Navigating Samarinda's climate: A comparative analysis of rainfall forecasting models by Mislan, Andrea Tri Rian Dani

“…Evaluation of goodness-of-fit using Root Mean Squared Error Prediction (RMSEP). The research results show that the Neural Network has better accuracy in predicting rainfall in Samarinda. …”
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Corporate governance and earnings management in banks: An empirical evidence from India by Sarit Biswas, Mousumi Bhattacharya, Pradip H Sadarangani, Justin Yiqiang Jin

“…Using a Panel Corrected Standard Error (PCSE) approach, the study finds that CG has a significant negative impact on EM in Indian commercial banks. …”
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Exploration of Algorithms and Heuristics in Puzzle Playing Activities of Early Childhood by Selvia Dwi Lusiana, Thorik Aziz

“…The findings identify several commonly used algorithmic strategies, such as edge-first, color or image-based grouping, and systematic trial and error. Frequently utilized heuristics include shape-based searching, using images as guides, and eliminating unsuitable options. …”
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The ubiquity of selective attention in the processing of feedback during category learning. by Katerina Dolguikh, Tyrus Tracey, Mark R Blair

“…We find that selective attention to task-relevant information is pervasive throughout feedback processing, suggesting a role for selective attention in memory encoding of category exemplars. We also find that error trials elicit additional stimulus processing during the feedback phase. …”
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Exploring the Adoption of Collaborative Robots for the Preparation of Galenic Formulations by Luigi Gargioni, Daniela Fogli, Pietro Baroni

“…This paper proposes the use of collaborative robots to help pharmacists carry out the most tiresome, precise, error-prone, and time-consuming tasks. In particular, an end-user development (EUD) environment called PRAISE (pharmaceutical robotic and AI system for end users) has been designed to support pharmacists in programming the tasks to be performed by a collaborative robot. …”
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The low prevalence effect in fingerprint comparison amongst forensic science trainees and novices. by Bethany Growns, James D Dunn, Rebecca K Helm, Alice Towler, Jeff Kukucka

“…., from different people) fingerprint pairs, people more often misjudge 'non-matching' pairs as 'matches'-an error that can falsely implicate an innocent person for a crime they did not commit. …”
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Effect of Macroeconomic Factors on Economic Growth in Indonesia by Hafidz Zainul Mustofa, Moh. Faizin

“…The analysis used the Vector Error Correction Model (VECM) approach to understand the long-run and short-run relationships. …”
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Navigating Ambiguity: Critiques of Indonesia's Health Law and its Impact on Legal Redress for Medical Malpractice Victims by Mia Amiati, Hamzah Halim, Jady Zaidi Hassim

“…This article critically examines the implications of the 2023 Health Law on victim redress, particularly concerning medical personnel protection and the application of restorative justice in life-threatening medical error cases. …”
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Predicting the unpredicted … brain response: A systematic review of the feature-related visual mismatch negativity (vMMN) and the experimental parameters that affect it. by Alie G Male

“…In this systematic review and meta-analysis, I consider aspects of experimental design that affect the visual mismatch negativity (vMMN)-an electrophysiological (neural) correlate of prediction error in vision that is typically largest between 150 ms and 300 ms in the event-related potential (ERP) at occipito-parietal regions on the scalp. …”
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Estimation of bimodal soil-water characteristics curve under wetting process. by Nura Bello, Alfrendo Satyanaga, Nurly Gofar, Jong Kim

“…The overall model performance has been evaluated through statistical methods using the coefficient of determination (R2) and Root Mean Square Error (RMSE). The evaluation also indicates a good performance of the model, with an average RMSE of 0.0263 and an average R2 of 0.9945 for the six soil samples used in the validation. …”
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A Feed-Forward Back-Propagation Neural Network Approach for Integration of Electric Vehicles into Vehicle-to-Grid (V2G) to Predict State of Charge for Lithium-Ion Batteries by Alice Cervellieri

