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detection of Asian Dust Storm Using MODIS Measurements

REMOTE SENSING 2017年第8期9卷 869-869页

作者： Xie, Yong Zhang, Wenhao Qu, John J. Nanjing Univ Informat Sci & Technol Sch Geog & Remote Sensing Nanjing 210044 Jiangsu Peoples R China Chinese Acad Sci Inst Remote Sensing & Digital Earth Beijing 100101 Peoples R China George Mason Univ Environm Sci & Technol Ctr Fairfax VA 22030 USA George Mason Univ Dept Geog & GeoInformat Sci GGS Fairfax VA 22030 USA

Every year, a large number of aerosols are released from dust storms into the atmosphere, which may have potential impacts on the climate, environment, and air quality. Detecting dust aerosols and monitoring their movements and evolutions in a timely manner is a very significant task. Satellite remote sensing has been demonstrated as an effective means for observing dust aerosols. In this paper, an algorithm based on the multi-spectral technique for detecting dust aerosols was developed by combining measurements of moderate resolution imaging spectroradiometer (MODIS) reflective solar bands and thermal emissive bands. Data from dust events that occurred during the past several years were collected as training data for spectral and statistical analyses. According to the spectral curves of various scene types, a series of spectral bands was selected individually or jointly, and corresponding thresholds were defined for step-by-step scene classification. The multi-spectral algorithm was applied mainly to detect dust storms in Asia. The detection results were validated not only visually with MODIS true color images, but also quantitatively with products of Ozone Monitoring Instrument (OMI) and Cloud Aerosol Lidar with Orthogonal Polarization (CALIOP). The validations showed that this multi-spectral detection algorithm was suitable to monitor dust aerosols in the selected study areas.

关键词： Asian dust storm MODIS detection algorithm

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Dust and Smoke detection for Multi-Channel Imagers

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REMOTE SENSING 2010年第10期2卷 2347-2368页

作者： Zhao, Tom X. -P. Ackerman, Steve Guo, Wei NOAA NESDIS Natl Climat Data Ctr Asheville NC 28801 USA Univ Wisconsin Cooperat Inst Meteorol Satellite Studies CIMSS Madison WI 53706 USA IM Syst Grp Inc Kensington MD 20895 USA

A detection algorithm of dust and smoke for application to satellite multi-channel imagers is introduced in this paper. The algorithm is simple and solely based on spectral and spatial threshold tests along with some uniformity texture. Detailed examinations of the threshold tests are performed along with explanations of the physical basis. The detection is performed efficiently at the pixel level and output is in the form of an index (or flag): 0 (no dust/smoke) and 1 (dust/smoke). The detection algorithm is implemented sequentially and designed to run on segments of data instead of pixel by pixel for efficient processing. MODIS observations are used to test the operation and performance of the algorithm. The algorithm can capture heavy dust and smoke plumes very well over both land and ocean and therefore is used as a global detection algorithm. The method can be applied to any multi-channel imagers with channels at (or close to) 0.47, 0.64, 0.86, 1.38, 2.26, 3.9, 11.0, 12.0 mu m (such as current EOS/MODIS and future JPSS/VIIRS and GOES-R/ABI) for the detection of dust and smoke. It can be used to operationally monitor the outbreak and dispersion of dust storms and smoke plumes that are potentially hazardous to our environment and impact climate.

关键词： dust smoke detection algorithm satellite imagers

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A Benchmarking on Optofluidic Microplastic Pattern Recognition: A Systematic Comparison Between Statistical detection Models and ML-Based algorithms

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IEEE ACCESS 2024年 12卷 20091-20102页

作者： Sasso, Daniele Merone, Mario Nicolai, Eleonora Vollero, Luca Sabatini, Anna Univ Campus Biomed Roma Dept Engn Res Unit Comp Syst & Bioinformat I-00128 Rome Italy Univ Roma Tor Vergata Dept Expt Med I-00133 Rome Italy

Microplastics, small particles of plastic found in the environment, have become an increasingly worrying topic in recent years. This paper compares a statistical detection model to classifiers from various supervised learning paradigms in order to detect microplastics. The objective of this paper is to present a benchmark for detecting microplastics using statistical and machine learning models. The main goal is to assess and compare their performance when the defined parameters deviate from the optimal solution of the respective model. Results are presented in terms of probability error, comparing the performance of the machine learning techniques to the statistical model. The study considers a range of signal-to-noise ratios and a priori event probabilities, focusing on the classifiers' ability to handle amplitude variability and threshold variation. Results show that as the number of analyzed particles in the flow increases, the detection performance improves, with Support Vector Machine, Linear Discriminant Analysis and Naive Bayes standing out from the other methods.

关键词： Plastics Particle measurements Biological system modeling Atmospheric measurements Water pollution Symbols Support vector machines detection algorithms Microplastics embedded system detection algorithm

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Shockable Rhythm detection algorithms for Electrocardiograph Rhythm in Automated Defibrillators

Shockable Rhythm Detection Algorithms for Electrocardiograph...

