Forecasting Occurrence and Intensity of Geomagnetic Activity With Pattern‐Matching Approaches by C. Haines, M. J. Owens, L. Barnard, M. Lockwood, A. Ruffenach, K. Boykin, R. McGranaghan

“…It is likely that the best method for a user will depend on their need for probabilistic information and tolerance of false alarms.…”
Get full text

Network Intrusion Detection and Prevention System Using Hybrid Machine Learning with Supervised Ensemble Stacking Model by Godfrey A. Mills, Daniel K. Acquah, Robert A. Sowah

“…In this paper, we present a hybrid intrusion detection system that combines supervised and unsupervised learning models through an ensemble stacking model to increase the detection accuracy rates of attacks in networks while minimising false alarms. Three machine learning algorithms comprising a multilayer perceptron neural network, a modified self-organizing map, and a decision tree were used for the detection framework. …”
Get full text

A cognitive model of perceptual anomalies: The role of source monitoring, top-down influence and inhibitory processes for hallucinations in schizophrenia spectrum disorders and hal... by Adrianna Aleksandrowicz, Joachim Kowalski, Steffen Moritz, Izabela Stefaniak, Łukasz Gawęda

“…No significant group differences were found for false alarms in the Go/No-Go Task. However, there was a significant relationship between perceptual anomalies and all the cognitive processes as well as self-disturbances and functioning in the entire sample. …”
Get full text

CBGS-YOLO: A Lightweight Network for Detecting Small Targets in Remote Sensing Images Based on a Double Attention Mechanism by Zhenyuan Wu, Di Wu, Ning Li, Wanru Chen, Jie Yuan, Xiangyue Yu, Yongqiang Guo

“…Conventional target detection methods are frequently incapable of addressing these complexities, resulting in a reduction in detection accuracy and an increase in false alarms. Hence, in this paper, we propose a lightweight remote-sensing image target detection network model, CBGS-YOLO, created by introducing the Ghost module to decrease the model parameters, applying the SPD-Conv module to optimize downsampling, and integrating the convolutional block attention module to enhance detection accuracy. …”
Get full text

Predictive Capabilities of Corotating Interaction Regions Using STEREO and Wind In‐Situ Observations by Yutian Chi, Chenglong Shen, Christopher Scott, Mengjiao Xu, Mathew Owens, Yuming Wang, Mike Lockwood

“…This demonstrates that a spacecraft situated 30° trailing Earth in its orbit, can optimize our space weather‐predicting capabilities for the Earth and lessen the risk of missing or “false alarms” CIRs.…”
Get full text

Invited perspectives: Integrating hydrologic information into the next generation of landslide early warning systems by B. B. Mirus, B. B. Mirus, T. Bogaard, R. Greco, M. Stähli

“…The extensive progress demonstrates the value of in situ hydrologic information for reducing both failed and false alarms through the ability to characterize infiltration during – as well as the drainage and drying processes between – major storm events. …”
Get full text

Revisiting ‘revisiting supervised methods for effort‐aware cross‐project defect prediction’ by Fuyang Li, Peixin Yang, Jacky Wai Keung, Wenhua Hu, Haoyu Luo, Xiao Yu

“…The results show that (1) The classification before sorting (CBS+) defect density calculation strategy achieves the best overall performance. (2) Using balanced distribution adaption (BDA) and joint distribution adaptation (JDA) with the K‐nearest neighbour classifier to build the EACPDP model can find 15% and 14.3% more defective modules and 11.6% and 8.9% more defects while achieving the acceptable initial false alarms (IFA). (3) Better comprehensive classification performance of the methods can bring better EACPDP performance to some extent. (4) A flexible adjustment of the defect threshold λ of the CBS+ strategy contribute to different goals. …”
Get full text

A multifactor coupled rarly-warning model for pipeline landslide hazards based on the dynamic evolutionary process of disaster by Sen WU, Dexu QI, Hu LI, Yu LAN, Jiang LI, Mingzhi SUN

“…However, the failure to account for the correlation between various indicators has led to a high frequency of false alarms. Based on the analysis of the dynamic evolutionary process of pipeline landslide hazards, this study proposes four stages of pipeline landslide hazards: (1) rainfall on the landslide leads to surface infiltration; (2) the groundwater level rises increasing the slope self-weight increases and reducing the geotechnical parameter; (3) the slope has undergone local deformation; (4) the landslide slides entirely and threatens pipeline safety. …”
Get full text

Glu4: An open-source package for real-time forecasting and alerting post-bariatric hypoglycemia based on continuous glucose monitoring by Luca Cossu, Francesco Prendin, Giacomo Cappon, David Herzig, Lia Bally, Andrea Facchinetti

“…The system showed a high specificity, with no false alarms being triggered during the monitoring period. …”
Get full text

Development and validation of a screening tool for sepsis without laboratory results in the emergency department: a machine learning studyResearch in context by Shan Jiang, Shuai Dai, Yulin Li, Xianlong Zhou, Cheng Jiang, Cong Tian, Yana Yuan, Chengwei Li, Yan Zhao

“…However, due to its low positive predictive value (PPV), the false alarms may increase in actual clinical practice. …”
Get full text