Optimal Coverage Path Planning for UAV-Assisted Multiple USVs: Map Modeling and Solutions by Shaohua Pan, Xiaosu Xu, Yi Cao, Liang Zhang

“…To this end, an innovative coverage path planning algorithm for UAV-assisted multiple USVs is proposed. …”
Get full text

A Lightweight Human Activity Recognition Method for Ultra-wideband Radar Based on Spatiotemporal Features of Point Clouds by Yongkun SONG, Tianxing YAN, Ke ZHANG, Xian LIU, Yongpeng DAI, Tian JIN

“…To address the issues of high computational complexity and extensive network parameters in existing action recognition algorithms, this study proposes an efficient and lightweight human activity recognition method using UWB radar based on spatiotemporal point clouds. …”
Get full text

Comparison of Satellite-based PM2.5 Estimation from Aerosol Optical Depth and Top-of-atmosphere Reflectance by Heming Bai, Zhi Zheng, Yuanpeng Zhang, He Huang, Li Wang

“…For both reflectance-based and AOD-based approaches, our cross validated results show that random forest algorithm achieves the best performance, with a coefficient of determination (R2) of 0.75 and root-mean-square error (RMSE) of 18.71 µg m−3 for the former and R2 = 0.65 and RMSE = 15.69 µg m−3 for the later. …”
Get full text

Effects of image compression on face image manipulation detection: A case study on facial retouching by Christian Rathgeb, Kevin Bernardo, Nathania E. Haryanto, Christoph Busch

“…Subsequently, reference images are compressed applying JPEG and JPEG 2000 at compression levels recommended for face image storage in electronic travel documents. Novel detection algorithms utilising texture descriptors and deep face representations are proposed and evaluated in a single image and differential scenario. …”
Get full text

Optimizing transient gas network control for challenging real-world instances using MIP-based heuristics by Hennings, Felix, Hoppmann-Baum, Kai, Zittel, Janina

“…To demonstrate the competitiveness of our approach, we test our algorithm on particularly challenging historical demand scenarios. …”
Get full text

Separating and quantifying facility-level methane emissions with overlapping plumes for spaceborne methane monitoring by Y. Pang, Y. Pang, L. Tian, D. Hu, S. Gao, G. Liu, G. Liu

“…However, the prevailing quantification algorithms usually require the methane column plume from a solitary point source as input. …”
Get full text

THE ACCEPTANCE OF AN EDUCATIONAL INTEGRATED DEVELOPMENT ENVIRONMENT TO LEARN PROGRAMMING FUNDAMENTALS by Nor Farahwahida Mohd Noor, Aslina Saad, Abu Bakar Ibrahim, Norashady Mohd Noor

“…The goal is to guide the users in problem-solving and help them write C programs based on problem-solving algorithms. The Rapid Application Development (RAD) Model was employed in the C-SOLVIS development process. …”
Get full text

Vision-Based Pick and Place Control System for Industrial Robots Using an Eye-in-Hand Camera by van-Truong Nguyen, Phu-Tuan Nguyen, Shun-Feng Su, Phan Xuan Tan, Thanh-Lam Bui

“…To address this issue, our research focuses on utilizing a low-cost 2D camera combined with deep learning algorithms mounted on the end-effector of the robotic arm. …”
Get full text

Fecal occult blood affects intestinal microbial community structure in colorectal cancer by Wu Guodong, Wu Yinhang, Wu Xinyue, Shen Hong, Chu Jian, Qu Zhanbo, Han Shuwen

“…Characteristic gut bacteria were screened, and various machine learning algorithms were applied to construct CRC risk prediction models. …”
Get full text

Blood-based biomarkers in patients with non-small cell lung cancer treated with immune checkpoint blockade by Yo-Ting Tsai, Jeffrey Schlom, Renee N. Donahue

“…Integration of multiple blood-based biomarkers into comprehensive panels or algorithms also has the potential to enhance predictive accuracy. …”
Get full text

A Novel Audio Copy Move Forgery Detection Method With Classification of Graph-Based Representations by Beste Ustubioglu, Gul Tahaoglu, Arda Ustubioglu, Guzin Ulutas, Muhammed Kilic

