Automated breast cancer detection by reconstruction independent component analysis (RICA) based hybrid features using machine learning paradigms by Lal Hussain, Shahzad Ahmad Qureshi, Amjad Aldweesh, Jawad ur Rehman Pirzada, Faisal Mehmood Butt, Elsayed Tag eldin, Mushtaq Ali, Abdulmohsen Algarni, Muhammad Amin Nadim

“…Various machine learning techniques have been employed to detect breast cancer, viz. Support Vector Machines (SVM), Decision Trees (DT), k-Nearest Neighbour, and Naïve Bayes classifiers. …”
Get full text

Characterizing and Detecting Multiscenario Degradation of the Maidika Alpine Wetland Nature Reserve in the Qinghai–Tibet Plateau Using Landsat Time Series by Ye Chen, Ren Ci, Dongping Zhong, Liangyun Liu, Jinyuan Yu, Dongdong Zhang, Yindong Tong, Yingchun Fu

“…Based on 3 elements, spectral–temporal characterization, classification, and degradation detection for wetland covers, this study proposes a continuous classification and degradation detection algorithm for alpine wetlands (AW-CCD). …”
Get full text

Sensing dynamic human activity zones using geo-tagged big data in Greater London, UK during the COVID-19 pandemic. by Tongxin Chen, Di Zhu, Tao Cheng, Xiaowei Gao, Huanfa Chen

“…Lastly, we examined the feature importance of explanatory variables as the metric of the relationship between human activity and urban characteristics using machine learning classifiers. The results show that dynamic human activity exhibits statistically significant differences in terms of the HAZ distributions across restriction phases and is strongly associated with urban characteristics (e.g., specific land use types) during the COVID-19 pandemic. …”
Get full text

Land use and land cover dynamics of the Weito River catchment in the Ethiopian rift using remote sensing and CA Markov modelling approaches by Tamene Tadele, Yohannes Degu, Abraham Mechal

“…The present study assessed the spatio-temporal dynamics of LULC in the Weito River Catchment (WRC) by classifying satellite images from 1986 (LANDSAT-5), 2003 (LANDSAT-7), and 2023 (LANDSAT-9) using maximum likelihood classification algorithm. …”
Get full text

Dynamics and Prediction of Land Use and Land Cover Changes Using Geospatial Techniques in Abelti Watershed, Omo Gibe River Basin, Ethiopia by Melkamu Ateka Derebe, Samuel Dagalo Hatiye, Ligalem Agegn Asres

“…Quantifications of spatial and temporal dynamics of land use/cover changes were accomplished by using three satellite images of 2000, 2010, and 2017 and classifying them via a supervised classification algorithm by using Earth Resources and Development System (ERDAS) software and finally applying the postclassification change detection technique was performed by using ArcGIS 10.3. …”
Get full text

Using LandTrendr to analyze forest disturbance, recovery, and attribution in Hunan province from 2001 to 2024 by Panlin Cao, Zhuo Zang, Meng Zhang, Xu Wang, Xian Tang, Jiahong Xiang, Shu Tang, Jing Wang, Yanan Zhang

“…This study uses Google Earth Engine and Landsat data (2001–2024) with the LandTrendr algorithm to detect spatiotemporal forest disturbances and recovery in Hunan Province, applying a random forest classifier to identify disturbance types. …”
Get full text

Spot the bot: the inverse problems of NLP by Vasilii A. Gromov, Quynh Nhu Dang, Alexandra S. Kogan, Assel Yerbolova

Get full text

A Comprehensive Comparative Study of Quick Invariant Signature (QIS), Dynamic Time Warping (DTW), and Hybrid QIS + DTW for Time Series Analysis by Hamid Reza Shahbazkia, Hamid Reza Khosravani, Alisher Pulatov, Elmira Hajimani, Mahsa Kiazadeh

“…This study presents a comprehensive evaluation of the quick invariant signature (QIS), dynamic time warping (DTW), and a novel hybrid QIS + DTW approach for time series analysis. …”
Get full text

Method for detecting rough road index using iot sensor fusion and v2v interaction for efficient road infrastructure management by Akhilesh Kumar Singh, Damodar Reddy Edla

Get full text

Advanced Hybrid Transformer-CNN Deep Learning Model for Effective Intrusion Detection Systems with Class Imbalance Mitigation Using Resampling Techniques by Hesham Kamal, Maggie Mashaly

“…Network and cloud environments must be fortified against a dynamic array of threats, and intrusion detection systems (IDSs) are critical tools for identifying and thwarting hostile activities. …”
Get full text

