TriageHD: A Hyper-Dimensional Learning-to-Rank Framework for Dynamic Micro-Segmentation in Zero-Trust Network Security by Ryozo Masukawa, Sanggeon Yun, Sungheon Jeong, Nathaniel D. Bastian, Mohsen Imani

“…TriageHD constructs dynamic scene graphs from time-based network flow data, integrating feature representations extracted via a self-attention-based payload encoder. …”
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A Network Traffic Anomaly Classification Model Based on Self-Attention Mechanism and Convolutional Gated Recurrent Unit by Yulian Li, Yang Su

“…However, traditional methods struggle to effectively identify minority-class traffic under conditions of data imbalance, which affects detection accuracy. To address this issue, this paper proposes a Custom Synthetic Minority Over-Sampling Technique (Custom SMOTE) algorithm, which precisely handles minority-class samples while significantly reducing memory consumption. …”
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Hardware-Optimized Architecture of On-Board Registration for Remote-Sensing Images —Take SURF as an Example by Xin Du, Cankun Yang, Ruofei Zhong, Qingyang Li, Yuanhang Wang, Zhaoming Huang, Xianlin Liu

“…However, due to the high computational complexity of feature detection and feature extraction, it is still a challenge to realize real-time registration for on-board edge devices with limited computing power and power consumption. …”
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A generative adversarial network-based accurate masked face recognition model using dual scale adaptive efficient attention network by Jafar A. Alzubi, Kiran Sree Pokkuluri, Rajesh Arunachalam, Surendra Kumar Shukla, Sumanth Venugopal, Karthikayen Arunachalam

“…Otherwise, generated feature set 1 and feature set 2 are given to the DS-AEAN for recognizing the faces to ensure the person’s identity. …”
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Enhancing weld quality of novel robotic-arm arc welding: Vision-based monitoring, real-time control seam tracking by Aman Sharma, Rishabh Chaturvedi, Kamal Sharma, Saad Abrahim Binhowimal, Jayant Giri, T. Sathish

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Enhanced Blind Separation of Rail Defect Signals with Time–Frequency Separation Neural Network and Smoothed Pseudo Wigner–Ville Distribution by Mingxiang Zhang, Kangwei Wang, Yule Yang, Yaojia Cao, Yong You

“…Simulation and experiments showed that compared with traditional algorithms like independent component analysis, shallow neural networks, and time–frequency blind source separation, the proposed algorithm can provide better separation performance and higher stability in rail crack detection.…”
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Adaptive Multi-Scale Bayesian Framework for MFL Inspection of Steel Wire Ropes by Xiaoping Li, Yujie Sun, Xinyue Liu, Shaoxuan Zhang

“…Our approach integrates discrete wavelet transform with adaptive thresholding and multi-scale feature fusion, enabling simultaneous detection of minute defects and large-area corrosion. …”
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Empirical Evaluation and Analysis of YOLO Models in Smart Transportation by Lan Anh Nguyen, Manh Dat Tran, Yongseok Son

“…You Only Look Once (YOLO) and its variants have emerged as the most popular real-time object detection algorithms. They have been widely used in real-time smart transportation applications due to their low-latency detection and high accuracy. …”
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Infrared Thermography-Based Insulator Fault Classification via Unsupervised Clustering and Semi-Supervised Learning by Usman Shafique, Syed Muhammad Alam, Umar Rashid, Wahab Javed, Haris Anwaar, Malik Shah Zeb, Talha Ahmad, Uzair Imtiaz, Frederic Nzanywayingoma

“…Then, in the supervised learning phase, a Gaussian kernel support vector machine (SVM) algorithm classifies various insulator defects using extracted features. …”
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Enhancing personalized learning: AI-driven identification of learning styles and content modification strategies by Md. Kabin Hasan Kanchon, Mahir Sadman, Kaniz Fatema Nabila, Ramisa Tarannum, Riasat Khan

“…This research endeavors to devise an effective method for detecting a learner’s preferred learning style and subsequently adapting the learning content to align with that style, utilizing artificial intelligence AI techniques. …”
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Automated Eddy Identification and Tracking in the Northwest Pacific Based on Conventional Altimeter and SWOT Data by Lan Zhang, Cheinway Hwang, Han-Yang Liu, Emmy T. Y. Chang, Daocheng Yu

