Results 171 to 180 of about 379,748 (264)

Toward Capacitive In‐Memory‐Computing: A Device to Systems Level Perspective on the Future of Artificial Intelligence Hardware

Advanced Intelligent Discovery, EarlyView.
Capacitive, charge‐domain compute‐in‐memory (CIM) stores weights as capacitance,eliminating DC sneak paths and IR‐drop, yielding near‐zero standbypower. In this perspective, we present a device to systems level performance analysis of most promising architectures and predict apathway for upscaling capacitive CIM for sustainable edge computing ...
Kapil Bhardwaj, Ella Paasio, Sayani Majumdar   +2 more
wiley   +1 more source

Perimenstrual exacerbation of symptoms in borderline personality disorder: evidence from multilevel models and the Carolina Premenstrual Assessment Scoring System. [PDF]

Psychol Med, 2018
Eisenlohr-Moul TA, Schmalenberger KM, Owens SA, Peters JR, Dawson DN, Girdler SS.   +5 more
europepmc   +1 more source

Advancing Efficient Error Reduction in DNA Data Storage Systems with Deep Learning‐Based Denoising Models

Advanced Intelligent Discovery, EarlyView.
Deep learning‐based denoising models are applied to DNA data storage systems to enhance error reduction and data fidelity. By integrating DnCNN with DNA sequence encoding methods, the study demonstrates significant improvements in image quality and correction of substitution errors, revealing a promising path toward robust and efficient DNA‐based ...
Seongjun Seo, Anshula Tandon, Nguyen Kim Uyen, Quoc Nam Le, Jee‐Hyong Lee, Sung Ha Park   +5 more
wiley   +1 more source

Exploring the role of hospitals and office-based physicians in timely provision of statins following acute myocardial infarction: a secondary analysis of a nationwide cohort using cross-classified multilevel models. [PDF]

BMJ Open, 2019
Schang L, Koller D, Franke S, Sundmacher L.   +3 more
europepmc   +1 more source

AI‐Guided Co‐Optimization of Advanced Field‐Effect Transistors: Bridging Material, Device, and Fabrication Design

Advanced Intelligent Discovery, EarlyView.
This article outlines how artificial intelligence could reshape the design of next‐generation transistors as traditional scaling reaches its limits. It discusses emerging roles of machine learning across materials selection, device modeling, and fabrication processes, and highlights hierarchical reinforcement learning as a promising framework for ...
Shoubhanik Nath, Shauryaraj K. Jilkar, Aditya Udgaonkar, Yu (Joe) Lu, Ali Mesbah   +4 more
wiley   +1 more source

Large‐Scale and Highly Reliable Hopfield Neural Networks Using Vertical NAND Flash Memory for the In‐Memory Associative Computing

Advanced Intelligent Systems, EarlyView.
Large‐scale Hopfield neural networks (HNNs) for associative computing are implemented using vertical NAND (VNAND) flash memory. The proposed VNAND HNN with the asynchronous update scenario achieve robust image restoration performance despite fabrication variations, while significantly reducing chip area (≈117× smaller than resistive random‐access ...
Jin Ho Chang, Jae Seung Woo, Suk‐Kang Sung, Ki‐Whan Song, Woo Young Choi   +4 more
wiley   +1 more source

Device‐Level Implementation of Reservoir Computing With Memristors

Advanced Intelligent Systems, EarlyView.
Reservoir computing (RC) is an emerging computing scheme that employs a reservoir and a single readout layer, which can be actualized in the nanoscale with memristors. As a comprehensive overview, the principles of RC and the switching mechanisms of memristors are discussed, followed by actual demonstrations of memristor‐based RC and the remaining ...
Sunbeom Park, Hyojung Kim, Ho Won Jang
wiley   +1 more source

Integrating Artificial Intelligence With Droplet‐Based Microfluidics: Advances, Challenges, and Emerging Opportunities

Advanced Intelligent Systems, EarlyView.
Droplet‐based microfluidics enables precise, high‐throughput microscale reactions but continues to face challenges in scalability, reproducibility, and data complexity. This review examines how artificial intelligence enhances droplet generation, detection, sorting, and adaptive control and discusses emerging opportunities for clinical and industrial ...
Junyan Lai, Sukrit Gaira, Rongfeng Wang, Qingtian Zhang, Ming Li, Liao Wu, Diangeng Li, Yi Li, Chengchen Zhang, Jinhong Guo, Shi‐Yang Tang   +10 more
wiley   +1 more source

A Flexible and Energy‐Efficient Compute‐in‐Memory Accelerator for Kolmogorov–Arnold Networks

Advanced Intelligent Systems, EarlyView.
This article presents KA‐CIM, a compute‐in‐memory accelerator for Kolmogorov–Arnold Networks (KANs). It enables flexible and efficient computation of arbitrary nonlinear functions through cross‐layer co‐optimization from algorithm to device. KA‐CIM surpasses CPU, ASIC, VMM‐CIM, and prior KAN accelerators by 1–3 orders of magnitude in energy‐delay ...
Chirag Sudarshan, Oliver Artner, Paul‐Philipp Manea, Sebastian Siegel, Susanne Hoffmann‐Eifert, Regina Dittmann, John Paul Strachan   +6 more
wiley   +1 more source

Methods for Setting Device Specifications for Analog In‐Memory Computing Inference

Advanced Intelligent Systems, EarlyView.
Non‐volatile memories (NVMs) are being developed for analog in‐memory computing for energy‐efficient, high‐speed deep learning inference. As technology is moving to industry adoption, a method to define required NVM specifications is critical for improving performance and reducing manufacturing cost.
Zhenyu Wu, Xin Su, Malte J. Rasch, Ning Li   +3 more
wiley   +1 more source