Intrusion Detection Based on Sequential Information Preserving Log Embedding Methods and Anomaly Detection Algorithms by Czangyeob Kim, Myeongjun Jang, Seungwan Seo, Kyeongchan Park, Pilsung Kang

“…It is further possible to distinguish abnormal behaviors more precisely by training classification models if sufficient amounts of labeled dataset is obtained through post analysis of anomaly detection results. In this study, we proposed an end-to-end abnormal behavior detection method based on sequential information preserving log embedding algorithms and machine learning-based anomaly detection algorithms. …”
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Parallel graph-based anomaly detection technique for sequential data by Ahmed Farag, Hatem Abdelkader, Rashed Salem

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Remote Sensing Change Detection by Pyramid Sequential Processing With Mamba by Jiancong Ma, Bo Li, Hanxi Li, Siying Meng, Ruitao Lu, Shaohui Mei

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Sequential Two-Mode Fusion Underwater Single-Photon Lidar Imaging Algorithm by Tian Rong, Yuhang Wang, Qiguang Zhu, Chenxu Wang, Yanchao Zhang, Jianfeng Li, Zhiquan Zhou, Qinghua Luo

“…This paper reports the sequential two-mode fusion imaging algorithm, which has a strong information extraction capability and can reconstruct scene target depth and reflection intensity images from complex signal photon counts. …”
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Detecting Simulated Nosocomial Disease Outbreaks with Sequential Monte Carlo Methods by Dr Conor Rosato

“…Discussion: The proposed algorithm successfully detects outbreaks in a timely manner. …”
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A Sequential Compressed Spectrum Sensing Algorithm against SSDH Attack in Cognitive Radio Networks by Zhuhua Hu, Yong Bai, Lu Cao, Mengxing Huang, Mingshan Xie

“…In this paper, a novel nonreconstructed sequential compressed wideband spectrum sensing algorithm (NSCWSS) is proposed. …”
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Algorithms for Integrated Object Detection in Wireless Sensor Networks by V. I. Parfenov, T. T. Bui

“…In this connection, the development of an integrated detection algorithm for sequential transmission of information from sensor to sensor is a relevant research task. …”
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High-resolution 2D-DoA sequential algorithm of azimuth and elevation estimation in automotive distributed system of coherent MIMO radars by I. V. Artyukhin

“…The Monte Carlo method is used to compare the effectiveness of the considered algorithms.Results. The 2D-DoA sequential algorithm of azimuth and elevation estimation is proposed. …”
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Video inter-frame tampering detection algorithm fusing multiple features by Hui XIAO, Bin WENG, Tianqiang HUANG, Han PU, Zehui HUANG

“…Traditional passive forensics of video inter-frame tampering often relies on single feature.Each of these features is usually suitable for certain types of videos,while has low detection accuracy for other videos.To combine the advantages of these features,a video inter-frame tampering detection algorithm that could fuse multi-features was proposed.The algorithm firstly classified the input video into one group based on its space information and time information values.Then it calculated the VQA features that represented the video inter-frame continuity.These features were sorted by the SVM-RFE feature recursive elimination algorithm.Finally,the sorted features were filtered and fused by the sequential forward selection algorithm and Adaboost binary classifier.Experimental results show that the proposed algorithm could achieve higher tampering detection accuracy.…”
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Two-level feature selection method based on SVM for intrusion detection by Xiao-nian WU, Xiao-jin PENG, Yu-yang YANG, Kun FANG

“…To select optimized features for intrusion detection，a two-level feature selection method based on support vector machine was proposed.This method set an evaluation index named feature evaluation value for feature selection，which was the ratio of the detection rate and false alarm rate.Firstly，this method filtrated noise and irrelevant features to reduce the feature dimension respectively by Fisher score and information gain in the filtration mode.Then，a crossing feature subset was obtained based on the above two filtered feature sets.And combining support vector machine，the sequential backward selection algorithm in the wrapper mode was used to select the optimal feature subset from the crossing feature subset.The simulation test results show that，the better classification performance is obtained according to the selected optimal feature subset，and the modeling time and testing time of the system are reduced effectively.…”
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A novel damage detection method based on sequential iteration and Gaussian mixture model for structural health monitoring under environmental effects by Jie-zhong Huang, Jian Yang, Dong-sheng Li, Wei-chen Kong, Ya-fei Wang

