Evaluation and Correction of GPM IMERG Precipitation Products over the Capital Circle in Northeast China at Multiple Spatiotemporal Scales by Wei Sun, Yonghua Sun, Xiaojuan Li, Tao Wang, Yanbing Wang, Qi Qiu, Zhitian Deng

“…Based on five evaluation indexes, NRMSE (Normalized Root Mean Square Error), NSE (Nash-Sutcliffe), FAR (False Alarm Ratio), UR (Underreporting Rate), and CSI (Critical Success Index), the monthly GPM products showed the best performance, better than GPM-HH products and GPM-D products. (2) The performance of GPM products in summer and autumn was better than in winter and spring. …”
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Automatic Multitarget Detection Method Based on Distributed Through-wall Radar by Xiao LIANG, Shengbo YE, Chenyang SONG, Yubing YUAN, Qunying ZHANG, Xiaojun LIU, Hejun JIANG, Hong LI

“…Target candidate distance cells are identified using a constant false alarm rate detection method, and candidate signals are enhanced using a filtering matrix. …”
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Statistical Evaluation and Trend Analysis of ANN Based Satellite Products (PERSIANN) for the Kelani River Basin, Sri Lanka by Helani Perera, Miyuru B. Gunathilake, Ravindu Panditharathne, Najib Al-mahbashi, Upaka Rathnayake

“…Four categorical indices including probability of detection (POD), false alarm ratio (FAR), critical success index (CSI), and proportional constant (PC) were used to evaluate the rainfall detection capability of SbPPs. …”
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Tangential Human Posture Recognition with Sequential Images Based on MIMO Radar by Chuanwei DING, Zhilin LIU, Li ZHANG, Heng ZHAO, Qing ZHOU, Hong HONG, Xiaohua ZHU

“…A time sequence of high-quality images is achieved to describe the structure of the human body and corresponding dynamic changes, where spatial and temporal features are extracted to enhance the recognition performance. First, a Constant False Alarm Rate (CFAR) algorithm is applied to locate the human target. …”
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A Deep Learning-Based Time-Frequency Scheme for Ship Detection Using HFSWR by Da Huang, Hao Zhou, Yingwei Tian, Zhiqing Yang, Weimin Huang

“…However, when using a constant false alarm rate (CFAR) detector, these systems experience performance degradation primarily because of echo nonstationarity. …”
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Towards a decision support system for post bariatric hypoglycaemia: development of forecasting algorithms in unrestricted daily-life conditions by Francesco Prendin, Olivia Streicher, Giacomo Cappon, Eva Rolfes, David Herzig, Lia Bally, Andrea Facchinetti

“…Algorithms’ performance was assessed by measuring Precision, Recall, F1-score, False-alarms-per-day and Time Gain (TG). Results The run-to-run forecasting algorithm based on recursive autoregressive model (rAR) outperformed the other techniques, achieving Precision of 64.38%, Recall of 84.43%, F1-score of 73.06%, a median TG of 10 min and 1 false alarm every 6 days. …”
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Adaptive decentralized AI scheme for signal recognition of distributed sensor systems by Shixiong Zhang, Hao Li, Cunzheng Fan, Zhichao Zeng, Chao Xiong, Jie Wu, Zhijun Yan, Deming Liu, Qizhen Sun

“…By fine-tuning pre-trained model with the unlabeled data in each domain, the ADAI scheme can train a series of adaptive AI models for all target domains, significantly reducing the false alarm rate (FAR) and missing alarm rate (MAR) induced by domain differences. …”
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Feature Selection Using Particle Swarm Optimization in Intrusion Detection by Iftikhar Ahmad

“…Excessive work is done on intrusion detection systems but still these are not powerful due to high number of false alarms. One of the leading causes of false alarms is due to the usage of a raw dataset that contains redundancy. …”
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The Value of CME Arrival Time Forecasts for Space Weather Mitigation by M. J. Owens, M. Lockwood, L. A. Barnard

“…This can help discriminate between geoeffective and nongeoeffective CMEs, reducing false alarms and expanding the range of operational scenarios under which a forecast provides value. …”
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STIDNet: Spatiotemporally Integrated Detection Network for Infrared Dim and Small Targets by Liuwei Zhang, Zhitao Zhou, Yuyang Xi, Fanjiao Tan, Qingyu Hou

