A Comparative Evaluation of Machine Learning-Based Intrusion Detection Systems for Securing Cloud Environments by Mohammad Shadi Alhakeem, Khawla Bin Ajlan

“…This research explores the integration of ML technologies in IDS and examines the application of feature selection methods to identify the key and most significant indicators for attack detection. …”
Get full text

Hyperspectral Imaging Combined with Deep Learning for the Early Detection of Strawberry Leaf Gray Mold Disease by Yunmeng Ou, Jingyi Yan, Zhiyan Liang, Baohua Zhang

“…In this study, the early detection of strawberry leaf diseases was performed using hyperspectral imaging combining multi-dimensional features like spectral fingerprints and vegetation indices. …”
Get full text

An FPGA Prototype for Parkinson’s Disease Detection Using Machine Learning on Voice Signal by Mujeev Khan, Abdul Moiz, Gani Nawaz Khan, Mohd Wajid, Mohammed Usman, Jabir Ali

“…This paper proposes an efficient machine learning model for PD detection using voice-based features, which offer a non-invasive, cost-effective, and accessible alternative to complex imaging methods. …”
Get full text

Flexible Adaptive Marine Predator Algorithm and Its Application in Fault Detection for Wind Turbines by WANG Wen, YI Jiabiao

Get full text

Detection and Pattern Recognition of Chemical Warfare Agents by MOS-Based MEMS Gas Sensor Array by Mengxue Xu, Xiaochun Hu, Hongpeng Zhang, Ting Miao, Lan Ma, Jing Liang, Yuefeng Zhu, Haiyan Zhu, Zhenxing Cheng, Xuhui Sun

“…Finally, principal component analysis (PCA) and machine learning algorithms were applied for CWA classification. …”
Get full text

Dynamic analysis of malicious behavior propagation based on feature selection in software network by Huajian Xue, Huajian Xue, Yali Wang, Qiguang Tang

“…This paper introduces a dynamic analysis detection method for malicious behavior based on feature extraction (MBDFE), designed to effectively identify and thwart the spread of malicious software. …”
Get full text

Early stroke behavior detection based on improved video masked autoencoders for potential patients by Meng Wang, Guanci Yang, Kexin Luo, Yang Li, Ling He

“…After that, the optimal parameters of EPBR-PS were determined through the experiment of learning rate and fusion weights of different features. On the NTU-ST dataset, comparative analysis with eight models demonstrated the superiority of EPBR-PS, evidenced by the average recognition accuracy of 89.61%, surpassing that 1.67% over the benchmark VideoMAE. …”
Get full text

Concrete Crack Skeleton Analysis: A Machine Vision Approach to Feature Extraction by Rui Wang, Xinxin Guo, Jiaxuan Liu, Yu Wan

Get full text

XGBoost Algorithm for Cervical Cancer Risk Prediction: Multi-dimensional Feature Analysis by Sudi Suryadi, Masrizal

“…This performance profile indicates adept navigation of the delicate balance between missed diagnoses and unnecessary interventions. Feature importance analysis revealed a multifaceted risk landscape, where screening test results contributed substantial predictive power (approximately 60%), complemented by demographic and behavioral factors, including age, reproductive history, and contraceptive usage patterns. …”
Get full text

Image Processing Using Feature-Based Segmentation Techniques for the Analysis of Medical Images by Christodoss Prasanna Ranjith, Krishnamoorthy Natarajan, Sindhu Madhuri, Mahesh Thylore Ramakrishna, Chandrasekhar Rohith Bhat, Vinoth Kumar Venkatesan

“…Then, the detection of bone fractures is automatically carried out. …”
Get full text

DISTINCT FEATURES OF STAGHORN NEPHROLITHIASIS IN SOUTH OF RUSSIA by A. V. Кhasigov, M. A. Khagokov, I. I. Belousov, M. I. Kogan

Get full text

A Disentangled Representation-Based Multimodal Fusion Framework Integrating Pathomics and Radiomics for KRAS Mutation Detection in Colorectal Cancer by Zhilong Lv, Rui Yan, Yuexiao Lin, Lin Gao, Fa Zhang, Ying Wang

“…In this paper, we propose a Disentangled Representation-based Multimodal Fusion framework integrating Pathomics and Radiomics (DRMF-PaRa) for KRAS mutation detection. Specifically, the DRMF-PaRa model consists of three parts: (1) the pathomics learning module, which introduces a tissue-guided Transformer model to extract more comprehensive and targeted pathological features; (2) the radiomics learning module, which captures the generic hand-crafted radiomics features and the task-specific deep radiomics features; (3) the disentangled representation-based multimodal fusion module, which learns factorized subspaces for each modality and provides a holistic view of the two heterogeneous phenotypic features. …”
Get full text

GENRE FEATURES OF THE POSTMODERN NOVEL “PERFUME: THE STORY OF A MURDERER” BY P. SÜSKIND by Nataliia А. Kovalova

“…The purpose of the article is to define the genre features of Patrick Süskind’s novel as a postmodern work. …”
Get full text

LH Gene Cloning, Sequence Feature Analysis and Prokaryotic Expression in Conger myriaster by Yan CHEN, Bao SHI, Chenggang WANG, Wanjun BO, Kewen YAN, Meijun TAO, Xinyu ZHAO, Xiaodong MA

Get full text

Fractals and Independent Component Analysis for Defect Detection in Bridge Decks by Ikhlas Abdel-Qader, Fadi Abu-Amara, Osama Abudayyeh

“…Using Ground-Penetrating Radar (GPR) raw scans, this framework is composed of a feature extraction algorithm using fractals to detect defective regions and a deconvolution algorithm using banded-independent component analysis (ICA) to reduce overlapping between reflections and to estimate the radar waves travel time and depth of defects. …”
Get full text

A Review of Explainable AI for Android Malware Detection and Analysis by Maryam Tanha, Somayeh Kafaie

“…Recent advances in complex machine learning models have significantly enhanced Android malware detection and analysis. However, these models often operate as closed boxes, making it difficult to understand which aspects of the input data influence their decisions. …”
Get full text

The analysis of fraud detection in financial market under machine learning by Jing Jin, Yongqing Zhang

“…Abstract With the rapid development of the global financial market, the problem of financial fraud is becoming more and more serious, which brings huge economic losses to the market, consumers and investors and threatens the stability of the financial system. Traditional fraud detection methods based on rules and statistical analysis are difficult to deal with increasingly complex and evolving fraud methods, and there are problems such as poor adaptability and high false alarm rate. …”
Get full text

Theoretical and Methodological Features of the Analysis of the Basic Concepts of the Modern Theory of National Security by A. B. Feonichev, K. Yu. Meleshin

Get full text

Recent Advancement in Small Traffic Sign Detection: Approaches and Dataset by R. Suresha, N. Manohar, G. Ajay Kumar, M. Rohit Singh

Get full text

VPN Traffic Analysis: A Survey on Detection and Application Identification by Yasameen Sajid Razooqi, Adrian Pekar

“…Based on a systematic review of the literature, we provide an in-depth analysis of the features, methodologies (including traditional and learning-based approaches), and datasets employed in recent studies. …”
Get full text