Causes and optimization of the false alarm rate of code review system by Yuanying XIAO, Yaodong YOU, Lixi XIANG

“…Code review technology has become a pivotal part in the construction of network security.Analysis of the test reports obtained by the current code auditing system shows that there are many false positives in the report.The shortcomings in the development of the code audit system were summarized,the principles of different detection algorithms were briefly described,the causes of false alarm rates were analyzed,corresponding optimization ideas were proposed,the technical principles of optimization were explained,and the application scenarios of optimization schemes were described.…”
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The Rise of Inequality and Poverty in Germany During the Pandemic: False Alarm? by Michael Dauderstädt

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Adaptive Constant False Alarm Detector Based on Composite Fuzzy Fusion Rules by Yuyao Yang, Chunbo Xiu

“…In order to improve the detection performance of the radar constant false alarm detector in a multiple-target environment, a Kaigh–Lachenbruch Quantile constant false alarm rate detector based on composite fuzzy fusion rules (CFKLQ-CFAR) is designed by combining fuzzy fusion rules and the Kaigh–Lachenbruch Quantile constant false alarm rate detector. …”
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False Alarm Reduction in Self-Care by Personalized Automatic Detection of ECG Electrode Cable Interchanges by Jocelyne Fayn, Paul Rubel

“…Introduction. False alarm reduction is an important challenge in self-care, whereas one of the most important false alarm causes in the cardiology domain is electrodes misplacements in ECG recordings, the main investigations to perform for early and pervasive detection of cardiovascular diseases. …”
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An Optimization Coverage Strategy for Wireless Sensor Network Nodes Based on Path Loss and False Alarm Probability by Jianing Guo, Yunshan Sun, Ting Liu, Yanqin Li, Teng Fei

“…It then employs the Neyman–Pearson criterion to formulate a maximum detection probability model under conditions where the cost function and prior probability are unknown, constraining the false alarm rate. Simulated experiments are conducted to assess the influence of various model parameters on detection probability, providing comparative analysis against traditional perception models. …”
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False Alarm Causes and Wind Field Sensitivity Analysis of a Severe Rainfall Event in the Guangdong-Hong Kong-Macao Greater Bay Area Urban Cluster by Lan Zhang, Jiawen Zheng, Huaiyu Li, Rui Yu, Lei Wei, Yufei Zhang

“…This study explores the reasons for false alarms and predictability using ground observation data, radar data, ECMWF-ERA5 reanalysis field data, and ECMWF and CMA-TRAMS forecast data. …”
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High-precision laser monitoring system with enhanced non-uniform scanning for railway safety by Yingying Yang, Cheng Wang, Xiaoqi Liu, Yu Liu, Weier Lu, Zhonglin Zhu, Hongye Yan, Guotang Zhao, Xuechun Lin

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Insect visual system inspired small target detection for multi-spectral remotely sensed images by HUANG Feng-chen1, LI Min1, SHI Ai-ye1, TANG Min1, XU Li-zhong1

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Ship detection optimization method in SAR imagery based on multi-feature weighting by Quanhua ZHAO, Xiao WANG, Yu LI, Guanghui WANG

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Control Monitoring Schemes for Monitoring Percentiles of Generalized Exponential Distribution with Hybrid Censoring by Shovan Chowdhury, Amarjit Kundu, Bidhan Modok

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Effective Lock Detectors Based on Costas Loop Output for SBPSK Mobile Communications by D. Ferramola, T. Casilli, S. Pradella, G. Giunta, D. Orlando

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Effect Analysis of Optical Masking Algorithm for GEO Space Debris Detection by Sijie Kong, Jin Zhou, Wenli Ma

“…The experimental results show that the proposed method can detect space debris effectively with low false-alarm by only three frames. When the SNR is higher than 3, the detection probability can reach 94%, and the false-alarm rate is below 2%. …”
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Anomaly intrusion detection based on modified SVM by Hui ZHANG, Cheng LIU

