Detecting Fake Reviews Using Aspect-Based Sentiment Analysis and Graph Convolutional Networks by Prathana Phukon, Petros Potikas, Katerina Potika

“…We present an aspect-based sentiment analysis approach, referred to as FakeDetectionGCN, to distinguish genuine feedback from deceptive content. …”
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Concrete Structure Identification and Damage Detection Based on Genetic Algorithm Combined with Cluster Analysis by Xukai Ren, Ke Wang, Xiaofang Han, JingYi Zhang

“…To improve the accuracy of concrete structure identification and damage detection, this study uses acoustic emission technology to obtain various waveform parameter features in the structure. …”
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Machine Learning Models for DDoS Detection in Software-Defined Networking: A Comparative Analysis by Ferdiansyah Ferdiansyah, Darius Antoni, Muhammad Valdo, Mikko Mikko, Chairul Mukmin, Usman Ependi

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A Data-Driven Comparative Analysis of Machine-Learning Models for Familial Hypercholesterolemia Detection by Tomasz Kocejko

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CNN Based Deep Learning Modeling with Explainability Analysis for Detecting Fraudulent Blockchain Transactions by Mohammad Hasan, Mohammad Shahriar Rahman, Mohammad Jabed Morshed Chowdhury, Iqbal H. Sarker

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Honey Adulteration Detection via Ultraviolet–Visible Spectral Investigation Coupled with Chemometric Analysis by Elisabeta-Irina Geană, Raluca Isopescu, Corina-Teodora Ciucure, Cristiana Luminița Gîjiu, Ana Maria Joșceanu

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Abnormal events detection using spatio-temporal saliency descriptor and fuzzy representation analysis by R. Tino Merlin, R. Karthick, A. Aalan Babu, G. Vennira Selvi, D. Usha, R. Nithya

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Comparative analysis of data transformation methods for detecting non-technical losses in electricity grids by Maria Gabriel Chuwa, Daniel Ngondya, Rukia Mwifunyi

“…This study explores various methods for transforming energy consumption patterns into two-dimensional (2D) representations to enhance feature extraction and NTL detection. Six encoding techniques for time series data were evaluated: Markov transition fields (MTF), Gramian angular summation field (GASF), Gramian angular difference field (GADF), Recurrence plots (RP), and time–frequency analysis methods, including short-time Fourier transform (STFT) and continuous wavelet transform (CWT). …”
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A Novel Supervoxel-Based NE-PC Model for Separating Wood and Leaf Components from Terrestrial Laser Scanning Data by Shengqin Gong, Xin Shen, Lin Cao

“…However, previous studies on wood–leaf separation exhibited limitations in unsupervised adaptability and robustness to complex tree architectures, while demonstrating inadequate performance in fine branch detection. This study proposes a novel unsupervised model (NE-PC) that synergizes geometric features with graph-based path analysis to achieve accurate wood–leaf classification without training samples or empirical parameter tuning. …”
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Research on soybean leaf disease recognition in natural environment based on improved Yolov8 by Chen Chen, Chen Chen, Xiaolei Lu, Lei He, Lei He, Ruoxue Xu, Ruoxue Xu, Yi Yang, Yi Yang, Jing Qiu, Jing Qiu

“…A lightweight detection head (LSCD) is further introduced to facilitate multiscale feature interactions while reducing the overall model parameter count. …”
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Bimodal data analysis for early detection of lameness in dairy cows using artificial intelligence by Yashan Dhaliwal, Hangqing Bi, Suresh Neethirajan

“…To address the urgent need for early detection, we introduce a novel bimodal artificial intelligence (AI) framework that leverages both facial biometric data and accelerometer-based movement metrics. …”
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Detecting faults in electronic combustion engine control systems by acoustic parameters by V. D. Gabidulin, V. N. Dobromirov

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Effective classification of android malware families through dynamic features and neural networks by Gianni D'Angelo, Francesco Palmieri, Antonio Robustelli, Arcangelo Castiglione

“…Furthermore, the creation of a training dataset that well represents the malware properties and behaviour is one of the most critical challenges in malware analysis. Therefore, the main aim of this paper is proposing a new dataset called Unisa Malware Dataset (UMD) available on http://antlab.di.unisa.it/malware/, which is based on the extraction of static and dynamic features characterising the malware activities. …”
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Automated detection of submarine pipelines in the Yellow River Estuary: a deep learning approach for side-scan sonar data in dynamic deltaic systems by Min Wei, Min Wei, Yongqing Yu, Xing Du, Yupeng Song, Lifeng Dong, Qikun Zhou, Linfeng Wang, Longying Zhang, Yamei Wang

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Molecular Detection of Feline Panleukopenia Virus From Clinical Cases in India by P. Saranraj, M. Manigandan, R. Nisha, L. Yuvalakshmi

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Sysmon event logs for machine learning-based malware detection by Riki Mi’roj Achmad, Dyah Putri Nariswari, Baskoro Adi Pratomo, Hudan Studiawan

“…An extensive set of experiment were conducted to look for the best approach and the most relevant features. Principal Component Analysis (PCA) was applied to select the most relevant features for both supervised and unsupervised learning models. …”
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Early detection of triple-negative breast cancer: evidence of a favourable prognostic impact in a comparative analysis of screen-detected versus symptomatic cases by Isabella Castellano, Stefano Rousset, Denise Casella, Giulia Capella, Fulvio Borella, Martina Di Rosa, Paola Cassoni, Alberto Catalano, Gianluigi Ferrante, Livia Giordano

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Enhanced intrusion detection model based on principal component analysis and variable ensemble machine learning algorithm by Ayuba John, Ismail Fauzi Bin Isnin, Syed Hamid Hussain Madni, Farkhana Binti Muchtar

“…Principal Component Analysis (PCA) has proven to be a helpful feature selection technique for dimensionality reduction. …”
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ALGORITHM FOR complex SMOKE AND FLAME detection based on video surveillance systems data analysis by R. P. Bohush, D. A. Tychko

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Comparative Analysis of Keypoint Detection Performance in SIFT Implementations on Small-Scale Image Datasets by Arif Rahman, Suprihatin, Imam Riadi, Tawar, Furizal

“…This study examines the keypoint extraction of three well-known SIFT libraries, i.e., David Lowe's implementation, OpenSIFT, and vlSIFT in vlfeat. Performance analysis was conducted on multiclass small-scale image datasets to capture the sensitivity of keypoint detection. …”
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