“…In this stage, the filtered audio is represented as a graph using the proposed spiral pattern information extraction method. Graph coloring algorithms are applied to convert the graph into a visual representation, which is then input into a specially designed Convolutional Neural Network (CNN) model for classification. …”
Get full text

Cryptanalysis of hyperchaotic S-box generation and image encryption by Mohammad Mazyad Hazzazi, Gulraiz, Rashad Ali, Muhammad Kamran Jamil, Sameer Abdullah Nooh, Fahad Alblehai

“…Because they feature substitution boxes, substitution-permutation networks (SPNs) are crucial for cryptographic algorithms such as the popular Advanced Encryption Standard (AES). …”
Get full text

Fractal analysis and microstructure development PVDF based multifunctional material by Peleš-Tadić Adriana, Vuković George, Kojović Aleksandar, Stojanović Dušica, Vlahović Branislav, Obradović Nina, Pavlović Vladimir

“…Theory of Iterated Function Systems and Voronoi tessellation, have been used for modeling PVDF porous structures. A Python algorithm was created to determine the distribution of pore areas in SEM micrographs. …”
Get full text

Constructing a machine learning model for systemic infection after kidney stone surgery based on CT values by Jiaxin Li, Yao Du, Gaoming Huang, Yawei Huang, Xiaoqing Xi, Zhenfeng Ye

“…Five machine learning algorithms and ten preoperative or intraoperative variables were used to develop a predictive model for SIRS. …”
Get full text

Identification of cell chemistries in lithium-ion batteries: Improving the assessment for recycling and second-life by Christopher Wett, Jörg Lampe, Dominik Görick, Thomas Seeger, Bugra Turan

“…The dV/dQ characteristics are chosen as features and four machine learning algorithms are trained on different lengths of OCV curves. …”
Get full text

The Referenced Vertex Ordering Problem: Theory, Applications, and Solution Methods by Omer, Jérémy, Mucherino, Antonio

“…We then discuss how upper and lower bounds can be computed during the enumeration to design a branch-and-bound algorithm. Finally, we validate our branch-and-bound algorithm by conducting a large set of computational experiments on instances coming from various real-life applications. …”
Get full text

ML-AMPSIT: Machine Learning-based Automated Multi-method Parameter Sensitivity and Importance analysis Tool by D. Di Santo, C. He, F. Chen, L. Giovannini

“…This tool leverages the strengths of multiple regression-based and probabilistic machine learning methods, including LASSO (see the list of abbreviations in Appendix B), support vector machine, classification and regression trees, random forest, extreme gradient boosting, Gaussian process regression, and Bayesian ridge regression. These regression algorithms are used to construct computationally inexpensive surrogate models to effectively predict the impact of input parameter variations on model output, thereby significantly reducing the computational burden of running high-fidelity models for sensitivity analysis. …”
Get full text

A Novel Method to Evaluate the Effect of Slope Blasting under Impact Loading by Wenhai Zhou, Zhenbao Li, Xin Wu, Shujiang Wang, Yaru Lv, Xiaoming Lou, Chaofei Du, Rui Liang

“…The validity index of the maximum membership principle is used to assess the accuracy of the evaluation results of two algorithms, and a relevant approaching degree is chosen to optimize the results. …”
Get full text

Safety Improvements for Personnel and Vehicles in Short-Term Construction Sites by Daniel Rau, Jonas Vogt, Philipp Schorr, Juri Golanov, Andreas Otte, Jens Staub, Horst Wieker

“…Focusing on defining the exact dimensions of static construction sites, this method employs high-precision Real-Time-Kinematics-GNSS for localizing traffic cones and deriving the construction site geometry through respective algorithms. By analyzing the geometry, we can identify situations where maintenance personnel are in close proximity to the active lane or when vehicles enter the construction site. …”
Get full text

Biomimic models for in vitro glycemic index: Scope of sensor integration and artificial intelligence by Mohammed Salman C K, Muskan Beura, Archana Singh, Anil Dahuja, Vinayak B. Kamble, Rajendra P. Shukla, Sijo Joseph Thandapilly, Veda Krishnan

“…Non-enzymatic sensors offer superior stability and repeatability in complex matrices, enabling real-time glucose quantification across multiple timepoints without enzyme degradation constraints. Machine learning algorithms, both supervised and unsupervised, enhance predictive accuracy by elucidating complex relationships within digestion data. …”
Get full text