“…A modified SVM multi-classification algorithm integrated with discriminant analysis (D-SVM) was pro-posed,which could solve the problem of low detection accuracy and high false alarm rate caused by unbalanced datasets.For a multi-classification problem could be divided into several binary classification problems,D-SVM could not only have the virtue of high detection accuracy,but also have a low false alarm rate even confronted with unbalanced datasets.Experiments based on KDD99 dataset verify the feasibility and validity of the integrated ap-proach.Results show that when confronted with multi-classification problems,D-SVM could achieve a high detec-tion accuracy and low false alarm rate even when SVM alone fails because of the unbalanced datasets.…”
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Improved Energy Detector with Weights for Primary User Status Changes in Cognitive Radio Networks by Xianzhong Xie, Xiaofeng Hu, Bin Ma, Ting Song

“…The probabilities of false alarm and detection for our ED are deduced under the new detection model. …”
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Opportunistic cooperative spectrum sensing based on eigenvalue ratio of random matrix by Wuji ZHANG, Shunlan LIU, Jianrong BAO

“…To overcome the deficiencies of low detection probability of traditional spectrum sensing,an EROC spectrum sensing algorithm based on the eigenvalue ratio of a random matrix was proposed.Based on the random detection theory,it used double thresholds and opportunistic cooperation to improve of traditional maximum and minimum eigenvalue (MME) algorithm,and it retained the advantages of the traditional energy detection algorithm.Moreover,on the premise of known false alarm probability,the decision threshold was deduced,and the odd-even slot division was used to effectively realize opportunistic cooperation in reception.Simulation results show that the proposed spectrum sensing algorithm has higher detection probability than MME algorithms in case of low signal-to-noise ratio and low false alarm probability.Therefore,it is suitable for application in wireless communications with deteriorate transmission channels.…”
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Variable threshold energy detection algorithm based on trust degree by Jie XIAO, Yuebin CHEN, Chutian CHEN, Ting ZHENG, Jiwu QIAN

“…Aiming at stochastic probabilistic SSDF attacks,a variable threshold energy detection algorithm based on trust degree was proposed.Firstly,the variable threshold was updated by comparing the actual fusion value with the upper and lower boundary values of the fusion center.The upper and lower boundary values were determined through the given false alarm probability andmissed probability.Secondly,a soft fusionmethod was used based on the ratio of correct perception times and the total number of times to update the trust value.Simulation results show that,compared with the traditional fixed threshold,the proposed algorithm can not only reduce the false alarm andmissed detection probability,but also improve the detection probability of the system.…”
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Anomaly detection in multidimensional time series for water injection pump operations based on LSTMA-AE and mechanism constraints by Mei Wang, Xinyuan Zhu, Guangyue Zhou, Kewen Li, Qingshan Wu, Wankai Fan

“…By utilizing LSTMA-AE, we aim to improve the accuracy of anomaly detection, while simultaneously employing mechanistic constraints to mitigate false alarm rates. Experimental results demonstrate that this approach significantly outperforms methods such as polynomial interpolation, random forest, and LSTM-AE in terms of anomaly detection accuracy on field datasets from oilfields, accompanied by a notably lower false alarm rate.…”
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Variability of Reaction Time as a Marker of Executive Function Impairments in Fibromyalgia by Stefan Duschek, Cristina Muñoz Ladrón de Guevara, María José Fernández Serrano, Casandra I. Montoro, Santiago Pelegrina López, Gustavo A. Reyes del Paso

“…In the entire sample, SD, sigma, and tau were inversely associated with the hit rate and positively associated with the false alarm rate. While the greater decline in hit rate after the change in task rule indicates deficient cognitive flexibility, the lack of any difference in false alarm rate suggests intact response inhibition. …”
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Distributed Fault-Tolerant Event Region Detection of Wireless Sensor Networks by Dyi-Rong Duh, Ssu-Pei Li, Victor W. Cheng

“…The proposed algorithm can identify faulty and fault-free sensors and ignore the abnormal readings to avoid false alarm. Moreover, every event region can also be detected and identified. …”
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Forecasting GOES 15 >2 MeV Electron Fluxes From Solar Wind Data and Geomagnetic Indices by C. Forsyth, C. E. J. Watt, M. K. Mooney, I. J. Rae, S. D. Walton, R. B. Horne

“…Hit rates range over 56–89% with false alarm rates of 11–53%. Applied to 2012, 2013, and 2017, our best forecasts have hit rates of 56–83% and false alarm rates of 10–20%. …”
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