3D evolutionarily designed metamaterials for scattering maximization by Dmitry Dobrykh, Konstantin Grotov, Anna Mikhailovskaya, Dmytro Vovchuk, Vladyslav Tkach, Mykola Khobzei, Anton Kharchevskii, Aviel Glam, Pavel Ginzburg

“…Abstract The rapid growth in drone air traffic calls for enhanced radar surveillance systems to ensure reliable detection in challenging conditions. Increasing radar scattering cross-section can greatly improve detection reliability in civilian applications. …”
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Research and Implementation of Travel Aids for Blind and Visually Impaired People by Jun Xu, Shilong Xu, Mingyu Ma, Jing Ma, Chuanlong Li

“…To address embedded device computational constraints, we developed a lightweight object detection and segmentation algorithm. Key innovations include a multi-scale attention feature extraction backbone, a dual-stream fusion module incorporating the Mamba architecture, and adaptive context-aware detection/segmentation heads. …”
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MoNetViT: an efficient fusion of CNN and transformer technologies for visual navigation assistance with multi query attention by Liliek Triyono, Liliek Triyono, Rahmat Gernowo, Prayitno

“…Experiments show MoNetViT outperforms other semantic segmentation algorithms in efficiency and effectiveness, particularly in detecting Aruco markers, making it a promising tool to improve navigation aids for the visually impaired.…”
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Phaseless Diagnosis and Pattern Correction of Faulty Antenna Arrays via Advanced Bayesian Compressive Sensing Approaches by Zi An Wang, Ping Li

“…This method features a modified forward projection rule to accelerate convergence and utilizes a BCS algorithm during backward projection to find sparse correction vectors. …”
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Intelligent Perception and Seam Tracking System for Thick Plate Weldments Based on Constant-Focus Optical Path by Lei Zhai, Wenze Ren, Fei Li, Rong Wu, Jinsong Lin, Jiahui Feng, Jun Zheng, Yang Liu

“…Furthermore, a sophisticated feature point extraction algorithm, which integrates a maximum distance search strategy with a least-squares fitting procedure, was developed to facilitate the precise and timely identification of weld seam characteristic points. …”
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Dual-verified secure localization method for unmanned intelligent vehicles by GU Xiaodan, XIA Guozheng, SONG Bingchen, YANG Ming, LUO Junzhou

“…Once an abnormal position was detected, an alert would be issued, ensuring the normal operation of the unmanned intelligent vehicles. …”
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EEG-Based Emotion Recognition Using Deep Learning Network with Principal Component Based Covariate Shift Adaptation by Suwicha Jirayucharoensak, Setha Pan-Ngum, Pasin Israsena

“…Automatic emotion recognition is one of the most challenging tasks. To detect emotion from nonstationary EEG signals, a sophisticated learning algorithm that can represent high-level abstraction is required. …”
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A single-camera gaze tracking system under natural light by Feng Xiao, Dandan Zheng, Kejie Huang, Yue Qiu, Haibin Shen

“…However, constrained by the performance of the specific sensors and algorithms, it has not been popularized for everyone. …”
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A validated heart-specific model for splice-disrupting variants in childhood heart disease by Robert Lesurf, Jeroen Breckpot, Jade Bouwmeester, Nour Hanafi, Anjali Jain, Yijing Liang, Tanya Papaz, Jane Lougheed, Tapas Mondal, Mahmoud Alsalehi, Luis Altamirano-Diaz, Erwin Oechslin, Enrique Audain, Gregor Dombrowsky, Alex V. Postma, Odilia I. Woudstra, Berto J. Bouma, Marc-Phillip Hitz, Connie R. Bezzina, Gillian M. Blue, David S. Winlaw, Seema Mital

“…Recent computational algorithms such as SpliceAI have shown an ability to predict such variants, but are not specific to cardiac-expressed genes and transcriptional isoforms. …”
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An upgraded high-precision gridded precipitation dataset for the Chinese mainland considering spatial autocorrelation and covariates by J. Hu, C. Miao, J. Su, Q. Zhang, J. Gou, J. Gou, Q. Sun, Q. Sun

