A Sensor Data Prediction and Early-Warning Method for Coal Mining Faces Based on the MTGNN-Bayesian-IF-DBSCAN Algorithm by Mingyang Liu, Xiaodong Wang, Wei Qiao, Hongbo Shang, Zhenguo Yan, Zhixin Qin

“…In the context of intelligent coal mine safety monitoring, an integrated prediction and early-warning method named MTGNN-Bayesian-IF-DBSCAN (Multi-Task Graph Neural Network–Bayesian Optimization–Isolation Forest–Density-Based Spatial Clustering of Applications with Noise) is proposed to address the challenges of gas concentration prediction and anomaly detection in coal mining faces. …”
Get full text

A Comparative Study of Unsupervised Deep Learning Methods for Anomaly Detection in Flight Data by Sameer Kumar Jasra, Gianluca Valentino, Alan Muscat, Robert Camilleri

“…The innovation of this paper involves utilizing Transformer architecture and LSTM with self-attention mechanism for the first time in the realm of aviation data, exploring the optimal method for inputting flight data into a model and evaluating all deep learning techniques for anomaly detection against the ground truth determined by human experts. …”
Get full text

Methods of detection of adverse events in critical care: a protocol for a systematic review by Oleksa Rewa, Sandy Widder, Jocelyn Slemko, Janice Y Kung, Jay Gorman

“…Critically ill patients are at high risk of adverse events; however, the optimal approach to detection in this setting is unknown. …”
Get full text

Comparative analysis of data transformation methods for detecting non-technical losses in electricity grids by Maria Gabriel Chuwa, Daniel Ngondya, Rukia Mwifunyi

“…Convolutional neural networks (CNN) have emerged as effective tools for automatically extracting features from raw data, but raw data often lacks the structure needed for optimal feature extraction. This study explores various methods for transforming energy consumption patterns into two-dimensional (2D) representations to enhance feature extraction and NTL detection. …”
Get full text

A Method for Predicting Coal-Mine Methane Outburst Volumes and Detecting Anomalies Based on a Fusion Model of Second-Order Decomposition and ETO-TSMixer by Qiangyu Zheng, Cunmiao Li, Bo Yang, Zhenguo Yan, Zhixin Qin

“…The paper proposes a methane outburst volume-prediction and early-warning method. This method is based on a secondary decomposition and improved TSMixer model. …”
Get full text

Monitoring the production of FRP composites: A review of in-line sensing methods by S. Konstantopoulos, E. Fauster, R. Schledjewski

Get full text

Residual host cell proteins: sources, properties, detection methods and data acquisition modes by Yifan Yao, Yifan Yao, Xuemei Wen, Xuemei Wen, Hongjuan Pan, Hongjuan Pan, Ziwei Chen

“…The research in the future includes the development of more efficient sample pretreatment methods and data processing techniques to improve the sensitivity and accuracy of detection. …”
Get full text

Research on detection and tracking methods of unmanned ship water targets based on light vision by LIU Yibo, QIU Xinyu, WANG Tianhao, GAOYAN Xiusong, WANG Yintao

“…This study explores technical methods based on light vision to address the problem of target detection and tracking by surface unmanned ships in complex environments. …”
Get full text

Benchmarking of Anomaly Detection Methods for Industry 4.0: Evaluation, Ranking, and Practical Recommendations by Aurélie Cools, Mohammed Amin Belarbi, Sidi Ahmed Mahmoudi

“…We conduct a unified comparison of ten anomaly detection methods, categorizing them according to their reliance on synthetic anomaly generation and their detection strategy, either reconstruction-based or feature-based. …”
Get full text

Research and application of deep learning object detection methods for forest fire smoke recognition by Luhao He, Yongzhang Zhou, Lei Liu, Yuqing Zhang, Jianhua Ma

Get full text

A Comparative Study of the Extraction Methods for the Simultaneous Detection of NPS Groups from Urine by M. Kuloglu Genc, S. Mercan, C. Bulut, Z. Turkmen

“…The selected SPE procedure was applied to 20 authentic urine samples taken from volunteers. Results: The optimized extraction method was validated in terms of selectivity, linearity, the limit of detection, the limit of quantification, accuracy, and precision. …”
Get full text

A PERFORMANCE-BASED APPROACH TO AIRSPACE OPTIMIZATION USING WIND-OPTIMAL TRACKS NETWORK IN HO CHI MINH FIR by Ngoc Hoang Quan NGUYEN, Minh Hoang LE, Trinh Binh DINH, Phuc Ky NGUYEN, Thu Thao NGUYEN, Toan Thinh LE, Van Tien Son NGUYEN, Hoang Vu NGUYEN

Subjects: “…optimization method…”
Get full text

Establishment of an indirect ELISA method for detecting bovine coronavirus antibodies based on N protein by Qiang Liu, Xiaoxia Niu, Lingling Jiang, Gang Zhang, Pu Wang, Sinong Zhang, Weifeng Gao, Huichen Guo, Huichen Guo, Yujiong Wang, Yong Li

“…An indirect enzyme-linked immunosorbent assay (iELISA) based on N protein was established for the detection of BCoV antibodies. Reaction conditions were optimized using a checkerboard approach, with the optimal antigen concentration at 1.25 μg/mL and the optimal antibody dilution at 1:200, the cutoff value distinguishing negative and positive serum samples was 0.986. …”
Get full text

Application of Faster R-CNN Deep Learning Method for Rice Plant Disease Detection by Halim Pujiono, Anik Vega Vitianingsih, Slamet Kacung, Anastasia Lidya Maukar, Seftin Fitri Ana Wati

“…This study aims to apply the Faster Region Convolutional Neural Network (Faster R-CNN), a deep learning approach, to detect rice plant diseases. The Grid Search method was employed as a hyperparameter tuning technique to identify the optimal parameter combination for enhancing algorithm performance. …”
Get full text

Interpretable adaptive fault detection method for smart grid based on belief rule base by Yingmei Li, Yaopu Bai, Ruohan Yang, Zhichao Feng, Wei He

“…This method considers the adaptive updating of the search domain of the model accuracy to achieve the balance and optimization between the two conflicting objectives of the model interpretability and the detection accuracy. …”
Get full text

Research on the lightweight detection method of rail internal damage based on improved YOLOv8 by Xiaochun Wu, Shuzhan Yu

Get full text

ICEEMDAN–VMD denoising method for enhanced magnetic memory detection signal of micro-defects by Shouhong Ji, Jie Yan, Yang Liu, Guojun He

“…To solve these problems, a denoising method for enhanced magnetic memory detection signals based on ICEEMDAN and VMD, called ICEEMDAN–VMD, is proposed in this paper. …”
Get full text

Transfer learning based EfficientNet method for transmission line insulator flaw detection by Aleena Swetapadma, Anamika Yadav

“…The proposed method uses a transfer learning-based EfficientNet model for insulator flaw detection. …”
Get full text

A Cost-Sensitive Small Vessel Detection Method for Maritime Remote Sensing Imagery by Zhuhua Hu, Wei Wu, Ziqi Yang, Yaochi Zhao, Lewei Xu, Lingkai Kong, Yunpei Chen, Lihang Chen, Gaosheng Liu

Get full text

Performance of digital filtering and synchronization method for APD communication receiver by Hui-Jun Zhang, Peng Lin, Tong Wang, Zi-Qi Zhang, Bai-Qiu Zhao, Wen-Fang Jiao, Xiao-Nan Yu

“…Unlike conventional methods, which typically rely solely on hardware optimization or basic thresholding techniques, the proposed approach integrates filtering and synchronization to improve weak-signal detection and reduce noise-induced errors. …”
Get full text