Process parameter optimization of laser beam machining for AISI -P20 mold steel using ANFIS method by Abdullah Eaysin, Sarower Kabir, Ebru Gunister, Nur Jahan, Amir Hamza, Muhammad Ali Zinnah, Adib Bin Rashid

“…The ANFIS model, developed and analyzed using MATLAB, successfully predicted response parameters and was experimentally validated, showing improved predictions over actual measurements. …”
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Clinical Utility of HeartLogic, a Multiparametric Telemonitoring System, in Heart Failure by Juan Carlos López-Azor, Noelia de la Torre, María Dolores García-Cosío Carmena, Pedro Caravaca Pérez, Catalina Munera, Irene Marco Clement, Rocío Cózar León, Jesús Álvarez-García, Marta Pachón, Fernando Arribas Ynsaurriaga, Rafael Salguero Bodes, Juan Francisco Delgado Jiménez, Javier de Juan Bagudá

“…Telemonitoring through multiple variables measured on cardiac devices has the potential to improve the follow-up of patients with heart failure. The HeartLogic algorithm (Boston Scientific), implemented in some implantable cardiac defibrillators and cardiac resynchronisation therapy, allows monitoring of the nocturnal heart rate, respiratory movements, thoracic impedance, physical activity and the intensity of heart tones, with the aim of predicting major clinical events. …”
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Nanosatellite Autonomous Navigation via Extreme Learning Machine Using Magnetometer Measurements by Gilberto Goracci, Fabio Curti, Mark Anthony de Guzman

“…The SLFN is trained using GPS data when available and predicts the state correction to be applied to the EKF estimates. …”
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An Analytical Solution for the Hydraulics of Looped Pipe Networks by Mohammad Mehdi Riyahi, Amin E. Bakhshipour, Carlo Giudicianni, Ulrich Dittmer, Ali Haghighi, Enrico Creaco

“…Finally, a Z-test hypothesis test is applied to assess the efficacy of the modified shortest-path algorithm. The results show that this algorithm attains an average accuracy of 90% in predicting exact flow directions, with a confidence level of 99%.…”
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Real-Time Acoustic Measurement System for Cutting-Tool Analysis During Stainless Steel Machining by Tom Salm, Kourosh Tatar, José Chilo

“…Using the TreeBagger machine-learning algorithm, the system accurately predicts tool wear, detecting both gradual and abrupt wear patterns. …”
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Supervised Clustering of Persian Handwritten Images by Sajedeh Moradnia, Mousa Golalizadeh

“…Focusing on the multi-class nature of Persian handwritten data, the identification of important variables for each digit not only reduces data dimensionality but also this reduction in dimensionality does not compromise the accuracy of predicting new observations at any stage of the algorithm. …”
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A Statistical Framework for Modeling Behavioral Engagement via Topic and Psycholinguistic Features: Evidence from High-Dimensional Text Data by Dan Li, Yi Zhang

“…This study investigates how topic-specific expression by women delivery riders on digital platforms predicts their community engagement, emphasizing the mediating role of self-disclosure and the moderating influence of cognitive and emotional language features. …”
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Where the wild bees are: Birds improve indicators of bee richness. by Josée S Rousseau, Alison Johnston, Amanda D Rodewald

“…We used a Bayesian variable selection algorithm to select variables that best predicted species richness of bees using two datasets: a semi-structured dataset covering a wide geographical and temporal range and a structured dataset covering a focused extent with a standardized protocol. …”
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User Random Access Technology Based on Beam Hopping Satellite Communication System by Zixuan HUANG, Jiaxi ZHOU, Jing ZHANG, Zhengyu ZHANG

