Hybrid Mode Sensor Fusion for Accurate Robot Positioning by Viktor Masalskyi, Andrius Dzedzickis, Igor Korobiichuk, Vytautas Bučinskas

“…Robotic systems are becoming increasingly crucial in applications requiring high precision. While a robot can operate using basic sensor feedback under controlled conditions, achieving micro-level accuracy requires more comprehensive data integration, especially in dynamic environments. …”
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Meta-Learning-Based Prediction of Different Corn Cultivars from Color Feature Extraction by Abdullah Beyaz, Dilara Gerdan

“…All algorithms were run with a 10-fold cross-validation method. …”
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Performance Comparison of Support Vector Machine (SVM) and k-Nearest Neighbors (kNN) in Verifying Material Orientation by Eldio Utama, Eko Rudiawan Jamzuri

“…This study compares the performance of Support Vector Machine (SVM) and k-Nearest Neighbors algorithms for verifying material orientation verification through automated optical inspection. …”
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Easy to Snack—Hard to Digest? Strategies of Dis/Array in Streaming, Social Media, and Television by Kim Carina Hebben, Christine Piepiorka

“…Conversely, array represents the efforts by platforms and users to restore order through algorithms, categorization, and interactive engagement. …”
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Efficient identification of maximum independent sets in stochastic multilayer graphs with learning automata by Mohammad Mehdi Daliri Khomami, Mohammad Reza Meybodi, Alireza Rezvanian

“…In this paper, we introduce the stochastic version of the maximum independent set and propose five algorithms based on learning automata to identify maximum independent sets in the stochastic multilayer graphs. …”
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Sentiment Analysis on the Relocation of the National Capital (IKN) on Social Media X Using Naive Bayes and K-Nearest Neighbor (KNN) Methods by Nova Wulandari, Yana Cahyana, Rahmat Rahmat, Hanny Hikmayanti

“…The algorithms' performance was assessed using accuracy, precision, recall, and F1-score metrics. …”
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Synchronization method for long-term evolution-based machine-type communication in low-power cellular Internet of Things by Rothna Pec, Joo-Hyung Choi, Chang-Hwan Park, Yong Soo Cho

“…Through simulation under long-term evolution-based machine-type communication environments, we show that the proposed methods for primary synchronization signal and secondary synchronization signal detection require six and five times less computational complexity than the conventional methods, respectively, while their performance is similar. The proposed algorithms allow machine-type communication devices in a discontinuous reception cycle to resynchronize quickly with less power when synchronization is lost during a deep sleep period.…”
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Estimating Tree Diameter at Breast Height (DBH) Using iPad Pro LiDAR Sensor in Boreal Forests by Matthew Guenther, Muditha K. Heenkenda, Brigitte Leblon, Dave Morris, Jason Freeburn

“…Two circle fitting algorithms (Pratt, Taubin) and two ellipse fitting algorithms (Taubin, Szpak) were applied to the extracted cross-sections to estimate DBH. …”
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A Decade in Software-Based Side and Covert Channel Attacks and Countermeasures: A Survey by Teodora Vasilas, Remus Brad

“…As technology continues to evolve, it provides significant benefits, such as seamless access to information, while also introducing critical security challenges, including privacy vulnerabilities and the rapid spread of misinformation. …”
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Drunk Driver Detection Using Thermal Facial Images by Chin-Heng Chai, Siti Fatimah Abdul Razak, Sumendra Yogarayan, Ramesh Shanmugam

“…Convolutional Neural Networks (CNNs) and YOLO (You Only Look Once) algorithms were employed to extract facial features, while classifiers such as Support Vector Machines (SVMs), Multi-Layer Perceptron (MLP), and K-Nearest Neighbors (KNN), as well as Random Forest and linear regression, classify individuals as sober or intoxicated based on their thermal images. …”
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Blending Ensemble Learning Model for 12-Lead Electrocardiogram-Based Arrhythmia Classification by Hai-Long Nguyen, Van Su Pham, Hai-Chau Le

“…The framework employs a predetermined meta-model from foundation models, while the remaining models serve as potential base estimators, ranked by accuracy. …”
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Untouched minds in a tangled web: navigating mental autonomy and epistemic welfare amidst digital propaganda by Emine Ozge Yildirim-Vranckaert, Aaron Hyzen

“…We begin by defining propaganda and discussing its potential to inflict harm through the transformational forces of datafication, algorithmization, and plaformization. A historical review of legal approaches to propaganda reveals critical gaps in existing frameworks, which continue to rely on outdated perceptions of autonomy that assume the mind is largely immune to external influences. …”
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Integrating Digital Twin and BIM for Special-Length-Based Rebar Layout Optimization in Reinforced Concrete Construction by Daniel Darma Widjaja, Jeeyoung Lim, Sunkuk Kim

“…The system employs heuristic algorithms to generate constructability-aware rebar configurations and leverages Industry Foundation Classes (IFC) schema-based data models for interoperability. …”
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Inertial Subrange Optimization in Eddy Dissipation Rate Estimation and Aircraft-Dependent Bumpiness Estimation by Zhenxing Gao, Qilin Zhang, Kai Qi

“…In current vertical wind-based eddy dissipation rate (EDR) estimation algorithms based on flight data, the inertial subrange is determined empirically. …”
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Optimization of High-Performance Computing Job Scheduling Based on Offline Reinforcement Learning by Shihao Li, Wei Dai, Yongyan Chen, Bo Liang

“…Experimental results demonstrate that, compared to heuristic and online DRL algorithms, the proposed approach achieves more efficient scheduling performance across various workloads and optimization goals, showcasing its practicality and broad applicability.…”
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Ultra-High Spatial Resolution Clinical Positron Emission Tomography (PET) Systems by Myungheon Chin, Muhammad Nasir Ullah, Derek Innes, Craig S. Levin

“…A key strategy involves organ-specific, or loco-regional, scanner configurations that optimize photon detection efficiency (PDE) while balancing the trade-off between spatial resolution and image signal-to-noise ratio (SNR). …”
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Investigation on Beamspace Multiple-Input Multiple-Output Synthetic Aperture Radar Data Imaging by Hongbo Mo, Wei Xu, Zhimin Zeng

“…Afterwards, the resulting MIMO-SAR raw data could be equivalent to the raw data of the single-channel burst mode, and classical burst mode imaging algorithms could be adopted to obtain final focused SAR images. …”
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STUDY OF ROBUST TOA DISCRIMINATORS FOR SPACE-BASED RADAR ALTIMETER by D. S. Borovitsky, A. E. Zhesterev, V. P. Ipatov, R. M. Mamchur

“…In the  robust  algorithms TOA-measuring  is performed without  using  any  echo  physical  model.  …”
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Industrial-scale prediction of cement clinker phases using machine learning by Sheikh Junaid Fayaz, Néstor Montiel-Bohórquez, Shashank Bishnoi, Matteo Romano, Manuele Gatti, N. M. Anoop Krishnan

“…Through post hoc explainable algorithms, we interpret the hierarchical relationships between clinker oxides and phase formation, providing insights into the functioning of an otherwise black-box model. …”
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Ecotoxicity prediction of chemical compounds using machine learning and different molecular structure representations by Michał Marek, Rafał Kurczab

“…Advancements in computational tools have facilitated interdisciplinary approaches in toxicology, enabling chemists to explore the toxicity and ecotoxicity of chemical compounds while minimizing ethically questionable or hazardous methods. …”
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