PD Detection and Analysis Triggered by Metal Protrusion in GIS Through Various Methods by Weifeng Xin, Wei Song, Manling Dong, Xiaochuan Huang, Xiaoshi Kou, Zhenyu Zhan, Xinyue Shi, Xutao Han

“…The PRPD patterns, maximum discharge amplitude of different defects and PD inception voltage (PDIV) detected by the three methods were analyzed. …”
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A multimodal functional structure-based graph neural network for fatigue detection by Dongrui Gao, Zhihong Zhou, Zongyao Peng, Haokai Zhang, Shihong Liu, Manqing Wang, Hongli Chang

“…Fatigue detection remains a critical research focus in the field. …”
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Financial Fraud Detection on Social Networks Based on a Data Mining Approach by Victoria Bozhenko, Serhii Mynenko, Artem Shtefan

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Opioid Crisis Detection in Social Media Discourse Using Deep Learning Approach by Muhammad Ahmad, Grigori Sidorov, Maaz Amjad, Iqra Ameer, Ildar Batyrshin

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Machine learning algorithms to detect patient–ventilator asynchrony: a feasibility study by Guillermo Gutierrez, Kendrew Wong, Arun Jose, Jeffrey Williams

“…We explored the feasibility of using machine learning algorithms to replicate the assessment of breathing patterns by experienced clinicians, based on airway flow and pressure signals. …”
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Botnet Detection Using Support Vector Machines with Artificial Fish Swarm Algorithm by Kuan-Cheng Lin, Sih-Yang Chen, Jason C. Hung

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Research on Detection Technology of Wind Turbine Blade AnomalyBased on Audio Data by HU Kaikai, CHEN Yanan, CHEN Gang, SHU Hui, LI Ziyuan

“…By installing a pickup on the wind turbine, analyzing and mining the collected wind turbine audio data, and based on the multi classification machine learning model, it explores a set of audio data feature analysis and pattern recognition methods. Simulation and practical application results show that this method can identify whether the blade is damaged and whether the cooling fan works, so as to eliminate the interference by the operation of cooling fan on the blade anomaly detection and realize the abnormal detection of blade whistle, so as to form a feasible blade anomaly detection method based on the audio data of wind turbine.…”
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Multilevel Feature Fusion-Based GCN for Rumor Detection with Topic Relevance Mining by Shenyu Chen, Meng Li, Weifeng Yang

“…However, existing methods for detecting rumors generally only learn pattern features or text content features from the whole propagation process, which fall short in capturing multilevel features with topic relevance of text content from social media data. …”
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Social Network Community Detection by Combining Self-Organizing Maps and Genetic Algorithms by Mehdi Ellouze

“…We have taken part in this effort, and we proposed an approach mainly based on pattern recognition techniques. The novelty of this approach is that we do not directly tackle the social networks to find these communities. …”
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Automatic Detection and Correction of Detuned Singing System for Use With Query-By-Humming Applications by Michał LECH

“…The common approach to searching for a requested song basing on the melody retrieved from hummed pattern usually employs the so-called Parsons code or melody contour. …”
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Long short‐term memory on abstract syntax tree for SQL injection detection by Z. Zhuo, T. Cai, X. Zhang, F. Lv

“…Abstract SQL injection attack (SQLIA) is a code injection technique, used to attack data‐driven applications by executing malicious SQL statements. Techniques like pattern matching, software testing and grammar analysis etc. are frequently used to prevent such attack. …”
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Entropy difference-based EEG channel selection technique for automated detection of ADHD. by Shishir Maheshwari, Kandala N V P S Rajesh, Vivek Kanhangad, U Rajendra Acharya, T Sunil Kumar

“…This paper presents an automated approach for ADHD detection using the proposed entropy difference (EnD)-based encephalogram (EEG) channel selection approach. …”
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Database anomaly detection model based on mining object-condition association rules by DAI Hua, QIN Xiao-lin, LIU Liang, BAI Chuan-jie

“…A database anomaly detection model based on mining object-condition association rules（OCAR） was proposed.Through analyzing and formalizing the only maximum conditional expression of SQL statements with WHERE clause, the object-condition association rule sets（OCARS） are mined, which represent normal user patterns.And the OCARS are used in anomaly detection.Additionally, OCARS mining algorithm and anomaly detection algorithm were given, and they could be easily used in anomaly transaction detection mechanism.In the end, the experiments about detecting SQL injection were given, and the performance and application were also analyzed.…”
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OUTLIER DETECTION ON HIGH DIMENSIONAL DATA USING MINIMUM VECTOR VARIANCE (MVV) by Andi Harismahyanti A., Indahwati Indahwati, Anwar Fitrianto, Erfiani Erfiani

“…Outliers are part of observations that do not follow the data distribution pattern and are located far from the data center. …”
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Of Women, Wine and Salt: Revisioning the Home in Harriet Prescott Spofford’s Detective Fiction by Stéphanie Durrans

“…The patterns of convergence that can be traced between these three tales highlight Spofford’s vision of the home as a highly unstable ground whose shaky foundations are best reflected through the metaphor of the cellar.…”
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Detecting ADHD through natural language processing and stylometric analysis of adolescent narratives by Juan Barrios, Elena Poznyak, Jessica Lee Samson, Halima Rafi, Simon Gabay, Florian Cafiero, Martin Debbané, Martin Debbané

“…This study explores, for the first time, the potential of Natural Language Processing (NLP) and stylometry to identify linguistic markers within Self-Defining Memories (SDMs) of adolescents with ADHD and to evaluate their utility in detecting the disorder. A further novel aspect of this research is the use of SDMs as a linguistic dataset, which reveals meaningful patterns while engaging psychological processes related to identity and memory.MethodOur objectives were to: (1) characterize linguistic features of SDMs in ADHD and control groups; (2) assess the predictive power of stylometry in classifying participants' narratives as belonging to either the ADHD or control group; and (3) conduct a qualitative analysis of key linguistic markers of each group. …”
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Integrated Sensor System for Real-Time Monitoring and Detection of Fish Quality and Spoilage by Binson V. A., Sania Thomas

“…The data acquisition system collects and processes information from the sensor array, while the data processing system extracts relevant features for subsequent analysis. A pattern recognition system, employing a robust LDA-XGBoost model, was employed to differentiate between fresh and spoiled fish. …”
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Detecting expert’s eye using a multiple-kernel Relevance Vector Machine by Giuseppe Boccignone, Mario Ferraro, Sofia Crespi, Carlo Robino, Claudio de’Sperati

“…Decoding mental states from the pattern of neural activity or overt behavior is an intensely pursued goal. …”
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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

“…This article uses two methods to detect changepoints: the Pruned Exact Linear Time (PELT) and the interpolation method. …”
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Optimized SPR-PCF sensor for sucrose detection inspired by vertical pupil geometry by Mohammad Reza Khodatars Dashtmian, Vahid Fallahi, Mahmood Seifouri, Saeed Olyaee

“…Abstract In this article, a surface plasmon resonance (SPR) sensor based on photonic crystal fiber (PCF) has been presented for use in detecting the concentration of sucrose solution. This sensor is expertly designed, drawing on the vertical pupil pattern found in the eyes of certain animals to optimize the concentration of the electromagnetic field at the center of the structure. …”
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