Results 61 to 70 of about 31,169 (266)

Halide Perovskite: A Rich Source of Thermal Insulator

Advanced Science, EarlyView.
Halide perovskites exhibit ultralow thermal conductivity driven by intrinsic lattice softness and strong anharmonicity, falling below conventional defect‐engineering limits. Weak metavalent bonding, A‐site rattling, and dynamic octahedral tilting drive phonon scattering to the Ioffe–Regel limit, where wave‐like tunneling replaces particle‐like ...
Haolin Ye, Bangzhi Ge, Yuan Yu, Chongjian Zhou   +3 more
wiley   +1 more source

دراسة إحصائية مقارنة للتنبؤ بإيرادات الموارد النفطية في جمهورية مصر العربية باستخدام نماذج الشبكات العصبية المتكررة [PDF]

Maǧallaẗ Al-Buḥūṯ Al-Mālīyyaẗ wa Al-Tiğāriyyaẗ
ملخص البحثيهدف هذا البحث إلى مقارنة كفاءة ودقة التنبؤ بإيرادات الموارد النفطية (ORR) باستخدام نماذج الشبكات العصبية المتكررة (RNN) مثل LSTM وGRU، بالإضافة إلى نماذج السلاسل الزمنية متعددة المتغيرات.
AHMED MOHAMED MOHEY ELDEEN AL HOSAFY
doaj   +1 more source

From Chatbots to Co‐Scientists: The Impact of Knowledge‐Generating AI (AI 4.0) on Healthcare and Research

Advanced Science, EarlyView.
This perspective contrasts the historical, linear progression of early AI with the dynamic, iterative nature of AI 4.0; and it describes the real‐world medical applications and the necessary evolution of laboratory infrastructure brought about by AI 4.0.
Weida Liu, Gary Peltz
wiley   +1 more source

Volatile ZrO2 Antiferroelectric Tunnel Junctions for Rapid, Energy‐Efficient Physical Reservoir Computing

Advanced Science, EarlyView.
An antiferroelectric tunnel junction serves as a reservoir computing node, where field‐induced phase transitions and spontaneous ZrO2 relaxation deliver nonlinear fading memory. An In‐Ga‐Zn oxide interlayer enlarges the memory margin and multibit state richness.
Taegyu Kwon, Moonseek Jeong, Su In Hwang, Geun Hyeong Park, Joonyong Kim, Hyojun Choi, Hyeong Seok Choi, Da Hyun Kim, Dong Hee Han, Ju Yong Park, Seungho Baek, Jung Ho Yoon, Dong Hyun Lee, Min Hyuk Park   +13 more
wiley   +1 more source

BraMARS: An Interpretable Histopathology‐Driven Deep Learning Model for Brain Metastasis Risk Stratification in Surgically Resected Limited‐Stage SCLC

Advanced Science, EarlyView.
This study presents BraMARS, an explainable deep learning model that estimates future brain metastasis risk in surgically resected limited‐stage small‐cell lung cancer using routine H&E‐stained whole‐slide images. By linking model‐attributed spatial histopathology with clinical outcomes and proteomic programs, BraMARS provides a biologically ...
Zijian Yang, Taolue Wang, Shilong Liu, Zicheng Zhang, Yibo Zhang, Fan Yang, Bo Yu, Shuaishuai Gao, Yu Chen, Lin Yang, Meng Zhou   +10 more
wiley   +1 more source

Enhanced High Dimensionality and the Information Processing Capacity in Interfered Spin Wave‐Based Reservoir Computing, Achieved With Eight Detectors

Advanced Electronic Materials, EarlyView.
Physical reservoir computing (PRC) based on spin wave interference has demonstrated high computational performance, yet room for improvement remains. In this study, we fabricated this concept PRC with eight detectors and evaluated the impact of the number of detectors using a chaotic time series prediction task.
Sota Hikasa, Wataru Namiki, Daiki Nishioka, Maki Nishimura, Ryo Iguchi, Kazuya Terabe, Takashi Tsuchiya   +6 more
wiley   +1 more source

Application of Deep Learning Algorithm for Web Shell Detection in Web Application Security System

Jurnal Sisfokom
A web shell is a script executed on a web server, often used by hackers to gain control over an infected server. Detecting web shells is challenging due to their complex behavior patterns. This research focuses on using a deep learning approach to detect
Rezky Yuranda, Edi Surya Negara
doaj   +1 more source

A Hybrid Model for Data-Driven Energy Consumption Forecasting in the Steel Industry: An Approach Based on LSTM and Hyperparameter Optimization with the Optuna Algorithm [PDF]

پژوهش‌های نظری و کاربردی هوش ماشینی
In the modern world, electrical energy, as one of the most fundamental needs of societies, plays a vital role in the industrial, economic, and social sectors.
Leila Zolqadr, Majid Shakhsi-Niaei, Yahia Zare Mehrjerdid, Mohammad Mehdi Lotfi   +3 more
doaj   +1 more source

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

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