“…However, for infrared dim and small targets with low signal-to-clutter ratios (SCRs), the detection difficulty lies in the fact that their poor local spatial saliency will lead to missed detections and false alarms. In this work, a spatiotemporally integrated detection network (STIDNet) is proposed for IRDSTD. …”
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Correlation Analysis Approach About Numerous Security Information and Event in Telecommunication Network by Ning Fan, Guoshui Shi, Jun Shen, Huamin Jin

“…Correlation analysis engine which correlate isolated security event as a chain to find out the real threat from a large number of false alarms or low level ones,is a key module of security operations centre（SOC）.The traditional correlation analysis mechanism is divided into two types:state machine and inference-engine.For poor precision and low efficiency,they don't adapt telecom network application.A new correlation analysis mechanism based on consecutive state by inference-engine was presented,which executed efficiently and accurately,to solve the problems of correlation analysis engine applied in telecom network.…”
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Dynamic Watermarking for Finite Markov Decision Processes by Jiacheng Tang, Jiguo Song, Abhishek Gupta

“…We derive a lower bound on the mean time between false alarms and an upper bound on the mean delay between the time an attack occurs and when it is detected. …”
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Comparing the Performance of Logit and Probit Early Warning Systems for Currency Crises in Emerging Market Economies by Fabio Comelli

“…For macroeconomic policy purposes, we conclude that a currency crisis defi nition identifying more rather than less crisis episodes should be used, even if this may lead to the risk of issuing false alarms.…”
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UAV and Its Approach in Oil and Gas Pipeline Leakage Detection by Saheed Akande, Adedotun Adetunla, Tosin Olanrewaju, Adeyinka Adeoye

“…A comparative analysis of the response time of the designed LDS and existing systems reveals that the designed LDS response time is 1146.7% faster and having a pictorial view of the localized area of interest would go a long way to preventing unnecessary mobilization for site visits and eradicating the costly effect of false alarms.…”
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Distributed Cognitive Radio Spectrum Access with Imperfect Sensing Using CTMC by K. Muthumeenakshi, S. Radha

“…This framework is also extended to incorporate the effects of imperfect spectrum sensing in the form of misdetection and false alarms. Simulation results show that the proposed algorithm attains an overall throughput that is better than CSMA when the primary user spectrum utilization is around 45%. …”
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Human response times are governed by dual anticipatory processes with distinct neural signatures by Ashwin G. Ramayya, Vivek Buch, Andrew Richardson, Timothy Lucas, Joshua I. Gold

“…Participants showed two forms of anticipatory response biases, distinguished by more premature false alarms (FAs) or faster response times (RTs) on long-delay trials. …”
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Beyond detection rate: understanding the vigilance decrement using signal detection theory by Henri Etel Skinner, Henri Etel Skinner, Barry Giesbrecht, Barry Giesbrecht

“…Commonly used tasks do not allow for the reliable computation of these metrics because they elicit a low number of false alarms or because they introduce confounding response demands. …”
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A Deep Learning Anomaly Detection Framework for Satellite Telemetry with Fake Anomalies by Yakun Wang, Jianglei Gong, Jie Zhang, Xiaodong Han

“…Moreover, we explored what conditions could lead to false alarms. The approach proposed has been deployed to the ground station to monitor the health status of the in-orbit satellites.…”
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Overview of Feature Extraction and Recognition Methods for Fiber Optic Vibration Signals by QIAN Junxia, GUO Jiaxing

“…However, this method can be challenging to distinguish between different types of intrusion behaviors and is prone to false alarms triggered by various environmental interferences. …”
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Design and realization of compressor data abnormality safety monitoring and inducement traceability expert system. by Yuan Wang, Shaolin Hu

“…The results show that this method effectively overcomes the problems of false alarms and missed alarms based on fixed threshold alarm methods, and achieves 100% classification of two types of faults: non starting of the drive machine and low oil pressure by constructing a PCA (Principal Component Analysis)-SPE (Square Prediction Error)-CNN (Convolutional Neural Network) classifier. …”
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