Parametric optimization of the slot waveguide characteristics using a machine-learning approach by Yadvendra Singh, Suraj Jena, Harish Subbaraman

“…This specific property of the slot waveguide provides interaction between active material and electric field, which led to many interesting applications, such as optical amplification, optical switching, and optical detection in integrated photonics. In the present work, we combine machine learning (ML) algorithms and finite element simulation to predict the power confinement ( $$\hbox {P}_{conf}$$ ) and mode effective index ( $$\hbox {n}_{eff}$$ ) of slot waveguides with respect to geometric parameters such as gap, slab width, and slab height. …”
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Enhancing Cross-Modal Camera Image and LiDAR Data Registration Using Feature-Based Matching by Jennifer Leahy, Shabnam Jabari, Derek Lichti, Abbas Salehitangrizi

“…Registering light detection and ranging (LiDAR) data with optical camera images enhances spatial awareness in autonomous driving, robotics, and geographic information systems. …”
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A selective CutMix approach improves generalizability of deep learning-based grading and risk assessment of prostate cancer by Sushant Patkar, Stephanie Harmon, Isabell Sesterhenn, Rosina Lis, Maria Merino, Denise Young, G. Thomas Brown, Kimberly M. Greenfield, John D. McGeeney, Sally Elsamanoudi, Shyh-Han Tan, Cara Schafer, Jiji Jiang, Gyorgy Petrovics, Albert Dobi, Francisco J. Rentas, Peter A. Pinto, Gregory T. Chesnut, Peter Choyke, Baris Turkbey, Joel T. Moncur

“…Training and validation of algorithms for cancer detection and grading were completed with three large datasets containing a total of 580 whole-mount prostate slides from 191 RP patients at two centers and 6218 annotated needle biopsy slides from the publicly available Prostate Cancer Grading Assessment dataset. …”
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Automated Pixel Purification for Delineating Pervious and Impervious Surfaces in a City Using Advanced Hyperspectral Imagery Techniques by Payam Sajadi, Mehdi Gholamnia, Stefania Bonafoni, Gerald Mills, Yan-Fang Sang, Zeting Li, Salman Khan, Jiazheng Han, Francesco Pilla

“…This study introduces a novel approach to these changes by integrating Coupled Non-negative Matrix Factorization (CNMF) image fusion with an automatic pixel purification algorithm. By fusing low-resolution hyperspectral (30m) with high-resolution panchromatic (5m) PRISMA imagery, we achieved enhanced spatial resolution, crucial for accurate land use and land cover (LULC) classification. …”
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Estimation of the High-Frequency Feature Slope in Gravitational Wave Signals from Core Collapse Supernovae Using Machine Learning by Alejandro Casallas-Lagos, Javier M. Antelis, Claudia Moreno, Ramiro Franco-Hernández

“…In addition, it is suitable for handling high-dimensional input data and produces efficient results with low computational cost. We evaluated the efficiency and performance of the ML algorithms using a set of metrics to measure their ability to accurately predict the HFF slope within the data set. …”
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Unlocking the bottleneck in forward genetics using whole-genome sequencing and identity by descent to isolate causative mutations. by Katherine R Bull, Andrew J Rimmer, Owen M Siggs, Lisa A Miosge, Carla M Roots, Anselm Enders, Edward M Bertram, Tanya L Crockford, Belinda Whittle, Paul K Potter, Michelle M Simon, Ann-Marie Mallon, Steve D M Brown, Bruce Beutler, Christopher C Goodnow, Gerton Lunter, Richard J Cornall

“…In this strategy, we use a modification of the Lander-Green algorithm to isolate causative recessive and dominant mutations, even at low coverage, on a pure strain background. …”
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Evaluation of Left Ventricular Rotation Using Speckle Tracking Technique in Echocardiographic Images of Coronary Artery Stenosis Patients by Zeinab Alsadat Ahmadi, Manijhe Mokhtari-Dizaji, hamideh khesali

“…This study tried to develop a low-dose CT protocol with the acceptable image quality of skull bone in order to evaluate craniosynostosis. …”
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Feature fusion with attributed deepwalk for protein–protein interaction prediction by Mei-Yuan Cao, Suhaila Zainudin, Kauthar Mohd Daud

“…These complementary features are fused through the weighting mechanism before being processed by the Attributed DeepWalk algorithm, which enhances protein representations by learning low-dimensional embeddings. …”
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“Can computed tomographic angiography” solve the puzzle of complexities in the pediatric complex congenital heart disease’s by Javaid Iqbal, Sheikh Riaz Rasool, Tariq Ahmad Gojwari, Naseer Ahmad Choh, Moonisah Rafiq

