A comparative analysis of fault detection and process diagnosis methods based on a signal processing paradigm by Dorel Aiordăchioaie

“…Abstract An important paradigm in industrial engineering for fault detection and diagnosis purposes is signal processing. …”
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Anomaly Detection and Radio-frequency Interference Classification with Unsupervised Learning in Narrowband Radio Technosignature Searches by Ben Jacobson-Bell, Steve Croft, Carmen Choza, Alex Andersson, Daniel Bautista, Vishal Gajjar, Matthew Lebofsky, David H. E. MacMahon, Caleb Painter, Andrew P. V. Siemion

“…The search for radio technosignatures is an anomaly detection problem: Candidate signals represent needles of interest in the proverbial haystack of radio-frequency interference (RFI). …”
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Curvature-Based Change Detection in Road Segmentation: Ascending Hierarchical Clustering vs. K-Means by David Jaurès Fotsa-Mbogne, Addie Bernice Nguensie-Wakponou, Jean Michel Nlong, Marcellin Atemkeng, Maurice Tchuente

“…Given the high frequency of data collection by accelerometers, the resulting large datasets pose a computational challenge for anomaly detection using supervised classification algorithms. …”
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Research on Automatic Tracking and Size Estimation Algorithm of “Low, Slow and Small” Targets Based on Gm-APD Single-Photon LIDAR by Dongfang Guo, Yanchen Qu, Xin Zhou, Jianfeng Sun, Shengwen Yin, Jie Lu, Feng Liu

“…In order to solve the problem of detecting, tracking and estimating the size of “low, slow and small” targets (such as UAVs) in the air, this paper designs a single-photon LiDAR imaging system based on Geiger-mode Avalanche Photodiode (Gm-APD). …”
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3D Deployment Optimization of Wireless Sensor Networks for Heterogeneous Functional Nodes by Zean Lu, Chengqun Wang, Peng Wang, Weiqiang Xu

“…Simulation results demonstrate that ISBOA exhibits a faster convergence speed and higher accuracy in both the 23 benchmark functions and the newly designed multi-objective optimization problem, significantly overcoming the shortcomings of the compared algorithms. …”
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Optimization of Graphene Oxide’s Characteristics with TOPSIS Using an Automated Decision-Making Process by Javanbakht T.

“…In the current research work, a novel automated decision-making process was used with the TOPSIS algorithm using the Łukasiewicz disjunction, which helped detect the confusion of properties and determine its impact on the rank of candidates. …”
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Plug Valve Surface Defects Identification through Nondestructive Testing and Fuzzy Deep-Learning Algorithm for Metal Porosity and Surface Evaluation by V. Jacintha, S. Karthikeyan, P. Sivaprakasam

“…The subsurface flaws detection is a challenging problem in valve inspection. …”
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Accurate Identification Partial Discharge of Cable Termination for High-Speed Trains Based on S-Transform and Two-Dimensional Convolutional Network Algorithm by Yunlong Xie, Peng You, Guangning Wu, Tingyu Zhang, Yang Luo, Shuyuan Zhou, Kai Liu, Kui Chen, Dongli Xin, Guoqiang Gao

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Analyzing social psychological impact on emotional expression through peer communication using crayfish optimization algorithm with deep learning model by Umkalthoom Alzubaidi

“…Finally, the crayfish optimization algorithm (COA) adjusts the VAE model’s hyperparameter values, improving classification. …”
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Systematic Literature Review for Detecting Intrusions in Unmanned Aerial Vehicles Using Machine and Deep Learning by Abdulaziz A. Alzubaidi

“…One of those attacks is intrusion malware, which uses malicious programs, signal spoofing, denial of services, targeting integrity, confidentiality, and availability of the system. Detecting these intrusions has recently gained attention in academia and industrial fields for addressing existing threats and developing detection frameworks, such as utilizing machine and deep learning algorithms. …”
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Open-Source Data Logger System for Real-Time Monitoring and Fault Detection in Bench Testing by Marcio Luís Munhoz Amorim, Jorge Gomes Lima, Norah Nadia Sánchez Torres, Jose A. Afonso, Sérgio F. Lopes, João P. P. do Carmo, Lucas Vinicius Hartmann, Cicero Rocha Souto, Fabiano Salvadori, Oswaldo Hideo Ando Junior

