Hybrid Ensemble Pruning Using Coevolution Binary Glowworm Swarm Optimization and Reduce-Error by Xuhui Zhu, Zhiwei Ni, Pingfan Xia, Liping Ni

“…It is hard to look for the exact result via the searching of intelligent algorithms or pruning of diversity measures. On the basis, we propose a hybrid ensemble pruning approach employing coevolution binary glowworm swarm optimization and reduce-error (HEPCBR). …”
Get full text

Altered actin centripetal retrograde flow in physically restricted immunological synapses. by Cheng-han Yu, Hung-jen Wu, Yoshihisa Kaizuka, Ronald D Vale, Jay T Groves

“…Flow-based particle tracking algorithms allow us to investigate the velocity distribution of actin flow field across the whole synapse, and centripetal velocity of actin flow decreases as it moves toward the center of synapse. …”
Get full text

APPLICATON OF MICROSEISMIC NOISE ESTIMATION IN OIL AND GAS EXPLORATION AIMED AT REDUCING ENVIRONMENTAL IMPACT by A. Yu. Tsivadze, Yu. V. Sirotinskiy, M. A. Abaturov

“…When implementing the MNE algorithms, Chebyshev spectroscopy and analysis of the noise in terms of Gaussian distribution were used.Results. …”
Get full text

Autonomous Drone-Based Pollination Systems for Enhancing Crop Yield in Orchards Using IoT and Machine Learning Optimization by Khan Roohee, Lalnunthari Banti

“…Pollination strategies are enhanced by all PSO algorithms which optimize of the flight path and operational parameters. …”
Get full text

SwinVNETR: Swin V-net Transformer with non-local block for volumetric MRI Brain Tumor Segmentation by Maria Nancy A, K. Sathyarajasekaran

“…The Dice similarity coefficients for the enhanced tumour (ET), whole tumour (WT), and tumour core (TC) are 0.84, 0.91, and 0.87, respectively. …”
Get full text

Local differential privacy-based frequent sequence mining by Teng Wang, Zhi Hu

“…PrivFSM∗ maximizes the utilization of users’ data by applying the whole data on every iteration with a complete privacy budget. …”
Get full text

GAINSeq: glaucoma pre-symptomatic detection using machine learning models driven by next-generation sequencing data by Muhammad Iqbal, Arshad Iqbal, Humaira Ayub, Maqbool Khan, Naveed Ahmad, Yasir Javed, Mohammed Ali Alshara

“…These algorithms demonstrated outstanding accuracy and resilience. …”
Get full text

Blind deconvolution estimation by multi-exponential models and alternated least squares approximations: Free-form and sparse approach. by Daniel U Campos-Delgado, Omar Gutierrez-Navarro, Ricardo Salinas-Martinez, Elvis Duran, Aldo R Mejia-Rodriguez, Miguel J Velazquez-Duran, Javier A Jo

“…In this work, two BDE algorithms are introduced based on linear combinations of multi-exponential functions to model each FluoIR in the sample. …”
Get full text

Oligogenic analysis across broad phenotypes of 46,XY differences in sex development associated with NR5A1/SF-1 variants: findings from the international SF1next studyResearch in co... by Chrysanthi Kouri, Idoia Martinez de Lapiscina, Rawda Naamneh-Elzenaty, Grit Sommer, Kay-Sara Sauter, Christa E. Flück, Saygin Abali, Zehra Yavas Abali, S. Faisal Ahmed, Leyla Akin, Maricruz Almaraz, Laura Audí, Murat Aydin, Antonio Balsamo, Federico Baronio, Jillian Bryce, Kanetee Busiah, Maria Caimari, Núria Camats-Tarruella, Ariadna Campos-Martorell, Luis Castaño, Anna Casteràs, Semra Çetinkaya, Hedi L. Claahsen - van der Grinten, Martine Cools, Ines Costa, Fatma Feyza Darendeliler, Justin H. Davies, Isabel Esteva, Helena Fabbri-Scallet, Courtney A. Finlayson, Emilio Garcia, Beatriz Garcia- Cuartero, Alina German, Evgenia Globa, Gil Guerra-Junior, Julio Guerrero, Tulay Guran, Sabine E. Hannema, Olaf Hiort, Josephine Hirsch, Ieuan Hughes, Marco Janner, Uchenna Kennedy, Zofia Kolesinska, Katherine Lachlan, Anna Lauber-Biason, Jana Krenek Malikova, Dagmar L’Allemand, Nina Lenhnerr-Taube, Angela Lucas-Herald, Jamala Mammadova, Veronica Mericq, Isabel Mönig, Francisca Moreno, Julia Mührer, Marek Niedziela, Anna Nordenstrom, Burçe Orman, Sukran Poyrazoglu, Jose M. Rial, Meilan M. Rutter, Amaia Rodríguez, Tara Schafer-Kalkhoff, Sumudu Nimali Seneviratne, Maria Sredkova-Ruskova, LIoyd J.W. Tack, Rieko Tadokoro-Cuccaro, Ajay Thankamony, Mónica Tomé, Amaia Vela, Malgorzata Wasniewska, David Zangen, Nataliya Zelinska