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2012 AASRI Conference on Computational Intelligence and Bioinformatics (CIB2012)

作者： Aijun Fan Peng Han Bin Liu Chongqing Academy of Science & Technology

The quick and accurate detection of shockable rhythms is important in real application of automatic external defibrillator or implantable cardioverter defibrillator to save lives. The crucial component in automatic defibrillator is the detection algorithm for shockable rhythms, including ventricular fibrillation and pulseless ventricular tachycardia. We summarized the main development of the algorithms, including the time-field detection method, frequency-field detection method, time-frequency analysis detection method and dynamics analysis method. Furthermore, the key issues for further study are also presented.

关键词： detection algorithm Electrocardiograph rhythm Shockable rhythms Non–shockable rhythms

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Review of real-time visual driver distraction detection algorithms 10

Review of real-time visual driver distraction detection algo...

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Proceedings of the 7th International Conference on Methods and Techniques in Behavioral Research

作者： Christer Ahlström Katja Kircher Swedish National Road and Transport Research Institute (VTI) Linköping Sweden

ISBN: (纸本)9781605589268

Many incidents and crashes can be attributed to driver distraction, and it is essential to learn how to detect distraction in order to develop efficient countermeasures. A number of distraction detection algorithms have been developed over the years, and the objective of this paper is to summarize available approaches and to describe these algorithms in a unified framework. The review is limited to real-time algorithms that are intended to detect visual distraction.

关键词： driver distraction eye tracking detection algorithm inattention

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Near-Real-Time detection of Tephra Eruption Onset and Mass Flow Rate Using Microwave Weather Radar and Infrasonic Arrays

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IEEE TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING 2016年第11期54卷 6292-6306页

作者： Marzano, Frank S. Picciotti, Errico Di Fabio, Saverio Montopoli, Mario Mereu, Luigi Degruyter, Wim Bonadonna, Costanza Ripepe, Maurizio Univ Roma La Sapienza Dipartimento Ingn Informaz DIET I-00184 Rome Italy Univ Aquila CETEMPS Ctr Excellence I-67100 Laquila Italy HIMET Srl I-67100 Laquila Italy Natl Res Council Italy CNR ISAC I-00133 Rome Italy Swiss Fed Inst Technol Dept Earth Sci Inst Geochem & Petrol CH-8092 Zurich Switzerland Cardiff Univ Sch Earth & Ocean Sci Cardiff CF10 3AT S Glam Wales Univ Geneva Dept Earth Sci CH-1205 Geneva Switzerland Univ Florence Dipartimento Sci Terra I-50121 Florence Italy

During an eruptive event, the near-real-time monitoring of volcanic explosion onset and its mass flow rate (MFR) is a key factor to predict ash plume dispersion and to mitigate risk to air traffic. Microwave (MW) weather radars have proved to be a fundamental instrument to derive eruptive source parameters. We extend this capability to include an early-warning detection scheme within the overall volcanic ash radar retrieval methodology. This scheme, called the volcanic ash detection (VAD) algorithm, is based on a hybrid technique using both fuzzy logic and conditional probability. Examples of VAD applications are shown for some case studies, including the Icelandic Grimsvotn eruption in 2011, the Eyjafjallajokull eruption in 2010, and the Italian Mt. Etna volcano eruption in 2013. Estimates of the eruption onset from the radar-based VAD module are compared with infrasonic array data. One-dimensional numerical simulations and analytical model estimates of MFR are also discussed and intercompared with sensor-based retrievals. Results confirm in all cases the potential of MW weather radar for ash plume monitoring in near real time and its complementarity with infrasonic array for early-warning system design.

关键词： detection algorithm microwave (MW) remote sensing volcanic ash weather radar

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Non-instinct detection of cellphone usage from lane-keeping performance based on eXtreme gradient boosting and optimal sliding windows

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IET INTELLIGENT TRANSPORT SYSTEMS 2022年第11期16卷 1600-1610页

作者： Liu, Tao Zhou, Ziyao Chai, Chen Islam, Md Mohaiminul Tongji Univ Coll Transportat Engn Shanghai 201804 Peoples R China Minist Educ Key Lab Rd & Traff Engn Shanghai Peoples R China Saic Gen Motors Corp Ltd Strateg Alliance & New Business Dept Shanghai Peoples R China

Driving distraction caused by cellphone usage has become a common safety threat. As distraction detection methods based on driver's position or eye movement may raise privacy issues, a promising way is to analyze the vehicle's lane-keeping performance. This paper proposed a detection algorithm based on eXtreme gradient boosting (XGBoost), to develop a real-time driving distraction detection based on lane-keeping performance. The algorithm includes knowledge-based volatility feature extraction and feature selection by recursive feature elimination (RFE). To obtain dynamic patterns of lane-keeping performance affected by different types of cellphone usage, browsing a short message, browsing a long message, and answering a phone call, a driving simulator experiment was conducted on 28 drivers. Results showed that the proposed XGBoost-RFE method is reliable and promising to predict phone usage with 80% accuracy. The results also evoke the fact that sliding window size, which is about 80% of subtask duration, can be appropriate for real-time detection of multiple cellphone usages. For overlap percentages, 67% of sliding window size can balance the efficiency and continuity of data in adjacent sliding windows. The paper's potential application includes the design of a real-time driving distraction detection system.

