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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Automated Detection of Connective Tissue by Tissue Counter Analysis and Classification and Regression Trees by Josef Smolle, Peter Kahofer

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Static Analysis-based Detection of Android Malware using Machine Learning Algorithms by Omar Emad Saied, Karam Hatim Thanoon

“…The rapid growth of Android applications has led to increased security threats, making malware detection a critical concern in cybersecurity. This research proposes a static analysis-based technique that employs machine learning for Android malware detection. …”
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Audio–Visual Synchronization and Lip Movement Analysis for Real-Time Deepfake Detection by Muhammad Javed, Zhaohui Zhang, Fida Hussain Dahri, Asif Ali Laghari, Martin Krajčík, Ahmad Almadhor

“…To address this issue, we propose a novel Audio–Visual Synchronisation and Fusion Framework (AVSFF) for real-time detection of deepfakes. This approach focuses on fine-grained lip movement analysis by detecting subtle inconsistencies between lip movements and corresponding audio. …”
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Multilingual Sarcasm Detection for Enhancing Sentiment Analysis using Deep Learning Algorithms by Ahmed Derbala Yacoub, Amal Elsayed Aboutabl, Salwa O. Slim

“…This research explores how sentiment analysis (SA) and sarcasm detection (SD) intersect, highlighting challenges in identifying how sarcasm influences sentiment polarity. …”
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Tongue Color Analysis and Diseases Detection Based on a Computer Vision System by Abdulghafor Khudhaer Abdullah, Saleem Lateef Mohammed, Ali Al-Naji, Mohammed Sameer Alsabah

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Wavelet-Based Analysis of Motor Current Signals for Detecting Obstacles in Train Doors by Yaojung Shiao, Premkumar Gadde, Chun-Yu Liu

“…The norm and peak of the current are used as obstacle detection features, and appropriate threshold values are obtained from a simulation. …”
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Video-Based Detection Infrastructure Enhancement for Automated Ship Recognition and Behavior Analysis by Xinqiang Chen, Lei Qi, Yongsheng Yang, Qiang Luo, Octavian Postolache, Jinjun Tang, Huafeng Wu

“…Ship behavior analysis, one of the fundamental tasks for fulfilling smart video-based detection infrastructure, has become an active topic in the CAS community. …”
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YLOMF: You Look Once for Multi-Feature—A Multi-Feature Multi-Task Network for Intelligent Real-Time Perception in Autonomous Driving by B. N. Anoop, S. K. Abhilash, Venu Madhav Nookala, S. Prita, S. Raghavendra

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A study for method-level code smells detection using machine learning algorithms by Rajwant Singh Rao, Seema Dewangan, Alok Mishra, Manjari Gupta

“…Although several machine learning algorithms have been proposed to detect code smells, the impact of feature selection and cross-validation on certain method-level smells, specifically Long Parameter List and Switch Statements, has not been adequately explored in prior research. …”
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FF-YOLO: An Improved YOLO11-Based Fatigue Detection Algorithm for Air Traffic Controllers by Shijie Tan, Weijun Pan, Leilei Deng, Qinghai Zuo, Yao Zheng

“…This paper proposes FF-YOLO, an improved YOLO11-based deep learning algorithm, to detect ATCO fatigue states through facial feature analysis. …”
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Prodromal Parkinsonian Features in Carriers of Gaucher Disease Compared to Controls by Michal Becker-Cohen, Ari Zimran, Tama Dinur, Maayan Tiomkin, Arndt Rolfs, David Arkadir, Peter Bauer, Elena Shulman, Gilad Yahalom, Mikhal E. Cohen, Orly Manor, Ora Paltiel, Shoshana Revel-Vilk

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Machine learning for brain tumor classification: evaluating feature extraction and algorithm efficiency by Krishan Kumar, Kiran Jyoti, Krishan Kumar

“…The objective of this study is to identify best combination of machine learning and features extraction method for brain tumor detection and classification. …”
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Features of accumulation of inorganic elements in seeds of white mustard (Sinapis alba L.) and black mustard (Brassica nigra L.) by О. І. Рудник-Іващенко, Л. М. Михальська, В. В. Швартау

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Enhanced Superpixel-Guided ResNet Framework with Optimized Deep-Weighted Averaging-Based Feature Fusion for Lung Cancer Detection in Histopathological Images by Karthikeyan Shanmugam, Harikumar Rajaguru

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Evaluating the Performance of Machine Learning Classifiers for Network Intrusion Detection: A Comparative Study Using the UNSW-NB15 Dataset by Iwan Handoyo Putro

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Traffic Scene Analysis using Hierarchical Sparse Topical Coding by P. Ahmadi, I. Gholampour, M. Tabandeh

“…Such descriptions may further be employed in different traffic applications such as traffic phase detection and abnormal event detection. One of the most recent and successful unsupervised methods for complex traffic scene analysis is based on topic models. …”
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SMS Scam Detection Application Based on Optical Character Recognition for Image Data Using Unsupervised and Deep Semi-Supervised Learning by Anjali Shinde, Essa Q. Shahra, Shadi Basurra, Faisal Saeed, Abdulrahman A. AlSewari, Waheb A. Jabbar

“…To address this, we merge a UCI spam dataset of regular text messages with real-world spam data, leveraging OCR technology for comprehensive analysis. The study employs a combination of traditional machine learning models, including K-means, Non-Negative Matrix Factorization, and Gaussian Mixture Models, along with feature extraction techniques such as TF-IDF and PCA. …”
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Cross-Layer Feature Fusion and Decentration Aberration Correction of Circular Points for Automated Guided Vehicle Terminal Positioning by Guiyang Zhang, Lanyu Yang, Kunkang Cao, Zengguang Man, Jian Wu, Boning Li

“…To address the visual detection and positioning challenge of the Automated Guided Vehicle (AGV) terminal, this study proposed a high-precision target recognition and positioning strategy based on cross-layer feature fusion and eccentricity error correction. …”
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Rock fracture type recognition based on deep feature learning of microseismic signals by LI Dianze, XU Huajie, ZHANG Bo

“…Microseismic monitoring has been widely used for detecting rock fractures. However, conventional machine learning methods for microseismic signal analysis exhibited limited feature extraction capabilities and were highly susceptible to noise, leading to reduced classification accuracy and poor generalization performance. …”
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