Prediction and early prevention of violence in children and adolescents by Ф. Сафуанов, А. Құдайбергенова, Э. Калымбетова, А. Урисбаева, А. Сулейменова

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Engaging Essential Patient Support Personnel in Research as Patient Partners: A Survey Study by Skubisz C, DeRosa S, Pacanowski CR

Subjects: “…Integrated Model of Behavioral Prediction…”
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Vehicle Routing Simulation for Prediction of Commuter’s Behaviour by Przemysław Szufel, Bartosz Pankratz, Anna Szczurek, Bogumił Kamiński, Paweł Prałat

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Fractional Gaussian Noise: Projections, Prediction, Norms by Iryna Bodnarchuk, Yuliya Mishura, Kostiantyn Ralchenko

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Can Informativity Effects Be Predictability Effects in Disguise? by Vsevolod Kapatsinski

“…This paper shows how to estimate the proportion of an observed informativity effect that is likely to be artifactual, due entirely to informativity improving the estimates of predictability, via simulation. The proposed simulation approach can be used to investigate whether an effect of informativity is likely to be real, under the assumption that corpus probabilities are an unbiased estimate of probabilities driving reduction behavior, and how much of it is likely to be due to noise in predictability estimates, in any real dataset.…”
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Habituation in Predictability-Modulations of Stimulus-Response Binding by Philip Schmalbrock, Jan Theeuwes, Christian Frings

“…These effects allow us to measure the strength of this shared representation and the impact it can have on behavior. A well-established finding is that particular variables can modulate the size of binding effects – one recently discovered modulator is stimulus predictability: If perceptual information is perfectly predictable, stimulus-response binding effects diminish. …”
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Behavior Coding of Adolescent and Therapy Dog Interactions During a Social Stress Task by Seana Dowling-Guyer, Katie Dabney, Elizabeth A. R. Robertson, Megan K. Mueller

“…Future research should focus on identifying specific patterns of interactive behaviors between dogs and humans that predict anxiolytic outcomes.…”
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Prevention or Promotion? Predicting Author's Regulatory Focus by Aswathy Velutharambath, Kai Sassenberg, Roman Klinger

“…The concept of regulatory focus is employed in psychology, to explain and predict this goal-directed behavior of humans underpinned by two unique motivational systems – the promotion and the prevention system. …”
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Prediction of cardiorrespiratory fitness by screen time in schoolchildrens by Amanda de Oliveira, Flávio Ricardo Guilherme, Stevan Ricardo dos Santos, Maria Teresa Martins Fávero, Vânia Renata Guilherme, Wilson Rinaldi

“…The time spent in front of the screens, results in accumulations of sedentary behavior, which is related to health damages to adolescents, such as a low cardiorespiratory fitness. …”
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AI-Based Prediction of Warpage in Organic Substrates by Jingyi Zhao, Meiying Su, Rui Ma

“…This study proposes an artificial intelligence (AI)-based method to predict the warpage behavior of organic substrates with diverse material and structural configurations. …”
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Churn prediction for SaaS company with machine learning by Hugo Eduardo Sanches, Ayslan Trevizan Possebom, Linnyer Beatrys Ruiz Aylon

“…Thus, this research aims to develop a model that effectively predicts customer churn for TecnoSpeed and provides insights into customer behavior. …”
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Functional Data Analysis for Prediction of Employee Presence by Nouhaila Goujili, Matthieu Saumard, Nicolas Cochard, Maher Jridi

“…The problem of space occupancy and the prediction of occupancy schedules has rarely been addressed, due to the highly stochastic behavior of occupants and the insufficient quality of data sets. …”
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Role of topological indices in predictive modeling and ranking of drugs treating eye disorders by Nazeran Idrees, Esha Noor, Saima Rashid, Fekadu Tesgera Agama

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Multi-group target tracking method based on adaptive predictive clustering in WSN by Shumu LIU, Jian YANG, Yuansong LI

“…Aiming at the imbalance between energy using and tracking accuracy in multi-sensor target tracking,a method of trade-off network lifetime and accuracy was proposed.It was a multi-group target tracking method based on adaptive predictive clustering (APCMT),realizing the simultaneous tracking of multiple groups.Firstly,cluster was realized,which was to capture the changes of group behavior attributes,such as forming,mergering and spliting.Then,sensors were selected,which were expected to contribute to the group area sensor activation,and the sensors were used for group tracking.Scene simulation was in a square area of 1 000 m ×1 000 m with 500 randomly deployed sensors.The effectiveness of the proposed method was verified by the simulation results.Compared with Kalman,energy-effective node selection (EENS) method and the improved dynamic cluster (IDC) method,the tracking precision of proposed method was higher.And because of the number of activate sensors was less,the computational time was less,the network lifetime had been improved significantly.…”
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Multi-group target tracking method based on adaptive predictive clustering in WSN by Shumu LIU, Jian YANG, Yuansong LI

“…Aiming at the imbalance between energy using and tracking accuracy in multi-sensor target tracking,a method of trade-off network lifetime and accuracy was proposed.It was a multi-group target tracking method based on adaptive predictive clustering (APCMT),realizing the simultaneous tracking of multiple groups.Firstly,cluster was realized,which was to capture the changes of group behavior attributes,such as forming,mergering and spliting.Then,sensors were selected,which were expected to contribute to the group area sensor activation,and the sensors were used for group tracking.Scene simulation was in a square area of 1 000 m ×1 000 m with 500 randomly deployed sensors.The effectiveness of the proposed method was verified by the simulation results.Compared with Kalman,energy-effective node selection (EENS) method and the improved dynamic cluster (IDC) method,the tracking precision of proposed method was higher.And because of the number of activate sensors was less,the computational time was less,the network lifetime had been improved significantly.…”
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Advances in modeling cellular state dynamics: integrating omics data and predictive techniques by Sungwon Jung

“…We highlight how these approaches integrated with various omics data such as transcriptomics, and single-cell RNA sequencing could be used to capture and predict cellular behavior and transitions. We also discuss applications of these modeling approaches in predicting gene knockout effects, designing targeted interventions, and simulating organ development. …”
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The Artificial Intelligence and the dispute for different ways in its predictive use in the criminal process by Rodrigo Régnier Chemim Guimarães

“…While in the United States research is free and has been developing, in France there has been recent criminalization of the behavior of those who use judicial decisions to do so. …”
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Predictive Modeling of the Hydrate Formation Temperature in Highly Pressurized Natural Gas Pipelines by Mustafa Karaköse, Özgün Yücel

“…Data were collected in accordance with the BOTAS Gas Network Code specifications, approved by the Turkish Energy Market Regulatory Authority (EMRA), and generated using DNV GasVLe v3.10 software, which predicts the phase behavior and properties of hydrocarbon-based mixtures under various pressure and temperature conditions. …”
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Unlocking Retail Insights: Predictive Modeling and Customer Segmentation Through Data Analytics by Juan Tang

“…The study advances current research by integrating predictive regression models with RFM segmentation, offering a dual-framework that enhances retail demand forecasting and customer behavior analysis, thereby bridging a critical gap in data-driven decision-making. …”
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Predictive value of the cell cycle markers in squamos cell carcinoma in the oral cavity by R. K. Dibirov, A. I. Yaremenko, N. N. Khromov-Borisov, S. I. Kutukova

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