Results 201 to 210 of about 48,058 (264)

Accelerating Discovery of Organic Molecular Crystals via Materials Informatics and Autonomous Experiments

Advanced Intelligent Discovery, EarlyView.
Materials informatics and autonomous experimentation are transforming the discovery of organic molecular crystals. This review presents an integrated molecule–crystal–function–optimization workflow combining machine learning, crystal structure prediction, and Bayesian optimization with robotic platforms.
Takuya Taniguchi, Kazuki Ishizaki, Ryo Fukasawa   +2 more
wiley   +1 more source

Understanding Climate Feedbacks and Sensitivity Using Observations of Earth's Energy Budget. [PDF]

Curr Clim Change Rep, 2016
Loeb NG, Su W, Kato S.
europepmc   +1 more source

A Memristor‐Based In‐Memory Computing System‐on‐Chip with Efficient Depthwise Convolution

Advanced Intelligent Systems, EarlyView.
We present a memristor‐based in‐memory computing (IMC) architecture that enables efficient depthwise convolution (DWC) acceleration. Fabricated in a system‐on‐chip with crossbar arrays, the design improves memory utilization. Experimental validation demonstrates the first hardware acceleration of DWC in IMC, achieving a digital comparable inference ...
Wenhao Song, Fuxi Cai, Sangsu Park, Zhaoyan Li, Seonghun Lee, Mingyi Rao, Woohyung Choi, Seungin Shin, Yan Zhu, Sujin Chae, Myoungsub Kim, Mingche Wu, Hyejung Choi, Yuan Dao, Jaeyun Yi, Youngman Cho, Seon Yong Cha, Ning Ge, Qiangfei Xia, Soo Gil Kim, Miao Hu, J. Joshua Yang   +21 more
wiley   +1 more source

The energy budget in C₄ photosynthesis: insights from a cell-type-specific electron transport model. [PDF]

New Phytol, 2018
Yin X, Struik PC.
europepmc   +1 more source

Resource‐Aware Contrastive Scattering Meta‐Learning for Efficient Few‐Shot Acoustic Anomaly Detection

Advanced Intelligent Systems, EarlyView.
This paper introduces a resource‐aware Contrastive Scattering Meta‐Learning (CSML) framework for acoustic anomaly detection. By leveraging training‐free wavelet scattering and metric‐based meta‐learning, the model achieves competitive performance with only 50 K learnable parameters—a 98% reduction compared to state‐of‐the‐art frameworks—enabling ...
Rami Zewail, Bassem Mokhtar
wiley   +1 more source

Talk to Your Data: An Agentic Artificial Intelligence‐Driven Decision‐Support Framework for Prosumer Energy Optimization and Recommendations

Advanced Intelligent Systems, EarlyView.
An agentic AI‐driven decision‐support framework for prosumers is proposed, integrating PV generation, load profiling, and multihorizon optimization within a four‐agent architecture. The approach significantly reduces grid dependence, enhances self‐sufficiency and prevents system oversizing.
Adela BÂRA, Simona‐Vasilica OPREA
wiley   +1 more source

Overcoming the Phase Discontinuity Problem in RIS Optimization: A Robust and Scalable Phase‐Aware Deep Regression Framework via Hybrid CNN–LSTM Architecture

Advanced Intelligent Systems, EarlyView.
The phase discontinuity problem—where the cyclic nature of phase angles causes catastrophic errors near the ±π boundary—is a fundamental obstacle in learning‐based reconfigurable intelligent surface (RIS) optimization. A phase‐aware hybrid CNN–LSTM framework resolves this by decomposing phase predictions into sine–cosine components, mapping circular ...
Seda Savaşçı Şen, Ali Çalhan, Murtaza Cicioğlu, Oğuzhan Demiryürek   +3 more
wiley   +1 more source

Ultralow‐Power Floating‐Gate InGaZnO Content‐Addressable Memory for Wearable Electrocardiogram Anomaly Detection

Advanced Intelligent Systems, EarlyView.
This study introduces a subthreshold in‐memory anomaly detection architecture for wearable ECG monitoring using floating‐gate IGZO content‐addressable memories on a flexible substrate. Area‐engineered coupling provides a high subthreshold slope, while subthreshold operation realizes intrinsic exponential distance evaluation and linear voltage sensing ...
Hyung‐Jun Noh, Sunyeol Bae, Yumin Yun, Junhyeong Park, Soo‐Yeon Lee   +4 more
wiley   +1 more source

Energy‐Aware Perturbation Optimization for Memristor‐Array Convolutional Neural Networks

Advanced Intelligent Systems, EarlyView.
Memristor‐array inference becomes more energy efficient when layer inputs are reshaped before computation. Sinusoidal perturbation encoding with dual‐threshold screening reduces active voltage pulses and contracts ADC input‐current ranges, jointly lowering crossbar and peripheral energy while preserving accuracy across hardware MNIST validation, deep ...
Ao Xu, Lun Lu, Youpeng Wu, Yao Guo, Yi Li, Yinan Wang, Qingjiang Li   +6 more
wiley   +1 more source

Uncovering renewable energy policy impact channels on land values, the local farm structure, and farmland heterogeneity

American Journal of Agricultural Economics, EarlyView.
Abstract Germany's Renewable Energy Sources Act (REA), enacted in 2000 and subsequently amended, subsidized national renewable energy production with fixed feed‐in tariffs for renewable energy sources (RE) from wind, solar, and biogas. Empirical studies suggest that the policy was creating windfall effects for landowners and attribute farmland use ...
Lars Isenhardt, Stefan Seifert, Saskia Wolff, Tobia Lakes, Marten Graubner, Axel Werwatz, Silke Hüttel   +6 more
wiley   +1 more source