Results 161 to 170 of about 235,717 (303)

Emerging Memory and Device Technologies for Hardware‐Accelerated Model Training and Inference

Advanced Electronic Materials, EarlyView.
This review investigates the suitability of various emerging memory technologies as compute‐in‐memory hardware for artificial intelligence (AI) applications. Distinct requirements for training‐ and inference‐centric computing are discussed, spanning device physics, materials, and system integration.
Yoonho Cho, Dae‐won Kim, Yujin Kim, Jung‐Heum Na, Yuwon Jeong, Dong‐Yeop Lee, Shinhyun Choi   +6 more
wiley   +1 more source

Social media distrust and turn to artificial intelligence among generation Z: a qualitative model linking digital minimalism and financial discipline with social policy recommendations. [PDF]

Front Artif Intell
Ökten B.
europepmc   +1 more source

Hydrogen‐State‐Engineered Oxide Semiconductor Channels Enabling Reliable 2T0C DRAM Operation

Advanced Electronic Materials, EarlyView.
We introduce a three‐step hydrogen annealing method for oxide semiconductor devices that modulates hydrogen incorporation and its passivation behavior. Consequently, interface traps are suppressed, whereas the mobility, reliability, and data retention of the IGO‐based 2T0C DRAM are simultaneously improved.
Jun‐Yeoub Lee, Taewon Hwang, Su‐Hwan Choi, Hye‐Jin Oh, Chang‐Kyun Park, Jin‐Seong Park   +5 more
wiley   +1 more source

TAXATION AND THE BUDGET SYSTEM [PDF]

The Bulletin of the National Tax Association, 1920
openaire   +1 more source

Enhancing Access to High School Summer STEM Programs Through Proactive Planning and Budgeting. [PDF]

Ecol Evol
Solomon KJ, Cross DA, Pendergast CL, McFarland MD, Capps KA.   +4 more
europepmc   +1 more source

Efficient In‐Hardware Matrix–Vector Multiplication and Addition Exploiting Bilinearity of Schottky Barrier Transistors Processed on Industrial FDSOI

Advanced Electronic Materials, EarlyView.
ABSTRACT Machine learning and Artificial Intelligence (AI) tasks have stretched traditional hardware to its limits. In‐hardware computation is a novel approach that aims to run complex operations, such as matrix–vector multiplication, directly at the device level for increased efficiency.
Juan P. Martinez, Niladri Bhattacharjee, Yuxuan He, Giulio Galderisi, Brojogopal Sapui, Sara Mannaa, Ian O'Connor, Violetta Sessi, Peter Javorka, Thomas Mikolajick, Jens Trommer   +10 more
wiley   +1 more source

An integrated model of financial socialization, technology, and financial capability in predicting financial well-being. [PDF]

PLoS One
Anh NQ.
europepmc   +1 more source

Ion‐Gating Reservoir Computing for Preprocessing‐Free Speech Recognition from Throat Vibrations

Advanced Electronic Materials, EarlyView.
This work presents a throat‐mounted mechanoelectric sensor integrated with an ion‐gel/graphene reservoir device for on‐device speech recognition. The system converts raw biomechanical vibrations into rich nonlinear current dynamics, enabling efficient classification through a simple linear readout. The approach highlights a compact and tunable physical‐
Daiki Nishioka, Akito Tateyama, Hina Kitano, Takashi Nakanishi, Kazuya Terabe, Takashi Tsuchiya   +5 more
wiley   +1 more source

Reforming hospital management education with the P-MASE pedagogy: a randomized controlled trial. [PDF]

BMC Med Educ
Zhang Y, Li W, Zhang C, Wang Y, Feng S.
europepmc   +1 more source

Smart Exploration of Perovskite Photovoltaics: From AI Driven Discovery to Autonomous Laboratories

Advanced Energy Materials, EarlyView.
In this review, we summarize the fundamentals of AI in automated materials science, and review AI applications in perovskite solar cells. Then, we sum up recent progress in AI‐guided manufacturing optimization, and highlight AI‐driven high‐throughput and autonomous laboratories.
Wenning Chen, Zheyu Zhang, Kelvian T. Mularso, Bonghyun Jo, Hyun Suk Jung   +4 more
wiley   +1 more source