“…Vibration sensors detect shaft and bearing problems, inadequate motor mounting, or overload conditions. …”
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Sulfur fumigation of botanical drugs: impact on chemical composition and pharmacological properties, and advances in detection technologies by Weiyi Xu, Hongyu Jin, Ying Wang, Feng Wei, Jing Liu

“…Prolonged exposure to these residues may result in respiratory problems and potential carcinogenic effects. In recent years, researchers have created various innovative detection technologies, including fluorescent probe rapid detection methods and machine learning algorithms, to improve the precision of identifying and quantifying chemical changes in sulfur-fumigated samples. …”
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Mf-net: multi-feature fusion network based on two-stream extraction and multi-scale enhancement for face forgery detection by Hanxian Duan, Qian Jiang, Xin Jin, Michal Wozniak, Yi Zhao, Liwen Wu, Shaowen Yao, Wei Zhou

“…Current face forgery detection algorithms achieve high detection accuracy within-dataset. …”
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The data dimensionality reduction and bad data detection in the process of smart grid reconstruction through machine learning. by Bo Yu, Zheng Wang, Shangke Liu, Xiaomin Liu, Ruixin Gou

“…To detect false data injection attacks (FDIAs) in power grid reconstruction and solve the problem of high data dimension and bad abnormal data processing in the power system, thereby achieving safe and stable operation of the power grid system, this study introduces machine learning methods to explore the detection of FDIAs. …”
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Performance of Fitness Functions Based on Natural Frequencies in Defect Detection Using the Standard PSO-FEM Approach by Xiao-Lin Li, Roger Serra, Julien Olivier

“…Structural defect detection based on finite element model (FEM) updating is an optimization problem by minimizing the discrepancy of responses between model and measurement. …”
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Hybrid TDOA/DOA Multiple PD Localization Using Two Arrays With KPCA-mnc-FastICA and Sparrow Search Algorithm by Zeyu Zhang, Xiaojun Tang, Xiaoshan Li, Chongzhi Liu

“…Our previous research, which is kernel principal component analysis modified noncircular fast independent component analysis (KPCA-mnc-FastICA), is further studied to calculate arrival time difference and direction of multiple sources simultaneously. To tackle the problem of slow calculation speed, this article explores a combined method of hybrid TDOA/DOA positioning model and sparrow search algorithm (SSA) with two arrays which is sufficient to meet the requirement of multiple PD localization. …”
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The Application of Artificial Digital Models in X-Ray Computed Tomography (CT) of the Core in Solving the Problem of Binarization of the Void Space of Reservoir Rocks by O. A. Melkishev, Y. V. Savitsky, S. V. Galkin

“…These phantoms were then converted into tomograms, allowing us to determine statistical characteristics of the values for X-ray densities of the samples at the reconstruction stage.Based on the statistical analysis of the X-ray density distribution in the sample, we determined the boundary values that are most suitable for reliable void space detection. Using regression and correlation methods, we developed a model to estimate the optimal boundary value for X-ray density in void space allocation.We proposed an algorithm for determining and applying this value in the analysis of core X-ray CT data.This model was tested on real samples that were not used in the development of the forecast model. …”
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G4 & the balanced metric family – a novel approach to solving binary classification problems in medical device validation & verification studies by Andrew Marra

“…In addition, data from an independently published study that tested the performance of a unique ultrasound artificial intelligence algorithm in the context of breast cancer detection was also considered. …”
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Fast Low Rank and Sparse Decomposition Based on Greedy Bilateral Smoothing for Infrared Small Target Detection by Yan-Shan Zhang, Ze-Yin Li, Dong-Dong Pang, Lu-Yao Wang, Cheng-Jun Wu, Kang Duan, Jun-Ming Gao

“…Leveraging the support of the low-rank approximation theory, the small target detection is formulated as an optimization problem involving a low-rank matrix and a sparse matrix. …”
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Main lobe deceptive jamming suppression based on blind source separation and energy detection for monopulse radar by Zhenhua Liu, Wei Liang, Ning Fu, Liyan Qiao, Jun Zhang

“…To tackle this problem, a novel main lobe jamming suppression method is proposed based on BSS and energy detection. …”
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