关键词： eXtreme gradient boosting multiple cellphone usages feature selection road vehicles window size distraction detection methods optimal sliding windows driver information systems knowledge-based volatility feature extraction cellphone usage detection algorithm road safety lane-keeping performance feature extraction real-time driving distraction detection system phone usage regression analysis noninstinct detection support vector machines real-time detection

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Stealthy attack detection and solution strategy for consensus-based distributed economic dispatch problem

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INTERNATIONAL JOURNAL OF ELECTRICAL POWER & ENERGY SYSTEMS 2018年 103卷 233-246页

作者： Zhang, Wenming He, Xing Southwest Univ Coll Elect & Informat Engn Chongqing Key Lab Nonlinear Circuits & Intelligen Chongqing 400715 Peoples R China

Distributed system is efficient and scalable in modern power grid. However, a distributed system is so susceptible to attack. In this paper, we formulate consensus-based distributed economic problem under attacks, and the convergence of the algorithm under a realizable and general stealthy attack is proved. Then the expression of the convergence point is also provided. Furthermore, a strategy based on a defined observation network is proposed to detect whether the system is attacked by the false data injection to broadcast information. Consequently, the misbehaving agents are detected and removed, and the other agents can reach the optimal point under new optimal objective, the incremental cost and total generation cost can be decreased. The simulation studies not only validate the theoretical results but also show the effectiveness of proposed strategy.

关键词： Stealthy attack Consensus detection algorithm Attack solution strategy

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detection and tracking of returns in sector-scan sonar image sequences

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IEE PROCEEDINGS-RADAR SONAR AND NAVIGATION 1996年第3期143卷 157-162页

作者： Chantler, MJ Lane, DM Dai, D Williams, N Department of Computing and Electrical Engineering Heriot-Watt University Edinburgh United Kingdom

The authors report the development of algorithms for the detection and tracking of object returns in noisy sector-scan sonar image sequences. Static objects are first removed using spatial and frequency domain filtering. The optical flow of the resulting images (containing only dynamic returns) is calculated. Significant dynamic returns are detected and segmented using adaptive thresholding. The average optical flow of each significant return is used by a tracking algorithm both to constrain search window radii and to derive a similarity measure. A tree of possible tracks is maintained in which the cumulative similarity measure is used to identify the most likely tracks and to prune out the least likely object sequences. The results of experiments using real scan sequences are presented to show the utility of the proposed tracking system.

关键词： detection algorithm tracking tree sonar image processing tracking algorithm adaptive thresholding object identification

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A Novel Voting Model Based on Parity Check Equations for Blind detection of M-Sequences

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IEEE ACCESS 2024年 12卷 34131-34140页

作者： Wang, Ping Yang, Qiang Hu, Yangheng Xiong, Jian Jia, Yong Guo, Dequan Chengdu Technol Univ Sch Network & Commun Engn Chengdu 610731 Sichuan Peoples R China Chengdu Univ Informat Technol Sch Automat Chengdu 610225 Sichuan Peoples R China Jiangxi Normal Univ Key Lab Nat Disaster Monitoring & Early Warning & Nanchang 330022 Peoples R China Chengdu Univ Technol Sch Mech & Elect Engn Chengdu 610225 Sichuan Peoples R China

A novel acquisition scheme of pseudo-noise (PN) codes is proposed for spreading satellite communication systems relying on the proposed multi-voter model of this paper. Based on the proposed model, the acquisition of PN codes can be attributed to a voting and selecting mechanism to pick out the erroneous chips. Although message passing algorithm (MPA) is a feasible algorithm for decoding PN codes, MPA does not get good detection performance due to the limited number of parity check equations in the acquisition scheme. To overcome the negative impact of the limited number of parity check equations, this paper proposes single-voter and multi-voter models, which combine chip and sequence estimation on the basis of the chip-flipping (CF). It is known that the bit-flipping (BF), weighted-bit-flipping (WBF) and other algorithms based on BF are credible for low density parity check (LDPC) codes. Because of the lack of research, these algorithms have not been extended to the detection of PN codes. As the same as BF, the inputs of the proposed CF algorithm are the hard-decision samples. For the proposed CF, there exists an optimal flipping-threshold which is similar to the random weight of the WBF. Owing to the low computation complexity of CF, the unlimited number of parity check equations can be enabled in the voting model. The experimental results show that the detection performance of the proposed method of N > 15 is improved by 2 dB compared with MAP-based method and 4 dB compared with LEAP-based method at the detection probability 99%.

关键词： Mathematical models Correlation Decoding Receivers Iterative decoding Estimation Computational complexity detection algorithms Spread spectrum communication PN codes voting model detection algorithm MPA

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