“…Effective radiation dose was significantly reduced by employing low radiation protocols. The additional findings detected on CTA in a significant proportion of patients had changed the operative course for surgeons. …”
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High-Quality Multispectral Image Reconstruction for the Spectral Camera Based on Ghost Imaging via Sparsity Constraints Using CoT-Unet by Tao Hu, Jianxia Chen, Shu Wang, Jianrong Wu, Ziyan Chen, Zhifu Tian, Ruipeng Ma, Di Wu

“…To solve the problem of poor quality in ghost imaging via sparsity constraints (GISC) multispectral image reconstruction with correlation operations and compressed sensing algorithms under low sampling rate detection conditions, we propose an end-to-end deep-learning-based method. …”
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Portable Impedance Analyzer for FET-Based Biosensors with Embedded Analysis of Randles Circuits’ Spectra by Norman Pfeiffer, Martin Bach, Alice Steiner, Anna-Elisabeth Gerhardt, Joan Bausells, Abdelhamid Errachid, Albert Heuberger

“…The introduced algorithm was evaluated on 100 simulated spectra of Randles circuits. …”
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Eyes on nature: Embedded vision cameras for terrestrial biodiversity monitoring by Kevin F. A. Darras, Marcel Balle, Wenxiu Xu, Yang Yan, Vincent G. Zakka, Manuel Toledo‐Hernández, Dong Sheng, Wei Lin, Boyu Zhang, Zhenzhong Lan, Li Fupeng, Thomas C. Wanger

“…Our camera uses interchangeable lenses to resolve barely visible and remote targets, as well as customisable algorithms for blob detection, region‐of‐interest classification and object detection to automatically identify them. …”
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A Comprehensive Review of Smartphone and Other Device-Based Techniques for Road Surface Monitoring by Saif Alqaydi, Waleed Zeiada, Ahmed El Wakil, Ali Juma Alnaqbi, Abdelhalim Azam

“…Smartphone sensors, such as accelerometers and gyroscopes, combined with data preprocessing techniques like filtering and reorientation, improve the quality of collected data. Machine learning algorithms, particularly CNNs, are utilized to classify road anomalies, enhancing detection accuracy and system efficiency. …”
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Positioning of Lightning Electromagnetic Radiation Sources With Satellite Constellations: Simulation and Preliminary Validation by Xiao Li, Zongxiang Li, Xiaoqiang Li, Xiong Zhang, Yunfen Chang, Kai Zhang, Yongli Wei, Baofeng Cao, Peng Li

“…This paper presents the study on the three‐dimensional (3D) positioning of LERS utilizing a low‐Earth‐orbit (LEO) satellite constellation. A positioning algorithm was constructed, and a Monte Carlo approach was utilized to simulate positioning capabilities in a LEO satellite configuration, emphasizing the effect of time error on positioning precision. …”
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Online Monitoring of Water-Quality Anomaly in Water Distribution Systems Based on Probabilistic Principal Component Analysis by UV-Vis Absorption Spectroscopy by Dibo Hou, Shu Liu, Jian Zhang, Fang Chen, Pingjie Huang, Guangxin Zhang

“…A small-scale water-pipe distribution network is tested to detect water contamination events. The tests demonstrate that the PPCA-based online monitoring model can achieve satisfactory results under the ROC curve, which denotes a low false alarm rate and high probability of detecting water contamination events.…”
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A “Salt and Pepper” Noise Reduction Scheme for Digital Images Based on Support Vector Machines Classification and Regression by Hilario Gómez-Moreno, Pedro Gil-Jiménez, Sergio Lafuente-Arroyo, Roberto López-Sastre, Saturnino Maldonado-Bascón

“…The results show that the filters proposed achieved good results, outperforming other state-of-the-art algorithms for low and medium noise ratios, and were comparable for very highly corrupted images.…”
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Real-time perception and intelligent early warning technology for power grid control operations based on multi-dimensional data fusion by Wei Li, Chao Hu, Bo Zhou, Weibo Peng

“…This technology integrates dynamic data from factories and stations, operation ticket content, and 3D virtual environment information, and uses deep learning and reinforcement learning algorithms to construct real-time perception and intelligent warning models. …”
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Security-centric node identification in complex networks by Lanying Liu, Ning Du, Duyong Sheng

“…Our experimental evaluation on various network topologies, including random, scale-free, small-world, and real-world networks, demonstrates that the proposed method effectively identifies security-critical nodes with high detection accuracy while maintaining a low false-positive rate. …”
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Source reconstruction accuracy of MEG and EEG Bayesian inversion approaches. by Paolo Belardinelli, Erick Ortiz, Gareth Barnes, Uta Noppeney, Hubert Preissl

“…Still, no correct network detection is possible without reliable source localization. …”
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Machine Learning for Chinese Corporate Fraud Prediction: Segmented Models Based on Optimal Training Windows by Chang Chuan Goh, Yue Yang, Anthony Bellotti, Xiuping Hua

“…The results indicate that segmented models have a better predictive performance than the general model for fraud types with low fraud rates and are as good as the general model for most industries when controlling for training set size. …”
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