Lightweight anomaly detection model for UAV networks based on memory-enhanced autoencoders by HU Tianzhu, SHEN Yulong, REN Baoquan, HE Ji, LIU Chengliang, LI Hongjun

“…Experiments on public data sets and NS-3 simulation data sets show that while ensuring lightweight, the proposed model reduces the false negative rate by an average of 35.9% and 48% compared with the baseline method.…”
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Anomaly detection algorithm based on fractal characteristics of large-scale network traffic by XU Xiao-dong1, ZHU Shi-rui2, SUN Ya-min1

“…Based on the fractal structure of the large-scale network traffic aggregation, anomalies were analyzed qualitatively and quantitatively from perspective of the global and local scaling exponents.Multi-fractal singular spectrum and Lipschitz regularity distribution were used to analyze the fractal parameters of abnormal flow, trying to identify the relationship between the changes of these parameters and the emergence of anomalies.Experimental results show that the emergence of anomalies has obvious signs on the singular spectrum and Lipschitz regularity distribution.Using this feature, a new multi-fractal-based anomaly detection algorithm and a new detection framework were constructed.On the DARPA/Lincoln laboratory intrusion detection evaluation data set 1999, this algorithm’s detection rate is high at low false alarm rate, which is better than EMERALD.…”
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Explainable few-shot learning workflow for detecting invasive and exotic tree species by Caroline M. Gevaert, Alexandra Aguiar Pedro, Ou Ku, Hao Cheng, Pranav Chandramouli, Farzaneh Dadrass Javan, Francesco Nattino, Sonja Georgievska

“…A set of explanation metrics, i.e., correctness, continuity, and contrastivity, accompanied by visual cases, provide further insights about the prediction results. …”
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Machine Learning-Based Detection of Non-Technical Losses in Power Distribution Networks by Mahmut Türk, Heybet Kılıç, Cem Haydaroglu

“…Unlike the studies in the literature, the data set is converted into two-dimensional matrices and analyzed with today's popular approaches, Convolutional Neural Network (CNN) and Long Short-Term Memory (LSTM) models; CNN surpassed LSTM's 64.17% accuracy rate with 97.50% accuracy rate. …”
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CHANGEPOINTS DETECTION OF PANDEMIC WAVE IN REAL-TIME: APPLICATIONS TO THE TRANSMISSION OF COVID-19 by Faihatuz Zuhairoh, Muhammad Rais Ridwan

“…PELT method determines the changepoint based on changes in the statistical properties of the sequence of observations which can be in the form of differences in the mean or variance of each set of observations. In contrast, the linear interpolation method determines the changepoint based on the slope of a data pattern. …”
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A Model for Fat Content Detection in Walnuts Based on Near-Infrared Spectroscopy by Langqin Luo, Honghua Zhang, Yu Wang, Jianliang Zhang, Rui Zhang, Shan Gao, Yuanyong Dian, Zijin Bai, Chunhui Feng, Ze Zhang

“…The results show that the correction set and validation set coefficients of determination of the walnut kernel fat content prediction model using the back propagation neural network algorithm were 0.86 and 0.89, respectively, with root mean square errors of 1.56 and 1.58, and an RPD value of 2.57; the coefficients of determination for the calibration and validation sets of SVR were 0.90 and 0.83, respectively, with root mean square errors of 1.76 and 1.70, respectively, and an RPD value of 1.70. …”
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Mass Spectrometric Fingerprinting to Detect Fraud and Herbal Adulteration in Plant Food Supplements by Surbhi Ranjan, Tanika Van Mulders, Koen De Cremer, Erwin Adams, Eric Deconinck

“…A complimentary evaluation between data obtained using a previously developed Diode Array Detection (DAD) method and the MS data was performed by data fusion techniques and newly generated models. …”
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Improved detection algorithm for rail profile wear based on line structured light by LIU Zhengfeng, CHEN Jianzheng, LI Wei

“…A laboratory experimental platform was set up to evaluate the developed rail profile wear detection system. …”
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Detection of Obstacle Intrusion in Front of Train Based on Vehicle-borne LiDAR by ZENG Xiang, JIANG Guotao, PAN Wenbo, LENG Binghan, CHEN Guibin

