Anomaly Detection in Wireless Sensor Networks Using Immune-Based Bioinspired Mechanism by Ramsha Rizwan, Farrukh Aslam Khan, Haider Abbas, Sajjad Hussain Chauhdary

“…In this paper, we propose a bioinspired solution using Negative Selection Algorithm (NSA) of the AIS for anomalies detection in WSNs. …”
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Lightweight anomaly detection model for UAV networks based on memory-enhanced autoencoders by HU Tianzhu, SHEN Yulong, REN Baoquan, HE Ji, LIU Chengliang, LI Hongjun

“…In order to solve the problems of high energy consumption and high reliance on manual annotation data of traditional intelligent attack detection methods in UAV networks, a lightweight UAV network online anomaly detection model based on a double-layer memory-enhanced autoencoder integrated architecture was proposed. …”
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Fault Detection of the Power System Based on the Chaotic Neural Network and Wavelet Transform by Zuoxun Wang, Liqiang Xu

“…To solve this problem, a criterion algorithm based on the chaotic neural network (CNN) and a fault detection algorithm based on discrete wavelet transform (DWT) are proposed in this paper. …”
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Joint user activity and signal detection for massive multiple-input multiple-output by Xiaoqun SONG, Ming JIN, Zhongjie JIA

“…In uplink grant-free massive multiple-input multiple-output (mMIMO) systems, the performance of available methods for joint user activity and signal detection deteriorates when the correlation of receiving antennas or the number of active devices increases.Moreover, the available methods require the knowledge of noise power, which is often practically unknown.To address the above issues, combining approximate message passing with unitary transformation and expectation maximization algorithm to jointly implement user activity and signal detection was proposed.Different from the conventional approximate message passing algorithm, the proposed one assumes that the noise power was unknown.Firstly, by exploiting the approximate message passing algorithm with unitary transform, the distribution of transmitted symbols together with the distribution of noise power was obtained.Secondly, expectation maximization algorithm was applied to estimate the user activity.Finally, the signal detection was implemented by deriving the posterior distribution of the decoupled signal belongs.Simulation results show that the proposed method is better than the traditional method in joint user activity and signal detection.…”
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Study on Support Vector Machine-Based Fault Detection in Tennessee Eastman Process by Shen Yin, Xin Gao, Hamid Reza Karimi, Xiangping Zhu

“…In order to further illustrate the efficiency, an industrial benchmark of Tennessee Eastman (TE) process is utilized with the SVM algorithm and PLS algorithm, respectively. By comparing the indices of detection performance, the SVM technique shows superior fault detection ability to the PLS algorithm.…”
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Retrieval of cloud fraction using machine learning algorithms based on FY-4A AGRI observations by J. Xia, L. Guan

“…Corrections have been made subsequently to the retrieved cloud fraction in areas where solar glint occurs using a correction curve fitted with sunglint angle as weight. The algorithm includes two steps: the cloud detection is conducted firstly for each AGRI field of view to identify whether it is clear sky, partly cloudy or overcast within the observation field. …”
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Crack Detection and Evolution Law for Rock Mass under SHPB Impact Tests by Xie Beijing, Dihao Ai, Yu Yang

“…In order to accurately identify and quantitatively calculate the surface cracks of rock mass under SHPB impact loading, an automatic crack detection algorithm was proposed and evaluated by the experiment. …”
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A New, Robust, Adaptive, Versatile, and Scalable Abandoned Object Detection Approach Based on DeepSORT Dynamic Prompts, and Customized LLM for Smart Video Surveillance by Merve Yilmazer, Mehmet Karakose

“…Abandoned object detection is achieved by tracking classes in consecutive frames with the DeepSORT algorithm and measuring the distance between them. …”
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Method for Changepoint Detection With Sample Size Accumulation During Radio Equipment Operation by Solomentsev Oleksandr, Zaliskyi Maksym, Herasymenko Tetyana, Petrova Yuliia

“…The proposed algorithm has advantages in mean time of decision making compared with CUSUM detection method.…”
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European ILD registry algorithm for self-assessment in interstitial lung diseases (eurILDreg ASA-ILD). by Ekaterina Krauss, Laurenz H Claas, Silke Tello, Jennifer Naumann, Sandra Wobisch, Stefan Kuhn, Raphael W Majeed, Karen Moor, Maria Molina-Molina, Oisin Byrne, Rebecca Borton, Marlies S Wijsenbeek, Nik Hirani, Carlo Vancheri, Bruno Crestani, Andreas Guenther, eurILDreg investigators