“…On the basis of geosynchronous earth orbit multi-beam satellite communication systems, this paper designed the process of user random access to the network and specifi c signaling interaction under the agile beam mechanism, and proposed the scheduling strategy and allocation scheme of the agile signaling beam.This scheme increased the fl exibility of access resource allocation under the premised of ensured that all users could accessed the network, eff ectively improved the utilization rate of satellite network resources.The request of user access to the satellite communication network belongs to the burst type, it is more suitable to use the random competition access, so this paper based on the general random competition access strategy, proposed an adaptive random competition access algorithm based on the heat value, based on the heat value predicted by the network side, the user selects diff erent random access strategies for access.Through the simulation and analysis of the optimization algorithm, it is proved that the algorithm could eff ectively reduced the probability of access collision under various network loads, so as to achieved the purpose of users quickly accessing the network.…”
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Assessing the Effectiveness of DL-Clustering for Energy Optimization in Wireless Sensor Networks by Shailaja S. Halli, Poornima G Patil

“…Mobile sinks and neighboring nodes are alerted if the fitness is low, which also predicts energy efficient traffic and creates an implicit alarm threshold. …”
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GEOGRAPHICALLY WEIGHTED MACHINE LEARNING MODEL FOR ADDRESSING SPATIAL HETEROGENEITY OF PUBLIC HEALTH DEVELOPMENT INDEX IN JAVA ISLAND by Muhammad Azis Suprayogi, Bagus Sartono, Khairil Anwar Notodiputro

“…Random Forest (RF) machine learning models have emerged as a prominent algorithm, addressing problems arising from the sole use of decision trees, such as overfitting and instability. …”
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Ensemble deep learning-enabled single-shot composite structured illumination microscopy (eDL-cSIM) by Jiaming Qian, Chunyao Wang, Hongjun Wu, Qian Chen, Chao Zuo

“…Experimental results demonstrate that eDL-cSIM integrates the advantages of various state-of-the-art neural networks, enabling robust super-resolution image predictions across different specimen types or structures of interest, and outperforms classical physics-driven methods in terms of imaging speed, reconstruction quality and environmental robustness, while avoiding intricate and specialized algorithmic procedures. …”
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A deep machine learning model development for the biomarkers of the anatomical and functional anti-VEGF therapy outcome detection on retinal OCT images by B.E. Malyugin, S.N. Sakhnov, L.E. Axenova, K.D. Axenov, E.V. Kozina, V.V. Vronskaya, V.V. Myasnikova

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A multi-model approach for distance and angle estimation using a custom-designed tag by Emre Erkan

“…In the second stage, the data obtained is analyzed through a MLP to predict distances and angular values. The performance of the proposed algorithm has been evaluated through experiments simulating real-world applications, yielding reliable results. …”
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Application of Artificial Intelligence in Tinnitus Diagnosis and Treatment: A Pilot Study by Yu Wang, Kaixiang Pan, Richard Tyler, Zhaoyi Lu, Shan Xiong, Yufei Xie, Tao Pan

“…We describe the curation of the input data, the algorithm (CTGan) used to extend the dataset, and the ML model (Random Forest) to predict each of the suggested treatments. …”
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A Recommendation System Based on Regression Model of Three-Tier Network Architecture by Wang Bailing, Huang Junheng, Zhu Dongjie, Hou Xilu

“…The correlation score is used to predict the test user preference for the test item. …”
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Learning Quantum Processes with Quantum Statistical Queries by Chirag Wadhwa, Mina Doosti

“…For the former, we present an efficient average-case algorithm along with a nearly matching lower bound with respect to the number of observables to be predicted. …”
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BLSTM based night-time wildfire detection from video. by Ahmet K Agirman, Kasim Tasdemir

“…Moreover, to pave the way for more targeted solutions to this challenging problem, experiment-based thorough investigations of possible sources of incorrect predictions and discussion of the unique nature of night-time wildfire videos are presented in the paper.…”
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Determination of the location of sonic boom by Rufin MAKAREWICZ

“…For general case (at arbitrary manoeuvring of aircraft) a procedure algorithm has been defined which permits to predict the boundary of audibility area. …”
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Control Theory and Bayesian Networks for Black Spots Study by Leonardo Flores, Jorge Vargas, Alan Ayala, Jeremy Ramos, Edwin Salas

“…To measure the performance and recovery of an urban road network, it is necessary to identify and predict the locations on the network where they occur. …”
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