Research review of digital modeling technologies with 3D spatial visualization for pipelines by Xin LIU, Shengwen TU, Yanfang HOU, Dong LIN, Jie SHU, Yu TANG

“…The principles, characteristics, and application scenarios of each category are described, with a comparative analysis of their advantages and disadvantages. Given the deficiencies in these technologies, particularly when addressing adverse geological areas frequently encountered by oil and gas pipelines, such as challenges in clearly representing pipeline deformation and subsequent difficulties in manual operation and maintenance, this paper discusses the applications and benefits of new technologies in pipeline visualization, including Inertial Measurement Unit (IMU), Light Detection and Ranging (LiDAR), Augmented Reality (AR), Digital Twin (DT), and the Internet of Things (IoT). …”
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Bone scintigraphy based on deep learning model and modified growth optimizer by Omnia Magdy, Mohamed Abd Elaziz, Abdelghani Dahou, Ahmed A. Ewees, Ahmed Elgarayhi, Mohammed Sallah

“…To address the aforementioned issues, this work proposed a machine-learning technique that uses phases to detect Bone scintigraphy. The first phase in the proposed model is the feature extraction and it was conducted based on integrating the Mobile Vision Transformer (MobileViT) model in our framework to capture highly complex representations from raw medical imagery using two primary components including ViT and lightweight CNN featuring a limited number of parameters. …”
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Fault Diagnosis in a Four-Arm Delta Robot Based on Wavelet Scattering Networks and Artificial Intelligence Techniques by Claudio Urrea, Carlos Domínguez

“…Sensitivity analysis demonstrates the classifier’s capacity to detect untrained faults, highlighting the importance of effective feature extraction and classification methods for fault diagnosis in complex robotic systems. …”
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USING RADIO FREQUENCY CURRENT TRANSFORMERS INSTEAD OF THE ROGOWSKI COILS IN HIGH VOLTAGE ROTATING EQUIPMENT by T.K. Nurubeyli, Z.K. Nurubayli, I.M. Ismayilov, G.N. Mammadova, A.R. Muslumzade

“…The analysis confirms the superior accuracy of RFCTs under real operating conditions, ensuring high-quality PD signal detection against noise, a capability difficult to achieve with RCs without additional filtering. …”
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Comparison of Diffuse Reflectance and Diffuse Transmittance Vis/NIR Spectroscopy for Assessing Soluble Solids Content in Kiwifruit Coupled with Chemometrics by Yu Xia, Wei Zhang, Tianci Che, Jinghao Hu, Shangqiao Cao, Wenbo Liu, Jie Kang, Wei Tang, Hongbo Li

“…The performance of two spectral acquisition methods—diffuse reflectance and diffuse transmission—in detecting SSC in kiwifruit was compared. Various preprocessing methods and feature wavelength selection techniques were employed, and regression models were constructed using partial least squares (PLS) analysis. …”
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An Innovative Artificial Intelligence Classification Model for Non-Ischemic Cardiomyopathy Utilizing Cardiac Biomechanics Derived from Magnetic Resonance Imaging by Liqiang Fu, Peifang Zhang, Liuquan Cheng, Peng Zhi, Jiayu Xu, Xiaolei Liu, Yang Zhang, Ziwen Xu, Kunlun He

“…Our dual-path architecture combines a CNN-LSTM encoder for cine CMR analysis and an MLP encoder for IVPG time-series data, followed by feature fusion and dense classification layers. …”
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ScaleViM-PDD: Multi-Scale EfficientViM with Physical Decoupling and Dual-Domain Fusion for Remote Sensing Image Dehazing by Hao Zhou, Yalun Wang, Wanting Peng, Xin Guan, Tao Tao

“…Remote sensing images are often degraded by atmospheric haze, which not only reduces image quality but also complicates information extraction, particularly in high-level visual analysis tasks such as object detection and scene classification. …”
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Optimized Design and Deep Vision-Based Operation Control of a Multi-Functional Robotic Gripper for an Automatic Loading System by Yaohui Wang, Sheng Guo, Jinliang Zhang, Hongbo Ding, Bo Zhang, Ao Cao, Xiaohu Sun, Guangxin Zhang, Shihe Tian, Yongxu Chen, Jixuan Ma, Guangrong Chen

“…Methodologically, we first developed three gripper prototypes, selecting the optimal design (30° angle between the gripper and container side) through workspace and interference analysis. A deep vision-based recognition system, enhanced by an improved YOLOv5 algorithm and multi-feature fusion, was employed for real-time object detection and pose estimation. …”
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SE-DeepLabV3+: Cervical Cell Segmentation and Classification Using a Novel SE-Based DeepLabV3+ and Ensemble Method by Betelhem Zewdu Wubineh, Andrzej Rusiecki, Krzysztof Halawa