“…<h4>Conclusion</h4>This study is designed to explore the potential of e-Health technologies, such as home monitoring via spirometry and oximetry, integrated with the eurILDreg ASA-ILD algorithm and patientMpower app, to improve early detection and management of ILD. …”
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Machine learning anomaly detection of lost and unaccounted for gas in natural gas networks by Omar Fayez Mohamed ElMahdy, Mohamed Ezz Hassan, Sayed M. Metwalli

“…A machine learning anomaly detection algorithm using multivariate Gaussian density estimation combined with principal component analysis (PCA) is developed. …”
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BT-YOLO11: Automatic Driving Road Target Detection in Complex Scenarios by Qi Wang, Qi Long Wang

“…Due to the problems faced by autonomous driving scenarios in complex scenarios, generalized target detectors are challenged, especially the detection accuracy of occluded and small targets. In order to solve this problem, a target detection algorithm for complex scenes BT-YOLO11 is proposed based on the latest YOLO11. …”
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An Improved 2D Pose Estimation Algorithm for Extracting Phenotypic Parameters of Tomato Plants in Complex Backgrounds by Yawen Cheng, Ni Ren, Anqi Hu, Lingli Zhou, Chao Qi, Shuo Zhang, Qian Wu

“…Phenotypic traits, such as plant height, internode length, and node count, are essential indicators of the growth status of tomato plants, carrying significant implications for research on genetic breeding and cultivation management. Deep learning algorithms such as object detection and segmentation have been widely utilized to extract plant phenotypic parameters. …”
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Practical Model for Short-Circuit Current Calculation of Photovoltaic Power Station Based on Improved RLS Algorithm by Zhiyuan Sun, Mosi Liu, Kun Zheng

“…The purpose of this paper is to study how to improve the practical model of short-circuit current calculation of photovoltaic power plants, so that it can be well applied to the current high-density current detection in China. Therefore, this paper improves the recursive least squares (RLS) algorithm and applies it to the practical model of short-circuit current calculation of photovoltaic power plants and describes the improvement process of the algorithm in detail. …”
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Smart Tool-Related Faults Monitoring System Using Process Simulation-Based Machine Learning Algorithms by Arash Ebrahimi Araghizad, Faraz Tehranizadeh, Kemal Kilic, Erhan Budak

“…In this paper a novel approach for monitoring tool-related faults in milling processes by utilizing process simulation-based machine learning algorithms, specifically Random Forest algorithms, for fault detection is presented. …”
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Antibody responses to Borrelia burgdorferi detected by western blot vary geographically in Canada. by Nicholas H Ogden, Julie Arsenault, Todd F Hatchette, Samir Mechai, L Robbin Lindsay

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An Online Data-Driven Method for Accurate Detection of Thermal Updrafts Using SINDy by Yufeng Lu, Chenglou Liu, Haichao Hong, Yunwei Huang, Tingwei Ji, Fangfang Xie

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An integrated approach of feature selection and machine learning for early detection of breast cancer by Jing Zhu, Zhenhang Zhao, Bangzheng Yin, Canpeng Wu, Chan Yin, Rong Chen, Youde Ding

“…Optimizing hyperparameters of five models using the Particle Swarm Optimization (PSO) algorithm. In the datasets, 26 features were filtered using our recommended algorithm, the LightGBM-PSO model demonstrated an outstanding performance. …”
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OS-PCMM: Automatic Registration Algorithm for Optical and SAR Image Based on Phase Congruency and Multimoment Feature by Yuan Liang, Tao Su, Ruiqiu Wang, Jiangtao Liu

“…In this article, we propose an automatic registration algorithm for optical and SAR images based on phase congruency and multimoment features. …”
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A Differential Biomarker Based on Recurrence Quantification Analysis of EEG Signal and Genetic Algorithm for Epilepsy Diagnosis by Vanithamani Palanisamy, A Ranichitra, Radhamani Ellapparaj

“…Recurrence Quantification Analysis (RQA) is a promising technique for detecting seizures without assuming stationary conditions, accommodating various signal and noise sizes. …”
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