GSPSO-LRF-ELM: Grid Search and Particle Swarm Optimization-Based Local Receptive Field-Enabled Extreme Learning Machine for Surface Defects Detection and Classification on the Magn... by Jun Xie, Jin Zhang, Fengmei Liang, Yunyun Yang, Xinying Xu, Junjie Dong

Get full text

Performance-Oriented and Sustainability-Oriented Design of an Effective Android Malware Detector by Sana Qadir, Amna Naeem, Mehdi Hussain, Huma Ghafoor, Aisha Hassan Abdalla Hashim

“…Keeping these design priorities in mind, we develop and empirically evaluate four different classifiers. Firstly, to ensure high detection rate, we use a dataset compiled using hybrid analysis of a diverse set of apps. …”
Get full text

Enhancing IoT cybersecurity through lean-based hybrid feature selection and ensemble learning: A visual analytics approach to intrusion detection. by Islam Zada, Esraa Omran, Salman Jan, Hessa Alfraihi, Seetah Alsalamah, Abdullah Alshahrani, Shaukat Hayat, Nguyen Phi

“…The dynamical growth of cyber threats in IoT setting requires smart and scalable intrusion detection systems. …”
Get full text

Optimized ReXNet variants with spatial pyramid pooling, CoordAttention, and convolutional block attention module for money plant disease detection by Parul Nasra, Jaibir Singh, Suman Rani, Gunjan Shandilya, Salil Bharany, Sandeep Sood, Ateeq Ur Rehman, Seada Hussen

Get full text

Detecting the Black Hole Candidate Population in M51’s Young Massive Star Clusters: Constraints on Accreting Intermediate-mass Black Holes by Kristen C. Dage, Evangelia Tremou, Bolivia Cuevas Otahola, Eric W. Koch, Kwangmin Oh, Richard M. Plotkin, Vivian L. Tang, Muhammad Ridha Aldhalemi, Zainab Bustani, Mariam Ismail Fawaz, Hans J. Harff, Amna Khalyleh, Timothy McBride, Jesse Mason, Anthony Preston, Cortney Rinehart, Ethan Vinson, Gemma Anderson, Edward M. Cackett, Shih Ching Fu, Sebastian Kamann, Teresa Panurach, Renuka Pechetti, Payaswini Saikia, Susmita Sett, Ryan Urquhart, Christopher Usher

“…They have long been linked to dense star cluster environments, thanks to cluster dynamics, but there are a limited number of secure detections. …”
Get full text

Multimodal Model for Non-Invasive Detection of DRD2, SSTR2 and ESR1 Receptor Profiling in Pituitary Neuroendocrine Tumors: A Retrospective Study by Jianglong Lu MD, Xianpeng Wang MBBS, Jinghao Jin MBBS, Fanjie Xu MBBS, Runhua Tang MBBS, Cheng Han MD, Zerui Wu MD, Zhipeng Su PhD, Yuhang Guo PhD

Get full text

BREAST-RANKNet: a fuzzy rank-based ensemble of CNNs with residual learning for enhanced breast cancer detection from ultrasound and mammogram images by Sohaib Asif, Lingying Zhu, Dane Yan, Luman Xu, Zhengqiu Huang, Haimin Xu, Ruxuan Yan, Linghong Cai, Changfu Zheng, Jiamei Lin, Enyu Wang

“…Abstract Breast cancer (BC) detection with medical imaging, like ultrasound and mammography, has advanced with deep learning (DL). …”
Get full text

Integrated Lower Limb Robotic Orthosis with Embedded Highly Oriented Electrospinning Sensors by Fuzzy Logic-Based Gait Phase Detection and Motion Control by Ming-Chan Lee, Cheng-Tang Pan, Jhih-Syuan Huang, Zheng-Yu Hoe, Yeong-Maw Hwang

“…A fuzzy logic inference system processes these signals, classifying gait phases such as stance, initial contact, mid-stance, and pre-swing. …”
Get full text

An Interpretable Machine Learning Framework for Athlete Motor Profiling Using Multi-Domain Field Assessments: A Proof-of-Concept Study by Bartosz Wilczyński, Maciej Biały, Katarzyna Zorena

Get full text

Enhanced surface deformation monitoring in open-pit mines via dynamic filtering and multiscale adaptive interpolation of D-InSAR/offset tracking fusion by Yuejuan Chen, Dejun Zhao, Pingping Huang, Bo Yin, Zhiqi Gao, Weixian Tan, Yaolong Qi, Wei Xu

“…The method uses multiscale Gaussian decomposition to separate global and local deformation features and applies adaptive dynamic filtering, which employs edge detection and adaptively switches between NLMS and LMS filters, based on the relative difference ratio to suppress noise and enhance edge details. …”
Get full text