Study of component features of essential oils of <i>Rosmarinus officinalis</i> and <i>Salvia sclarea</i> of Crimean origin by R. E. Ermachenkov, A. L. Markov, M. M. Agaev, E. V. Burtseva, I. I. Terninko

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River Channel Microgeomorphic Feature Extraction and Potential Sandstorm Source Identification Method Based on a Convolutional Autoencoder Model by Kecong Wu, Lirong Chen, Yalige Bai, Xinhang Wang, Danzeng Pingcuo, Zhongpeng Han, Chengshan Wang

“…River channel&#x0027;s microgeomorphic features are crucial for identifying potential sandstorm sources and studying sediment source-sink processes. …”
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Soft detection model of corrosion leakage risk based on KNN and random forest algorithms by Yang YANG, Chengzhi LI, Xuan DU, Xiao YU, Shaohua DONG

“…Consequently, enhancing both the quantity and quality of detection data, along with refining the feature extraction approach for key risk indicators, is anticipated to further boost the accuracy of the model. …”
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A NOVEL VOICE-BASED SYSTEM FOR PARKINSON’S DISEASE DETECTION USING RNN-LSTM by Repudi Pitchiah, T. Sasi Rooba, Uma Pavan Kumar

“…In this study, RNN-LSTM is combined with numerous architectures to develop more accurate prediction models for the detection of PD on the basis of feature analysis of various patient speech samples. …”
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Distributed denial-of-service (DDOS) attack detection using supervised machine learning algorithms by S. Abiramasundari, V. Ramaswamy

“…In this paper, a PCA-based Enhanced Distributed DDoS Attack Detection (EDAD) framework has been proposed. Various Machine Learning (ML) algorithms and feature selection techniques have been used to detect DDoS attacks. …”
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Multivariate Statistical Approach for Anomaly Detection and Lost Data Recovery in Wireless Sensor Networks by Roberto Magán-Carrión, José Camacho, Pedro García-Teodoro

“…The present paper introduces a novel data loss/modification detection and recovery scheme in this context. Both elements, detection and data recovery, rely on a multivariate statistical analysis approach that exploits spatial density, a common feature in network environments such as WSNs. …”
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Enhancing Malware Detection via RGB Assembly Visualization and Hybrid Deep Learning Models by Esra Eroğlu Demirkan, Murat Aydos

“…This research contributes to the field by integrating static binary analysis with advanced computer vision techniques, offering a scalable and effective solution for malware detection.…”
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ObjectDetection in Agriculture: A Comprehensive Review of Methods, Applications, Challenges, and Future Directions by Zohaib Khan, Yue Shen, Hui Liu

“…This comprehensive review synthesizes object detection methodologies, tracing their evolution from traditional feature-based approaches to cutting-edge deep learning architectures. …”
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Advances and Challenges in Deep Learning for Automated Welding Defect Detection: A Technical Survey by Abdulrahim Mohammed, Muhammad Hussain

“…The study also highlights the integration of advanced preprocessing techniques, such as noise reduction and contrast enhancement, within DL workflows to improve feature extraction and detection accuracy. Persistent challenges, such as the scarcity of large, labeled datasets, lack of real-time applicability, and limited model interpretability, are explored in depth. …”
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Lightweight and Accurate YOLOv7-Based Ensembles With Knowledge Distillation for Urinary Sediment Detection by Keita Sasaki, Hiroki Nishikawa, Ittetsu Taniguchi, Takao Onoye

“…To address these demands, we propose a lightweight and accurate detection framework that combines YOLOv7-based ensemble learning with feature-based knowledge distillation. …”
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Assessing ML classification algorithms and NLP techniques for depression detection: An experimental case study. by Giuliano Lorenzoni, Cristina Tavares, Nathalia Nascimento, Paulo Alencar, Donald Cowan

“…Early mental disorder detection can reduce costs for public health agencies and prevent other major comorbidities. …”
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Breast mass lesion area detection method based on an improved YOLOv8 model by Yihua Lan, Yingjie Lv, Jiashu Xu, Yingqi Zhang, Yanhong Zhang

“…Future work will explore the potential applications of the developed models to other medical image analysis tasks.…”
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Combined Thermal Index Development for Urban Heat Island Detection in Area of Split, Croatia by Majda Ćesić, Katarina Rogulj, Andrija Krtalić

“…This research compares ground-based and sensor-based temperatures, and their analysis results in the proposal of a new index: the Combined Thermal Index. …”
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A Garbage Detection and Classification Method Based on Visual Scene Understanding in the Home Environment by Yuezhong Wu, Xuehao Shen, Qiang Liu, Falong Xiao, Changyun Li

“…Aiming at the problems of complex systems with data source and cloud service center data transmission delay and untimely response, at the same time, in order to realize the perception, storage, and analysis of massive multisource heterogeneous data, a garbage detection and classification method based on visual scene understanding is proposed. …”
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Enhancing Software Quality with AI: A Transformer-Based Approach for Code Smell Detection by Israr Ali, Syed Sajjad Hussain Rizvi, Syed Hasan Adil

“…Traditional machine-learning techniques, such as gradient boosting and support vector machines (SVM), have demonstrated effectiveness in code smell detection but require extensive feature engineering and struggle to capture intricate semantic dependencies in software structures. …”
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Machine Learning Approaches for Data-Driven Self-Diagnosis and Fault Detection in Spacecraft Systems by Enrico Crotti, Andrea Colagrossi

“…Fault scenarios are defined based on potential failures in these elements, guiding the data-driven feature extraction and labeling process. Supervised learning algorithms, including Support Vector Machines (SVMs) and Artificial Neural Networks (ANNs), are implemented and benchmarked against a simple threshold-based detection method. …”
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Cyberattack Detection Systems in Industrial Internet of Things (IIoT) Networks in Big Data Environments by Abdullah Orman

“…Second, while existing studies frequently favor hybrid models, findings from this study reveal that the standalone MLP model outperforms other architectures, achieving the highest detection accuracy of 99.99%. This outcome highlights the critical role of dataset-specific feature distributions in determining model effectiveness and calls for a more nuanced approach when selecting detection models for IIoT cybersecurity applications. …”
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SensorDBSCAN: Semi-Supervised Active Learning Powered Method for Anomaly Detection and Diagnosis by Petr Ivanov, Maria Shtark, Alexander Kozhevnikov, Maksim Golyadkin, Dmitry Botov, Ilya Makarov

“…Fault detection and diagnosis (FDD) is a critical challenge in industrial processes aimed at minimizing risks such as safety hazards, costly downtime, and suboptimal production. …”
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Artificial Intelligence for DC Arc Fault Detection in Photovoltaic Systems: A Comprehensive Review by Kamal Chandra Paul, Disnebio Waldmann, Chen Chen, Yao Wang, Tiefu Zhao

“…This review article provides a comprehensive analysis of AI-based techniques for series arc fault detection in PV systems, covering key aspects such as data preprocessing, feature extraction, model optimization, and hardware implementation. …”
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Driver drowsiness shield (DDSH): a real-time driver drowsiness detection system by Archita Bhanja, Dibyajyoti Parhi, Dipankar Gajendra, Kreetish Sinha, Arup Kumar Sahoo

“…This paper aims to develop an advanced real-time drowsiness detection system using deep learning algorithms. For this purpose, we utilized an eye image dataset from the MRL Eye Dataset and performed extensive feature engineering and preprocessing to prepare the data for analysis. …”
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