“…Future work should refine the PET algorithm for SWOT’s swath altimetry, addressing data gaps and unclosed contours. …”
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Diagnostic challenges of heart failure with preserved ejection fraction: focus on echocardiography by A. A. Ivanova, O. N. Dzhioeva, E. A. Lavrenova, E. A. Rogozhkina, O. M. Drapkina

“…The low assessment rate of some ultrasonic HFpEF mar­kers and DST among functional diagnostics specialists in the Russian Federation reduces the detection rate of HFpEF. It is necessary to develop diagnostic algorithms based mainly on clinical and anam­nestic data and available for use by doctors of any specialty.…”
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An AI recognition method for children's clinical operative pain by skin potential (SP) signal by Mingxuan Huang, Cangcang Fu, Linbo Chui, Jiadong He, Xiaozhi Wang, Jikui Luo, Bin Wu, Yonggang Chen, Shaohua Hu, Jihua Zhu, Yubo Li

“…Then, we applied wavelet transform (WT) to capture the time-frequency characteristics of the signals and extract energy features and created a feature set comprising 30 features and selected 10 most relevant ones using the “SelectKBest” function.We compared six algorithms, optimized their parameters, and evaluated the stability and fitting performance of each algorithm. …”
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APPROACH TO IMAGE ANALYSIS FOR COMPUTER VISION SYSTEMS by N. A. Iskra

“…The aim of the work is to develop a method for automatically construction of a semantic model, that formalizes the spatial relationships between objects in the image and research thereof. A distinctive feature of this model is the detection of salient objects, due to which the construction algorithm analyzes significantly less relations between objects, which can greatly reduce the image processing time and the amount of resources spent for processing. …”
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A virtual rail train path recognition method based on binocular stereo vision by ZENG Junwei, GENG Li, LU Chenyang, REN Lihui

“…Meanwhile, a binocular matching algorithm based on multi-target tracking was proposed, addressing the drawbacks of general binocular matching algorithms including substantial computations and deficient ability to match repeated objects. …”
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Fast forward modeling and response analysis of extra-deep azimuthal resistivity measurements in complex model by Pan Zhang, Shaogui Deng, Xiyong Yuan, Fen Liu, Weibiao Xie

“…Considering the increased detection range of EDARM and the requirements for computational efficiency, this paper presents a 2.5-dimensional (2.5D) finite element method (FEM). …”
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AI driven cardiovascular risk prediction using NLP and Large Language Models for personalized medicine in athletes by Ang Li, Yunxin Wang, Hongxu Chen

“…Using advanced NLP techniques, including biomedical text mining, entity recognition, and feature extraction, the system processes structured and unstructured clinical data to detect abnormalities associated with sudden cardiac arrest (SCA), arrhythmias, and genetic cardiomyopathies. …”
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Current Status of Application of Spaceborne GNSS-R Raw Intermediate-Frequency Signal Measurements: Comprehensive Review by Qiulan Wang, Jinwei Bu, Yutong Wang, Donglan Huang, Hui Yang, Xiaoqing Zuo

“…Secondly, the key role of coherence detection in spaceborne GNSS-R is discussed. By analyzing the phase and amplitude information of the reflected signals, parameters such as scattering characteristics, roughness, and the shape of surface features are extracted. …”
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A 3-D Defect Profile Inversion Method Based on the Continuity Correction Strategy by Chenlin Wang, Jianhua Tang, Yicheng Duan, Senxiang Lu, Hao Wen

“…Inversion is a key step in MFL detection, and iterative inversion based on an optimization algorithm is an effective method for constructing the 3-D profile of defects in pipelines. …”
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Histopathological image based breast cancer diagnosis using deep learning and bio inspired optimization by Venkata Nagaraju Thatha, M. Ganesh Karthik, Venu Gopal Gaddam, D. Pramodh Krishna, S. Venkataramana, Kranthi Kumar Lella, Udayaraju Pamula

“…Abstract Breast cancer diagnosis remains a crucial challenge in medical research, necessitating accurate and automated detection methods. This study introduces an advanced deep learning framework for histopathological image classification, integrating AlexNet and Gated Recurrent Unit (GRU) networks, optimized using the Hippopotamus Optimization Algorithm (HOA). …”
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