“…The classification model utilizes an ensemble approach by combining features from multiple pre-trained convolutional neural networks (CNNs) and introducing learnable weights (dense layers applied to the global average pooling layer) to dynamically adjust the importance of each model’s feature and improve prediction accuracy. …”
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Extracting Vehicle Trajectories Using Unmanned Aerial Vehicles in Congested Traffic Conditions by Eui-Jin Kim, Ho-Chul Park, Seung-Woo Ham, Seung-Young Kho, Dong-Kyu Kim

“…In this study, we propose and compare two learning-based frameworks for detecting vehicles: the aggregated channel feature (ACF), which is based on human-made features, and the faster region-based convolutional neural network (Faster R-CNN), which is based on data-driven features. …”
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DMoC-UNet: A Dynamic Mixture-of-Convolution Network for Enhanced Pathological Image Segmentation by Jingwei Zhu, Lining Qin, Zixin Teng, Xiaomin Li, Kuiwu Li, Haoran Chu

“…Pathological image segmentation is a cornerstone in medical image analysis and is crucial for tumor detection, tissue classification, and pathological diagnosis. …”
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Hybrid Machine Learning for CNC Process Monitoring by Robin Strobel, Samuel Deucker, Hanlin Zhou, Hafez Kader, Alexander Puchta, Benjamin Noack, Jurgen Fleischer

“…By accurately predicting reference signals and comparing them with real-time measurements, deviations can be used for effective model-based process monitoring and anomaly detection. This study explores the efficacy of hybrid machine learning (ML) models in predicting reference signals for CNC axes using features derived from a physical model. …”
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Applications of gene pair methods in clinical research: advancing precision medicine by Changchun Wu, Xueqin Xie, Xin Yang, Mengze Du, Hao Lin, Jian Huang

“…Effectively mining these large-scale, high-dimensional data is crucial for facilitating disease detection, subtype differentiation, and understanding the molecular mechanisms underlying disease progression. …”
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Improved security for IoT-based remote healthcare systems using deep learning with jellyfish search optimization algorithm by Faris Kateb, Mahmoud Ragab, Felwa Abukhodair, Omar Ahmed Abdulkader, Louai A. Maghrabi, Sami Saeed Binyamin, Mohammed Khaled Al-Hanawi

“…The bacterial foraging optimization algorithm (BFOA) method is used for feature extraction. Moreover, a convolutional neural network with long short-term memory (CNN-LSTM-Attention) technique is used for disease detection and classification. …”
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A non-invasive computer-aided personalized diagnosis system for Osteopenia and Osteoporosis by Hadeel Osama El-Sisi, Fatma El-Zahraa Ahmed El-Gamal, Noha Ahmed Hikal

“…To achieve an effective disease management and fractures avoidance, the detection of the disease at its early stage, the Osteopenia stage, is extremely beneficial. …”
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Two-dimensional spatial orientation relation recognition between image objects by Gong Peiyong, Zheng Kai, Jiang Yi, Zhao Huixuan, Huai Honghao, Guan Ruijie

“…These results validate TSOVF’s capacity to advance fine-grained visual relationship detection while providing a reproducible framework for future research in spatial-semantic analysis.…”
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Small-Sample Authenticity Identification and Variety Classification of <i>Anoectochilus roxburghii</i> (Wall.) Lindl. Using Hyperspectral Imaging and Machine Learning by Yiqing Xu, Haoyuan Ding, Tingsong Zhang, Zhangting Wang, Hongzhen Wang, Lu Zhou, Yujia Dai, Ziyuan Liu

“…This approach highlights the potential of hyperspectral imaging and machine learning in plant authenticity identification and provides a new perspective for the detection of counterfeit species.…”
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MRI-Driven Longitudinal Studies of Hippocampal Alterations During the Initial Cognitive Decline by Qunxi Dong, Yuhang Sheng, Junru Zhu, Honghong Liu, Zhigang Li, Jingyu Liu, Yalin Wang, Bin Hu

“…This work proposed an automated MRI-driven longitudinal hippocampal alteration analysis system (LHAAS), which consists of hippocampal segmentation, reconstruction, registration, multivariate morphometric feature extraction, and longitudinal analysis of hippocampal morphometric and volumetric differences between groups. …”
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Detección y diagnóstico de fallas en motores mediante el análisis de vibraciones aplicando técnicas de inteligencia artificial. by Jair Elías Araujo Vargas, Dilan Yesid Franklin Coronel, Victor Manuel Arias Ruiz

“…Therefore, the performance of different artificial intelligence algorithms in the field of fault detection and diagnosis using vibration analysis in motors was evaluated. …”
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Integrative Modeling of Urinary Metabolomics and Metal Exposure Reveals Systemic Impacts of Electronic Waste in Exposed Populations by Fiona Hui, Zhiqiang Pang, Charles Viau, Gerd U. Balcke, Julius N. Fobil, Niladri Basu, Jianguo Xia

“…<b>Methods</b>: We applied untargeted high-resolution metabolomics using dual-column LC-MS/MS and a multi-step analysis workflow combining MS1 feature detection, MS2 annotation, and chemical ontology classification, to characterize urinary metabolic alterations in 91 e-waste workers and 51 community controls associated with the Agbogbloshie site (Accra, Ghana). …”
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