“…WES data were analysed using a tailored filtering algorithm designed to identify rare variants in DSD and SF-1-related genes. …”
Get full text

Intelligent Machine Vision Based Modeling and Positioning System in Sand Casting Process by Shahid Ikramullah Butt, Umer Asgher, Umar Mushtaq, Riaz Ahmed, Faping Zhang, Yasar Ayaz, Mohsin Jamil, Muhammad Kamal Amjad

“…The coordinates of the center of pouring cup are found by using computer vision algorithms. The output is then transferred to a microcontroller which controls the alignment mechanism on which the mold is placed at the optimum location.…”
Get full text

AUTOMATED BIM ENTITY RECONSTRUCTION FROM UNSTRUCTURED 3D POINTCLOUDS by Jan Voříšek, Bořek Patzák, Edita Dvořáková, Daniel Rypl

“…Typically, engineers manually obtain floor plans, structural models, or the whole BIM model, which is a very time-consuming task for large building projects. …”
Get full text

Perceptual objective evaluation for multimodal medical image fusion by Chuangeng Tian, Juyuan Zhang, Lu Tang

“…Due to the lack of dataset for the objective evaluation task, we collect 129 pairs of source images from public datasets, namely, the Whole Brain Atlas, and construct a MMIF quality database containing 1,290 medical fused images generated using MMIF algorithms. …”
Get full text

A Review of Reinforcement Learning for Fixed-Wing Aircraft Control Tasks by David J. Richter, Ricardo A. Calix, Kyungbaek Kim

“…A lot of that can be attributed to the recent advancements in machine learning (ML) and deep learning (DL) as a whole, the power of deep neural networks and the incorporation of them into reinforcement learning algorithms and techniques. …”
Get full text

Integrating Model‐Informed Drug Development With AI: A Synergistic Approach to Accelerating Pharmaceutical Innovation by Karthik Raman, Rukmini Kumar, Cynthia J. Musante, Subha Madhavan

“…Artificial intelligence (AI), encompassing techniques such as machine learning, deep learning, and Generative AI, offers powerful tools and algorithms to efficiently identify meaningful patterns, correlations, and drug–target interactions from big data, enabling more accurate predictions and novel hypothesis generation. …”
Get full text

GCBRGCN: Integration of ceRNA and RGCN to Identify Gastric Cancer Biomarkers by Peng Zhi, Yue Liu, Chenghui Zhao, Kunlun He

“…It demonstrates exceptional performance, surpassing traditional machine learning and graph neural network algorithms with an area under the curve (AUC) of 0.8172 in the task of predicting GC biomarkers. …”
Get full text

Platform Employment — the Scale and Evidence of Instability by V. N. Bobkov, E. A. Chernykh

“…Platforms are digital (virtual) technological devices-software, algorithms, control systems using artificial intelligence and other digital means of labour. …”
Get full text

ABOUT COMPLEX APPROACH TO MODELLING OF TECHNOLOGICAL MACHINES FUNCTIONING by A. A. Honcharov

“…These problems concern not only properties of some types of equipment but they have respect to regularities of control object functioning as a whole. A technological machine is thought of as such technological complex where it is possible to lay emphasis on a control system (or controlling device) and a controlled object. …”
Get full text

Applying deep learning to teleseismic phase detection and picking: PcP and PKiKP cases by Congcong Yuan, Jie Zhang

“…Recently, deep learning algorithms exhibit a powerful capability of detecting and picking on P- and S-wave phases. …”
Get full text

Rediscovering histology – the application of artificial intelligence in inflammatory bowel disease histologic assessment by Giovanni Santacroce, Irene Zammarchi, Olga Maria Nardone, Ivan Capobianco, Miguel Puga-Tejada, Snehali Majumder, Subrata Ghosh, Marietta Iacucci

“…By leveraging advanced algorithms, AI enhances diagnostic accuracy, reduces assessment variability and streamlines histological workflows in clinical settings. …”
Get full text

Averaging gate approximation error and performance of Unitary Coupled Cluster ansatz in Pre-FTQC Era by Kohdai Kuroiwa, Yuya O. Nakagawa

“…Fault-tolerant quantum computation (FTQC) is essential to implement quantum algorithms in a noise-resilient way, and thus to enjoy advantages of quantum computers even with presence of noise. …”
Get full text