“…In the second step, the expectation-maximization (EM) algorithm is used to establish the GMM, clustering the training data into local subsets. …”
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Refining malaria diagnosis in high-transmission areas: a dual-approach with rapid diagnostic tests (RDTs) and dbPCR-NALFIA by Diane Yirgnur Some, Francois Kiemde, Hermann Sorgho, Marc Christian Tahita, Antonia Windkouni Bere, Abdoulaye Ouedraogo, Souleymane Vivien Banao, Kouadjo Bagre, Gérémie Djiri, Georges Some, Toussaint Rouamba, Yeri Esther Hien, Aly Savadogo, Henk D. F. H. Schallig, Halidou Tinto

“…Following confirmation of undetermined sequential interpretation with dbPCR-NALFIA, the sequential algorithm had a sensitivity of 97.9%, a specificity of 94.8%, a positive predictive value of 97.2%, and a negative predictive value of 96.1%. …”
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Financial Fraud Detection Approach Based on Firefly Optimization Algorithm and Support Vector Machine by Ajeet Singh, Anurag Jain, Seblewongel Esseynew Biable

“…In this paper, a new methodology has been proposed for detecting credit card fraud (financial fraud) that is a hybridization of the firefly bio-inspired optimization algorithm and a support vector machine (called FFSVM), which comprises two sequential levels. …”
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Voice pathology detection using machine learning algorithms based on different voice databases by Nurul Mu'azzah Abdul Latiff, Fahad Taha Al-Dhief, Nurul Fariesya Suhaila Md Sazihan, Marina Mat Baki, Nik Noordini Nik Abd. Malik, Musatafa Abbas Abbood Albadr, Ali Hashim Abbas

“…Unlike traditional approaches that focus solely on single-database training and testing, this study presents a cross-database evaluation strategy to assess the robustness and generalizability of machine learning algorithms for voice pathology detection. Several algorithms, including Online Sequential Extreme Learning Machine (OSELM), Support Vector Machine (SVM), Decision Tree (DT), and Naïve Bayes (NB), were evaluated using two databases: the Saarbrucken Voice Database (SVD) and the Malaysian Voice Pathology Database (MVPD). …”
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Smart deep learning model for enhanced IoT intrusion detection by Faisal S. Alsubaei

“…This paper addresses these limitations with large preprocessing steps followed by hyperparameter tuning of machine learning XGBoost and deep learning Sequential Neural Network (OSNN) algorithms through Grid Search for their best values to improve multiclass intrusion detection across varied datasets. …”
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A novel myocarditis detection combining deep reinforcement learning and an improved differential evolution algorithm by Jing Yang, Touseef Sadiq, Jiale Xiong, Muhammad Awais, Uzair Aslam Bhatti, Roohallah Alizadehsani, Juan Manuel Gorriz

“…However, the detection of myocarditis using CMR images can be challenging due to low contrast, variable noise, and the presence of multiple high CMR slices per patient. …”
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Localization of Conveyor Belt Damages Using a Deep Neural Network and a Hybrid Method for 1D Sequential Data Augmentation by Iwona Komorska, Andrzej Puchalski, Damian Bzinkowski

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Decision support algorithm to prevent hardware failures by E. A. Abidova

“…The goal is achieved by developing an algorithm for detecting the beginning of a deviation in a time series consisting of sequentially recorded diagnostic parameters. …”
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A belief propagation algorithm based on track‐before‐detect for tracking low‐observable and manoeuvering targets using multiple sensors by Chenghu Cao, Haisheng Huang, Xin Li, Yongbo Zhao

“…Based on the factor graph representing the multi‐sensor statistical model, the marginal posterior densities are derived by performing the message passing equations of the proposed belief propagation algorithm for target detection and target state estimation. …”
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A computational framework for IoT security integrating deep learning-based semantic algorithms for real-time threat response by Ripal Ranpara, Shobhit K. Patel, Om Prakash Kumar, Fahad Ahmed Al-Zahrani

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