pressure on slurry diffusion shape and distance. …”
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Multiple sclerosis diagnosis with brain MRI retrieval: A deep learning approach by R.M. Haggag, Eman M. Ali, M.E. Khalifa, Mohamed Taha

“…Our framework utilizes The Inception V3 model that is pre-trained on ImageNet and RadImageNet datasets, and we modified the model by adding a new block of six layers to reduce the features’ dimensionality in the feature extraction phase. …”
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Design of an Intervention and Education System for Children with Emotional Disorders Based on Semantic Analysis by Ruifang Yang, Yiqun Wang

“…This paper acquires video data by deploying a common camera acquisition and transforms, annotates, frames, and processes the data with the help of feature engineering methods. …”
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Numerical Investigation of the Impact of Variation of Negative Electrode Porosity upon the Cycle Life of Lithium-Ion Batteries by Shuangchao Li, Peichao Li, Runzhou Yu

“…This study introduces a numerical model for the battery aging process, grounded in existing research on SEI formation and its temperature-dependent aging kinetics. …”
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