In response to the energy and memory limitations of WSNs, this research work introduces a new approach: EMPIRE-CS (Energy and Memory-optimized Performance with Iterative Reinforcement and Compressive Sensing). It is a hybrid approach combining compressive sensing with reinforcement learning and game-theoretic cluster...
S. Balamurali, SatheeshKumar Palanisamy, N. Sathishkumar et al.· Scientific Reports· 0 citations
Modern digital integrated circuits contain very large numbers of logic gates, and the conventional heuristics used in logic synthesis and netlist optimization struggle to explore the resulting design space efficiently. Artificial Intelligence (AI) and Machine Learning (ML) have therefore been investigated as complement...
VALERIO LARRYII PENULIAR· Zenodo (CERN European Organi...· 0 citations
Simulator, baselines, experiment scripts, per-scenario results and trained models for the multi-year allocation of a rooftop-PV subsidy budget across the 32 neighbourhoods of an IEEE 33-bus feeder under uncertain acceptance, demand growth and irradiance (19 years of PVGIS data for Tehran). The package contains the LinD...
Hesam Jafari, Hadi Sahebi· Zenodo (CERN European Organi...· 0 citations
Project TALOS is an autonomous research intelligence platform powered by deep reinforcement learning (DDDQN), multi-tier LLM orchestration, and the Grey Wolf Optimizer (GWO). It conducts end-to-end scientific literature discovery and evaluation across 18 academic APIs.
Christos Smarlamakis, Efstratios Georgopoulos· Zenodo (CERN European Organi...· 0 citations
This research explores how Artificial Intelligence can enhance the optimization of Arithmetic Logic Units (ALUs), which are crucial for processor speed, energy efficiency, and silicon area. Traditional ALU design relies on fixed architectures and rule-based heuristics, but the proposed framework integrates Graph Neural...
Jhon Rymr Agustin· Zenodo (CERN European Organi...· 0 citations
This research journal discusses how Artificial Intelligence (AI) and Machine Learning (ML) can enhance computer architecture design by addressing challenges in performance and energy efficiency. Traditional methods rely on expert intuition and exhaustive simulations, which are limited when exploring vast design spaces....
Marlyn Sto Domingo· Zenodo (CERN European Organi...· 0 citations
Project TALOS is an autonomous research intelligence platform powered by deep reinforcement learning (DDDQN), multi-tier LLM orchestration, and the Grey Wolf Optimizer (GWO). It conducts end-to-end scientific literature discovery and evaluation across 18 academic APIs.
Christos Smarlamakis, Efstratios Georgopoulos· Zenodo (CERN European Organi...· 0 citations
An error management climate (EMC) promotes open discussion, analysis, and constructive handling of errors, fostering learning and innovation. However, how to develop such a climate in construction organizations remains poorly understood. This paper examines practical mechanisms for cultivating EMC in project environm...
Peter E. D. Love· Journal of construction engi...· 0 citations
Project TALOS is an autonomous research intelligence platform powered by deep reinforcement learning (DDDQN), multi-tier LLM orchestration, and the Grey Wolf Optimizer (GWO). It conducts end-to-end scientific literature discovery and evaluation across 18 academic APIs.
Christos Smarlamakis, Efstratios Georgopoulos· Zenodo (CERN European Organi...· 0 citations
Prabha Jha used her experience with MIT Open Learning’s program for senior executives to develop AI solutions for her employer, Verizon, and to write a book.
Assistant Professor Benjamin Lindquist studies how engineers deliberately injected randomness into early AI, giving rise to deep-learning models that sometimes hallucinate.