Adaptive Refinement of Segmented Object Contour Based on the Brightness of Neighboring Pixels Using the Ensemble Method by Vladyslav D. Koniukhov

“…Improving the accuracy of computer vision algorithms plays a significant role in the tasks of medical image segmentation. …”

Detection of Alzheimer and mild cognitive impairment patients by Poincare and Entropy methods based on electroencephalography signals by Umut Aslan, Mehmet Feyzi Akşahin

“…Because there is no treatment for AD, early prediction of AD can be helpful to reducing the progression of this disease. …”
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GLOBAL TRENDS ON RESEARCH TOWARDS THE VALUATION PROCESS OF AN AGRICULTURE LAND by Silvia CHIOREAN, Iulia COROIAN, Tudor SĂLĂGEAN, Mircea Emil NAP, Jutka DEAK, Ioan LUPUȚ

“…The increased use of data analytics and machine learning algorithms enables better prediction of land values based on various factors such as soil quality, climate, and historical performance by processing large datasets. …”
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Diabetes Mellitus Detection System In Human Body Through Urine Media Using Naïve Bayes Method by Yuda Kasmien Adha, Tati Erlina

“…The system is made using the NaÏve Bayes algorithm to be able to classify urine that has been tested Benedict including into non-diabetes or diabetes, the system is also made using multiple linear regression algorithms to be able to predict the sugar content contained in urine. …”
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Influence of the media used in the operation of aircraft on the durability of airport cement surfaces by Piotr Nita, Małgorzata Linek

“…In terms of mass, dynamic and temperature interactions, these are measurable phenomena that can be determined and predicted using appropriate methods and algorithms. …”
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The constrained-disorder principle defines the functions of systems in nature by Yaron Ilan

“…The paper reviews variability-based CDP algorithms and CDP-based second-generation artificial intelligence systems and their potential for improving systems’ prediction and efficiency by using variability.…”
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Stellar ejection velocities from the binary supernova scenario: A comparison across population synthesis codes by Tom Wagg, David D. Hendriks, Mathieu Renzo, Katelyn Breivik

“…We present a comparison of the predicted ejection velocities of disrupted binary companions in three different population synthesis codes: COSMIC, COMPAS, and binary_c, which use two independent algorithms for the treatment of natal kicks. …”
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DeepBase: A Deep Learning-based Daily Baseflow Dataset across the United States by Parnian Ghaneei, Hamid Moradkhani

“…This study focuses on estimating baseflow using deep learning algorithms that enhance the estimation capabilities in both gauged and ungauged basins. …”
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Reinforcement Learning Applications in Cyber Security: A Review by Murat Gök, Emine Cengiz

“…Traditional computer algorithms may be insufficient against these attacks in the virtual world. …”
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Global decline in net primary production underestimated by climate models by Thomas J. Ryan-Keogh, Alessandro Tagliabue, Sandy J. Thomalla

“…Here we use contemporary remote sensing net primary production trends (1998–2023) from six remote sensing algorithms to discriminate amongst fifteen divergent model projections. …”
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Application of Improved WOA in Hammerstein Parameter Resolution Problems under Advanced Mathematical Theory by Lu Zhao, Jiangjun Liu, Yuan Li

“…In identifying Hammerstein model under heavy-tailed noise, the average prediction recognition accuracy of the improved whale algorithm was 92.38%, the determination coefficient was 0.89, the percentage fitting error was 0.03, and the system error was 0.02. …”
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Bistability and oscillations in the Huang-Ferrell model of MAPK signaling. by Liang Qiao, Robert B Nachbar, Ioannis G Kevrekidis, Stanislav Y Shvartsman

“…As a result, these models try to predict the dynamics of systems with tens or even hundreds of free parameters. …”
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Pharmacotherapeutic Options for Ophthalmic Conjunctivitis by A. D. van Eyk

“…There is however a challenge in distinguishing between the various types of conjunctivitis due to the similarity in the symptoms and due to a lack of tests and prediction algorithms, thus antibiotic therapy is often incorrectly initiated. …”
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Integrative multi-omics module network inference with Lemon-Tree. by Eric Bonnet, Laurence Calzone, Tom Michoel

“…Novel candidate driver genes predicted by Lemon-Tree were validated using tumor pathway and survival analyses. …”
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Target Tracking Using a Time-Varying Autoregressive Dynamic Model by Ralph J. Mcdougall, Simon J. Godsill

“…Target tracking algorithms commonly use structured dynamic models which require prior training of fixed model parameters. …”
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Behavioral discrimination and time-series phenotyping of birdsong performance. by Avishek Paul, Helen McLendon, Veronica Rally, Jon T Sakata, Sarah C Woolley

“…Moreover, the algorithm accurately predicted female performance on individual motif exemplars. …”
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Organization of physical interactomes as uncovered by network schemas. by Eric Banks, Elena Nabieva, Bernard Chazelle, Mona Singh

“…Network schemas specify descriptions of proteins and the topology of interactions among them. We develop algorithms for systematically uncovering recurring, over-represented schemas in physical interaction networks. …”
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A conditional opposition-based particle swarm optimisation for feature selection by Jingwei Too, Ali Safaa Sadiq, Seyed Mohammad Mirjalili

“…Hence, feature selection is a necessary pre-processing stage to select the important features that may considerably increase the efficiency of underlying classification algorithms. As a popular metaheuristic algorithm, particle swarm optimisation has successfully applied to various feature selection approaches. …”
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Propensity to childhood anxiety and depression due to exposure to adversity: A multidimensional construct. by Angélica C G Santos, Ariane Silva, Matheus Libório, Cristiane Neri Nobre, Hasheem Mannan, Marcos Flávio S V D'Angelo

“…The literature does not present a consensus on the composition of indicators that make predictions, prognostic algorithms, or management strategies in mental health promotion and prevention. …”
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A Review on Machine Learning Models in Injection Molding Machines by Senthil Kumaran Selvaraj, Aditya Raj, R. Rishikesh Mahadevan, Utkarsh Chadha, Velmurugan Paramasivam

“…Neural networks have considerable applications in the injection molding process consisting of optimization, prediction, identification, classification, controlling, modeling, and monitoring, particularly in manufacturing. …”
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