“…In this work, we develop a Feed-Forward Back-Propagation Network (FFBPN) using MATLAB 2024 software, employing the Levenberg–Marquardt algorithm and varying the number of hidden neurons to achieve better performance; performance was measured by the maximum coefficient of determination (R²) and the minimum mean squared error (MSE). Utilizing the NASA Prognostics Center of Excellence (PCoE) dataset, we validate the model’s capability to accurately predict the life cycle of EV batteries. …”
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Sovereign Credit Rating Determinants of the EU Countries: The Role of the Euro Area Crisis and Its Legacy by Ewa Stawasz-Grabowska

“…The frequency of data is yearly, and panel error correction model is used as the main research method. …”
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Generalized cue reactivity in rat dopamine neurons after opioids by Collin M. Lehmann, Nora E. Miller, Varun S. Nair, Kauê M. Costa, Geoffrey Schoenbaum, Khaled Moussawi

“…The leading hypothesis is that drug-induced dopamine release represents a persistently positive reward prediction error that causes runaway enhancement of dopamine responses to drug cues, leading to their pathological overvaluation. …”
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Orthographic processing of proper Names: A proposal to investigate the orthographic cue for second language readers by Kimberly Klassen

“…A proposed method to investigate the initial capital letter as a cue for L2 English proper name recognition is a name decision task, a variation on a lexical decision task, using English proper names and common nouns that are familiar to Japanese participants. Reaction times and error percentages to proper names with case type as a factor (i.e., initial capital letter or all lowercase) will be submitted to a linear mixed effects analysis. …”
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Fuzzy C-Means and Explainable AI for Quantum Entanglement Classification and Noise Analysis by Gabriel Marín Díaz

“…The results have practical implications in quantum error correction, quantum cryptography, and the optimization of quantum technologies under realistic conditions.…”
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Barriers to Regular Student Attendance in Sociology Programs at Mid-West University, Nepal by Anand Prasad Subedi, Bed Prakash Dhakal

“…The sample size of the survey is determined based on [ ]  formula where the margin of error is 0.05, in which the sample size (n) is 63. …”
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Comparative analysis of mental and physical fatigue on motor coordination, visual search patterns, perceived effort, and performance outcomes in closed-loop aiming task. by Maryam Khalaji, Parvaneh Shamsipour Dehkordi, Fatemehsadat Mousavian, Saeed Alboghebeish

“…In addition to the radial error, swing accuracy, Quiet Eye Duration (QED), and fixation number were recorded before and after fatigue. …”
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Comparative Judgment: Building a Shared Consensus Over Rater Variation in Assessing Second Language Writing Performance by Qian Wu

“…Instead of treating rater variation as an undesired source of measurement error, the method of comparative judgment (CJ) uses pairwise comparisons to elicit relative judgments from raters and statistical estimation to construct a measurement scale to rank object items, offering a viable approach to accommodate rater-associated heterogeneity of judgment making on the one hand and obtain reliable and valid outcomes on the other hand. …”
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Student Enrolment and Output Effects in Poland: 2SLS and VAR Estimates by Joanna Żyra

“…Research Design & Methods: Educational effects on output, i.e. industrial production and gross domestic product (GDP), are estimated by means of Two-Stage Least Squares (2SLS) model, vector error-correction autoregression (VAR/VEC) model, and with the application of annual data sample for the period of 1992-2017. …”
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Artificial neural networks for predicting first-lactation 305-day milk yield in crossbred cattle by SM Usman, A Kumar, A Sherasiya, IM Youssef, MM Abo Ghanima, J Chandrakar, R Tiwari, NP Singh, QS Sahib, T Dutt, AA Swelum

“…The study compares ANN and multiple linear regression models, showing that ANNs provide superior predictive accuracy and lower error margins. This has important implications for local dairy farming systems, particularly in data-limited environments, as it offers a practical tool for early identification of high- and low-producing cows. …”
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