“…Finally, a convex hull of obstacles is extracted for interpolation sampling, yielding a dense edge point set to be used to identify obstacle intrusion. This method was proven in the field onboard tests,with a detection accuracy of above 99.4% for track, and higher than 99.7% for trains, poles and towers, and pedestrians, and an obstacle intrusion determination accuracy of 100% after accurate track detection,demonstrating the effectiveness of the proposed methodology in obstacle identification and intrusion determination in front of trains.…”
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Motion Object Detection Model for Electronic Referee Scoring in Table Tennis Events. by Xiaoke Li, Lili Guo

“…The test results showed that the average loss value of the model was only 0.33, the average detection accuracy in the 20-category data set was 0.94, and the average detection time was 103.9 ms. …”
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Mechanisms for Securing Autonomous Shipping Services and Machine Learning Algorithms for Misbehaviour Detection by Marwan Haruna, Kaleb Gebremichael Gebremeskel, Martina Troscia, Alexandr Tardo, Paolo Pagano

“…On one side, our solution is intended to secure communication channels between the SCCs and the vessels using Secure Exchange and COMmunication (SECOM) standard; on the other side, it aims to secure the underlying digital infrastructure in charge of data collection, storage and processing by relying on a set of machine learning (ML) algorithms for anomaly and intrusion detection. …”
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A New Mask R-CNN-Based Method for Improved Landslide Detection by Silvia Ullo, Amrita Mohan, Alessandro Sebastianelli, Shaik Ahamed, Basant Kumar, Ramji Dwivedi, Ganesh R. Sinha

“…A data set of 160 elements is created containing landslide and nonlandslide images. …”
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Early detection of bloodstream infection in critically ill children using artificial intelligence by Hye-Ji Han, Kyunghoon Kim, June Dong Park

“…Background Despite the high mortality associated with bloodstream infection (BSI), early detection of this condition is challenging in critical settings. …”
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Event‐triggered attack detection and state estimation based on Gaussian mixture model by Lu Jiang, Di Jia, Jiping Xu, Cui Zhu, Kun Liu, Yuanqing Xia

“…Finally, centralised data fusion is performed according to the results of attack detection and event‐triggered judgement to realise remote state estimation. …”
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Minimising latency of pitch detection algorithms for live vocals on low-cost hardware

“…A pitch estimation device was proposed for live vocals to output appropriate pitch data through the musical instrument digital interface (MIDI). …”
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Radar Obstacle Detection Based on Pre-Built Maps in Rail Transit Scenarios by LI Yuanzhengyu, PAN Wenbo, HUANG Wenyu, CHEN Zhiwei, YUAN Chao, YANG Zhenyu

“…This system also enables real-time heading angle corrections and obstacle filtering based on positioning information and semantic map data. On-board experiments conducted in a rail transit environment demonstrated the system's capabilities in stably detecting obstacles at distance above 800 m and building maps to cover the entire test line. …”
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Detection and simulation of Kermanshah dust storm using HYSPLIT and WRF-chem models by Tooba Alizadeh, Majid Rezaei Banafsheh, Hashem Rostamzadeh, Gholamreza Goodarzi, Hedar Maleki, Hamzeh Alizadeh

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SympCoughNet: symptom assisted audio-based COVID-19 detection by Yuhao Lin, Xiu Weng, Bolun Zheng, Weiwei Zhang, Zhanjun Bu, Yu Zhou

“…Our model demonstrated significant performance improvements over traditional audio-only approaches, achieving 89.30% accuracy, 94.74% AUROC, and 91.62% PR on the test set. The results confirm that incorporating symptom data enhances COVID-19 detection performance. …”
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Sensitivity and Consistency Analysis of BDS-3 GEO Satellite Orbit Maneuver Detection by Yage Miao, Rui Tu, Ju Hong, Shixuan Zhang, Fangxin Li, Mingyue Liu, Xiaochun Lu

“…We set different empirical thresholds to analyze the effect of threshold selection on the maneuvering detection sensitivity. …”
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Comparing Micro-Ultrasound to mpMRI in Detecting Clinically Significant Prostate Cancer by Christian Pavlovich, Laurence Klotz

“…Materials and Methods: Retrospective data from consecutive patients with any indication for prostate biopsy in 2 academic institutions were included. …”
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