Natural and Social Sciences (IPAS) learning for students with mild intellectual disabilities requires structured, concrete instruction suited to individual needs. This study described the implementation of Direct Instruction in IPAS learning for Phase B students with mild intellectual disabilities at SLB BC Murni Bandu...
The demonstration method has proven capable of providing a concrete and meaningful learning experience for students, making it a highly relevant alternative solution to address low academic achievement in elementary science. The low Natural and Social Sciences (IPAS) learning outcomes among fourth-grade students at SDN...
Natural and Social Sciences (IPAS) learning in elementary schools requires contextual conceptual understanding; however, student achievement remains low due to passive instructional practices that fail to accommodate diverse learning styles. This study aimed to determine the effect of the quantum teaching learning mode...
Yeni Madina Matondang, Antonius Remigius Abi, Lasmaria Agnes Sinaga· LEARNING Jurnal Inovasi Pene...· 0 citations
The Frontier Index is a continuously updated, evidence-scored index of the latest scientific discoveries and breakthroughs in science and technology. Each entry carries a transparent Frontier Score from 0 to 100, composed of three pillars (evidence, impact, and novelty), computed from up to 13 independent public data s...
Frontier· Zenodo (CERN European Organi...· 0 citations
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Peer review is a scholarly and professional duty for which every researcher bears direct responsibility. This responsibility stems from the fact that the scientific development of any field, along with the enhancement of its journals and scholarly resources, is profoundly influenced by the quality of its peer review pr...
We propose a spectral-based, unsupervised representation learning framework to derive low-dimensional embeddings for clinical concepts and patients in rare disease cohorts from electronic health records, where data are high-dimensional but sample sizes are limited. To overcome this challenge, we incorporate a knowledge...
Feiqing Huang, Zongqi Xia, Rong Ma et al.· 0 citations
We study online conformal prediction in a partially observed panel: a new cross-section of peer outcomes is observed before each target outcome, target feedback may be intermittent or absent, and neither units nor rounds need be exchangeable. We propose Weighted Temporal Quantile Adjustment (W-TQA), which combines simi...
Autocorrelation is a common property of time-series, where each observation is dependent on its predecessors. In deep time-series forecasting, it raises two central challenges: (1) designing backbone architectures to model autocorrelation in history sequences, and (2) devising loss functions to model autocorrelation in...
Hao Wang, Licheng Pan, Qingsong Wen et al.· 0 citations
Models with intractable normalizing constants are widely used in statistics and machine learning. Assessing the adequacy of such models poses significant challenges: obtaining samples from the fitted model often requires sophisticated sampling algorithms. Moreover, model fitting sometimes requires iterative numerical o...
A growing class of machine-learning objects -- covariance and Gram matrices, kernel and attention matrices, MIMO channel matrices, density operators -- are naturally spectra rather than coordinate vectors. Building a denoising diffusion model for such data by corrupting eigenvalues coordinatewise is not merely elegant:...
In many real-world applications, ensuring the robustness and stability of deep neural networks (DNNs) is crucial, particularly for image classification tasks that encounter various input perturbations. While Mixup-based data augmentation techniques have been widely adopted to enhance the resilience of trained models ag...
Jiaming Hu, Yeping Jin, Debarghya Mukherjee et al.· 0 citations
The identifiability analysis of linear Ordinary Differential Equation (ODE) systems is a necessary prerequisite for making reliable causal inferences about these systems. While identifiability has been well studied in scenarios where the system is fully observable, the conditions for identifiability remain unexplored w...
Yuanyuan Wang, Biwei Huang, Wei Huang et al.· 0 citations
A machine-learning approach called CheMeleon provides a practical way to develop new drugs or other molecules with much less detailed, expensive experimentation.
Is your company’s AI sovereign? A practical guide for CIOs on AI vendor lock-in, EU Data Act switching, cloud sovereignty, and testing your exit plan before you need it. The post Sovereignty Is the Option to Leave appeared first on GPT-Lab.
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