Forecasting of Energy Production for Photovoltaic Systems Based on ARIMA and ANN Advanced Models by Laurentiu Fara, Alexandru Diaconu, Dan Craciunescu, Silvian Fara

“…This article is dedicated to two forecasting models: (1) ARIMA (Autoregressive Integrated Moving Average) statistical approach to time series forecasting, using measured historical data, and (2) ANN (Artificial Neural Network) using machine learning techniques. The main contributions of the authors could be synthetized as follows: (1) analysis and discussion of the experimental and simulated results regarding solar radiation forecast, as well as energy production prediction and forecasting based on ARIMA and ANN models for two case studies: (a) laboratory BIPV system developed at the Polytechnic University of Bucharest and (b) large PV park placed in a specific site of the south of Romania. …”
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Pengaruh Sertifikasi Guru, Profesionalisme, dan Disiplin Kerja Terhadap Kinerja Guru by Deka Dwi Susanti, Andi Kristanto, Kaniati Amalia

“…Work discipline, which includes punctuality, adherence to rules, and commitment to teaching duties, further supports the improvement of teaching quality and student learning outcomes. These three variables work together to enhance overall teacher performance, ultimately contributing to the achievement of better educational outcomes. …”
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Mathematical and computational modeling for organic and insect frass fertilizer production: A systematic review. by Malontema Katchali, Edward Richard, Henri E Z Tonnang, Chrysantus M Tanga, Dennis Beesigamukama, Kennedy Senagi

“…Mathematical models such as simulation, regression, dynamics, and kinetics have been applied while computational data driven machine learning models such as random forest, support vector machines, gradient boosting, and artificial neural networks have also been applied as well. …”
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Out-of-school children and the role of social reconstructionism in education in the context of Cambodia: an implication for reform policy by Yem Bunthorn

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Astrocyte and Neuronal Plasticity in the Somatosensory System by Robert E. Sims, John B. Butcher, H. Rheinallt Parri, Stanislaw Glazewski

“…This is thought to underlie learning and memory processes and so adaptation to a changing environment. …”
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Rolling Bearing Degradation State Identification Based on LPP Optimized by GA by He Yu, Hong-ru Li, Zai-ke Tian, Wei-guo Wang

“…In view of the problem that the actual degradation status of rolling bearing has a poor distinguishing characteristic and strong fuzziness, a rolling bearing degradation state identification method based on multidomain feature fusion and dimension reduction of manifold learning combined with GG clustering is proposed. Firstly, the rolling bearing all-life data is preprocessed by local characteristic-scale decomposition (LCD) and six typical features including relative energy spectrum entropy (LREE), relative singular spectrum entropy (LRSE), two-element multiscale entropy (TMSE), standard deviation (STD), RMS, and root-square amplitude (XR) are extracted and compose the original multidomain feature set. …”
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MSLp: Deep Superresolution for Meteorological Satellite Image by Liling Zhao, Hao Yu, Yan Wang

“…Fortunately, based on zero-shot learning theory, the complexity of the meteorological satellite image can be used to enhance its own image resolution. …”
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Cohesion policy and metropolitan governance: innovation in stakeholders collaboration practices in Lisbon by Margarida Queirós, Luís Balula, Mário Vale

“…These initiatives have broken down planning silos, promoting "soft spaces of governance" that encouraged knowledge exchange and institutional learning among territorial stakeholders. However, challenges persist in the absence of a coherent regional strategy and the prioritization of broad EU objectives over tailored regional needs. …”
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Engine on/off management with consideration of thermal dynamics for HEVs by Wei Wang, Tielong Shen

“…Existing solutions mainly focus on the non-linear optimization or complex learning-based methods, which unavoidably lead to high computation burden and hard to be online implemented. …”
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Enhancing urban air quality prediction using time-based-spatial forecasting framework by Shrikar Jayaraman, Nathezhtha T, Abirami S, Sakthivel G

“…The proposed Time-Based-Spatial (TBS) forecasting framework is integrated with spatial and temporal information using machine learning techniques on data collected from a wide range of cities. …”
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Power Prediction-Based Model Predictive Control for Energy Management in Land and Air Vehicle with Turboshaft Engine by Zhengchao Wei, Yue Ma, Changle Xiang, Dabo Liu

“…An integrated power predictor consisting of the classification of input status and the subpredictors are developed based on the deep learning method to improve the accuracy of the prediction model of the model predictive control (MPC). …”
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Optimizing Credit Card Fraud Detection: A Genetic Algorithm Approach with Multiple Feature Selection Methods by Sunil Kumar Patel, Devina Panday

“…This study dives into the realm of machine learning, evaluating the performance of various algorithms - logistic regression (LR), decision tree (DT), and random forest (RF) - in detecting credit card fraud. …”
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Prediction of individual patient outcomes to psychotherapy vs medication for major depression by Devon LoParo, Boadie W. Dunlop, Charles B. Nemeroff, Helen S. Mayberg, W. Edward Craighead

“…Individual response to treatment, however, is variable, implying individual differences that could allow for prospective differential prediction of treatment response and personalized treatment recommendation. We used machine learning to develop predictor variables that combined demographic and clinical items from a randomized clinical trial. …”
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Stokes flows in a two-dimensional bifurcation by Yidan Xue, Stephen J. Payne, Sarah L. Waters

“…We parametrize the flow conductances of 2D bifurcation as functions of the dimensionless parameters of bifurcation geometry and a fixed object using a machine learning approach, which is simple to use and provides more accurate approximations than Poiseuille’s law. …”
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Comparison of the Performance of the C.45 Algorithm with Naive Bayes in Analyzing Book Borrowing at the Library Pringsewu Muhammadiyah University by Dani Wilian, Sriyanto Sriyanto

“…This research underscores the potential of data mining techniques to optimize library management and proposes avenues for future investigation, such as exploring advanced machine learning algorithms and expanding datasets for use in broader library contexts.…”
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Language awareness as a prerequisite of literacy skills by Anna Kucharská, Klára Špačková, Martina Šmejkalová

“…Identifying literacy difficulties in terms of specific learning disabilities is an important topic for elementary school pupils. …”
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Automatic Emergence Detection in Complex Systems by Eugene Santos, Yan Zhao

“…In addition, we demonstrate that this framework has uniform polynomial time complexity across all three learning, fusion, and reasoning procedures.…”
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Moral Foundations of the Theory of Education in Russian Neo-Kantianism by P. A. Vladimirov, A. V. Lebedeva

“…The emphasis is placed on two aspects: 1) philosophy and pedagogy complement each other within the framework of practical philosophy in determining the teleological reason for learning and upbringing, and 2) spiritual and moral foundations determine the efficiency of the process of forming a free and creative individual. …”
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Nonlinear Control of an Active Magnetic Bearing System Achieved Using a Fuzzy Control with Radial Basis Function Neural Network by Seng-Chi Chen, Van-Sum Nguyen, Dinh-Kha Le, Nguyen Thi Hoai Nam

“…The proposed controller can be feasibly applied to AMB systems exposed to various external disturbances; demonstrating the effectiveness of the NFC with self-learning and self-improving capacities is proven.…”
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A Bibliometric Analysis of Publications on University-Industry Collaboration Using VOSviewer and R-biblioshiny by Zhan Guofang, Mohamad Sattar Rasul, Marlissa Omar

“…Additionally, based on keyword co-occurrence analysis, research related to university-industry collaboration is distributed across five clusters: (1) innovation and technology transfer, (2) internships and work experience, (3) cooperative education and learning outcomes, (4) collaboration models and partnerships, and (5) collaboration barriers, challenges, and sustainability. …”
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