Results 71 to 80 of about 4,702 (258)

Highly‐Uniform Passive Crossbar Arrays of Resistive Switching Random Access Memory (RRAM) for In‐Memory Computing Applications

Advanced Electronic Materials, EarlyView.
Passive resistive memory arrays promise efficient in‐memory computing but suffer from sneak paths and programming variability. Here, highly uniform 32 × 32 passive RRAM crossbars are programmed with multilevel precision below 3% error and 99.5% yield.
S. Ricci, P. Mannocci, M. Porzani, D. Bridarolli, F. Carletti, M. Farronato, D. Ielmini   +6 more
wiley   +1 more source

Shallow, Deep, Ensemble models for Network Device Workload Forecasting [PDF]

Annals of computer science and information systems, 2020
Cenru Liu
doaj   +1 more source

A Dual‐Branch Flux‐Based Extended Memristor Model With Machine‐Learning‐Assisted Calibration

Advanced Electronic Materials, EarlyView.
Multilayer oxide memristors integrated in crossbar arrays are described through a dual‐branch, flux‐controlled compact model. A three‐stage calibration workflow combining Latin hypercube sampling, Bayesian optimization, and gradient‐based refinement extracts device parameters from experimental data.
Davide Rossetti, K. Nikiruy, A.S. Demirkol, Alon Ascoli, M. Ziegler, R. Tetzlaff, Fernando Corinto   +6 more
wiley   +1 more source

Deep Learning-Driven Workload Prediction and Optimization for Load Balancing in Cloud Computing Environment

Cybernetics and Information Technologies
Cloud computing revolutionizes as a technology that succeeds in serving large-scale user demands. Workload prediction and scheduling tend to be factors dictating cloud performance.
Karimunnisa Syed, Pachipala Yellamma
doaj   +1 more source

Attention-Driven AI Model Generalization for Workload Forecasting in the Compute Continuum

IEEE Transactions on Machine Learning in Communications and Networking
Effective resource management in edge-cloud networks demands precise forecasting of diverse workload resource usage. Due to the fluctuating nature of user demands, prediction models must have strong generalization abilities, ensuring high performance ...
Berend J. D. Gort, Godfrey M. Kibalya, Angelos Antonopoulos   +2 more
doaj   +1 more source

Determining the Relationship Between Composition, Structure, and Device Properties of GexSe1‐x‐Based Selector‐Only Memory

Advanced Electronic Materials, EarlyView.
Composition‐dependent structural evolution in GeXSe1‐X selector‐only memory (SOM) is correlated with device switching behavior. Increasing Ge strengthens network rigidity, suppresses atomic motion, and stabilizes threshold switching, while narrowing the memory window. The revealed structure–property relationship provides a guideline for compositionally
Tien Anh Nguyen, Changdeok Han, Dipannita Ghosh, Suyong Chae, Moongyu Choi, Sanghyun Ban, Myoungsub Kim, Sangmin Yoo, Seung Hwan Lee, Sieun Chae   +9 more
wiley   +1 more source

Predictable and Scalable Analog Matrix–Vector Multiplication in Memristor Crossbars via Closed‐Form Wire‐Resistance Compensation

Advanced Electronic Materials, EarlyView.
Wire resistance and sneak paths severely compromise the performance of large memristor crossbars. A predictive closed‐form distributed line‐resistance model, combined with a fourmatrix geometry‐averaging algorithm, eliminates these parasitic limitations.
Davide Rossetti, Yichun Xu, Ludovica Asselta, J. Joshua Yang, R. Stanley Williams, Fernando Corinto   +5 more
wiley   +1 more source

A machine-learning decision support system for demand-driven nurse staffing in outpatient clinics: Design and validation at an Indonesian public hospital

Transactions on Computational Modeling and Intelligent Systems
Public hospitals in developing countries often plan their health workforce reactively despite highly variable daily patient demand, leading to uneven workloads and longer waiting times.
Muhammad Fadhillah Hadi, Asmuliardi Muluk   +1 more
doaj   +1 more source

Determinants of Knowledge and Usage of Generative Artificial Intelligence in Agricultural Extension: Evidence From Tennessee Extension Personnel

Agribusiness, EarlyView.
ABSTRACT This paper examines the determinants of generative AI (GenAI) knowledge and usage among agricultural extension professionals. Drawing on survey data from agricultural extension personnel in Tennessee, we employ regression analyses and latent Dirichlet allocation (LDA) for topic modeling of open‐ended responses to study the knowledge and usage ...
Abdelaziz Lawani, Jason de Koff, James Muriuki, Anna‐Liisa Ihuhwa   +3 more
wiley   +1 more source

Extending OpenStack Monasca for Predictive Elasticity Control

Big Data Mining and Analytics
Traditional auto-scaling approaches are conceived as reactive automations, typically triggered when predefined thresholds are breached by resource consumption metrics.
Giacomo Lanciano, Filippo Galli, Tommaso Cucinotta, Davide Bacciu, Andrea Passarella   +4 more
doaj   +1 more source