“…Regarding precipitation event detection, CHM_PRE V2 achieved a Heidke skill score of 0.68 and a false alarm ratio of 0.24, surpassing the previously optimal dataset by 17.24 % and 29.17 %, respectively. …”
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Empirical Analysis of Honeybees Acoustics as Biosensors Signals for Swarm Prediction in Beehives by Kainat Iqbal, Bayan Alabdullah, Naif Al Mudawi, Asaad Algarni, Ahmad Jalal, Jeongmin Park

“…Swarm prediction can be done by visually inspecting hives, monitoring temperature, or analyzing acoustic features with machine learning. Acoustic monitoring is instrumental in detecting changes in colony behavior since it overcomes the constraints of visual inspections and is not affected by external factors like temperature. …”
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Methionine synthase reductase A66G polymorphism and ischemic stroke in younger patients by O. V. Tsyganenko, L. I. Volkova, A. M. Alasheev

“…Methionine synthase reductase (MTRR) A66G polymorphism is one of the risk factors for ischemic stroke (IS). However, clinical features of IS in MTRR A66G polymorphism are not yet studied.Objective: to investigate clinical features of IS in MTRR A66G polymorphism.Patients and methods. …”
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Astronomaly Protege: Discovery through Human-machine Collaboration by Michelle Lochner, Lawrence Rudnick

“…By operating in this feature space, PROTEGE is able to recommend interesting sources with completely different morphologies in image space to those it has been trained on. …”
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Ship Contour: A Novel Ship Instance Segmentation Method Using Deep Snake and Attention Mechanism by Chen Chen, Songtao Hu, Feng Ma, Jie Sun, Tao Lu, Bing Wu

“…To address this issue, this paper introduces Ship Contour, a real-time segmentation method for ship instances based on contours that detects ship targets using an improved CenterNet algorithm. …”
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External phantom-based validation of a deep-learning network trained for upscaling of digital low count PET data by Anja Braune, René Hosch, David Kersting, Juliane Müller, Frank Hofheinz, Ken Herrmann, Felix Nensa, Jörg Kotzerke, Robert Seifert

“…The performance of this algorithm has so far only been clinically evaluated on patient data featuring limited scan statistics and unknown actual activity concentration. …”
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Artificial Intelligence in Healthcare: Innovation and Impact in Medical Practice by Amelia-Maria ISAC, Corina VERNIC

“…Data were extracted from two key studies published between 2016 and 2021: (1) “Development and Validation of a Deep Learning Algorithm for Detection of Diabetic Retinopathy in Retinal Fundus Photographs” (Gulshan et al., 2016) and (2) “Deep Learning for Alzheimer’s Disease: A Systematic Review” (Wang et al., 2021). …”
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Predicting police and military violence: evidence from Colombia and Mexico using machine learning models by Juan David Gelvez

“…Such misconduct is not random, making its prevention both crucial and challenging due to the difficulty of measuring and detecting these phenomena beforehand. Recent advances in artificial intelligence offer new tools for this task. …”
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Identification of Elephant Rumbles in Seismic Infrasonic Signals Using Spectrogram-Based Machine Learning by Janitha Vidunath, Chamath Shamal, Ravindu Hiroshan, Udani Gamlath, Chamira U. S. Edussooriya, Sudath R. Munasinghe

“…It is experimentally found that the combination of the Mel-frequency cepstral coefficient (MFCC) feature extraction method and the ridge classifier machine learning algorithm give the highest accuracy of 97% in detecting infrasonic elephant rumbles hidden in seismic signals. …”
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High-Resolution Computed Tomography of Single Breast Cancer Microcalcifications in Vivo by Kazumasa Inoue, Fangbing Liu, Jack Hoppin, Elaine P. Lunsford, Christian Lackas, Jacob Hesterman, Robert E. Lenkinski, Hirofumi Fujii, John V. Frangioni

“…Two ray-tracing image reconstruction algorithms were tested: a voxel-driven “fast” cone beam algorithm (FCBA) and a detector-driven “exact” cone beam algorithm (ECBA). …”
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Color and Grey-Level Co-Occurrence Matrix Analysis for Predicting Sensory and Biochemical Traits in Sweet Potato and Potato by Judith Ssali Nantongo, Edwin Serunkuma, Gabriela Burgos, Mariam Nakitto, Joseph Kitalikyawe, Thiago Mendes, Fabrice Davrieux, Reuben Ssali

“…High correlations between sensory panel aroma and flavor with instrumental color were detected (up to r=0.66), although the validity of these correlations needs to be tested. …”
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