Results 141 to 150 of about 14,108,597 (163)

LLM‐Assisted Design of Ultralow‐κ$\kappa$ Chalcogenides

Advanced Science, EarlyView.
An AI assisted, physics guided workflow accelerates the discovery of ultralow thermal conductivity materials by combining Bayesian optimization, evidence conditioned LLM reasoning, and automated physics‐based validation. The framework uncovers dynamically stable Ag based chalcogenides with ultralow thermal conductivity and promising thermoelectric ...
Yujie Liu, Congran Jia, Yuzhou Hao, Xuejie Li, Yang Wang, Artem Oganov, Jun Sun, Xiangdong Ding, Turab Lookman, Zhibin Gao   +9 more
wiley   +1 more source

Spatiotemporal Regulation of Hierarchical Assembly of Hydroxyapatite for Enamel Remineralization

Advanced Science, EarlyView.
Biomimetic repair exhibits unique advantages for enamel regeneration compared with conventional clinical treatments. An enzymatic mineralization system (EMS) is developed, where the resulting HAP nanorods hierarchically assemble into a highly ordered structure on the enamel surface through the spatiotemporal modulation of interfacial energies of ...
Zhenhang Tang, Zhisen Zhang, Yuanyu Zhou, Wenzhi Wu, Congrui Zhao, Chang Liu, Tong Shi, Wenjing Jin, Zhaoming Liu, Weifeng Fang, Qingyun Lin, Yi He, Zhijian Xie, Ruikang Tang, Changyu Shao, Zhuo Chen   +15 more
wiley   +1 more source

Hardware‐Native Gaussian Sampling With Probabilistic Ising Machines for Modern Communication Paradigms

Advanced Science, EarlyView.
Probabilistic Ising machines are introduced as hardware‐native Gaussian samplers for edge communication workloads. Tunable variance and sampling density enable accurate distributions for Falcon‐class post‐quantum signatures and diffusion‐based semantic communication.
Davi Rodrigues, Andrea Grimaldi, Deborah Volpe, Youwei Bao, Shuhan Yang, Eleonora Grassucci, Giulio Siracusano, Massimo Chiappini, Mario Carpentieri, Hyunsoo Yang, Giovanni Finocchio   +10 more
wiley   +1 more source

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Automatic Extraction of Decision Rules from Non-deterministic Data Systems: Theoretical Foundations and SQL-Based Implementation

Communications in Computer and Information Science, 2009
We present a framework for SQL-based extraction of decision rules from data, with no need of retrieving massive amounts of rows from a database. We also explain how to design efficient methods for mining non-deterministic data, without any intermediate stages related to the analysis of undetermined values.
Dominik Slezak, Hiroshi Sakai
openaire   +4 more sources

Stable rule extraction and decision making in rough non-deterministic information analysis

International Journal of Hybrid Intelligent Systems, 2011
Rough Non-deterministic Information Analysis (RNIA) is a rough set-based data analysis framework for Non-deterministic Information Systems (NISs). RNIA-related algorithms and software tools developed so far for rule generation provide good characteristics of NISs and can be successfully applied to decision making based on non-deterministic data.
Hiroshi Sakai, Hitomi Okuma, Michinori Nakata, Dominik Slezak   +3 more
openaire   +3 more sources

Deterministic and Nondeterministic Decision Trees for Recognition of All Realizable Decision Rules

Lecture Notes in Computer Science
The exploration of the relationships between decision trees and systems of decision rules is a significant research domain within computer science. While established methods exist for converting decision trees into systems of decision rules, the reverse ...
Mikhail Moshkov, Kerven Durdymyradov
exaly   +2 more sources

Comparison of Some Classification Algorithms Based on Deterministic and Nondeterministic Decision Rules

Lecture Notes in Computer Science, 2010
We discuss two, in a sense extreme, kinds of nondeterministic rules in decision tables. The first kind of rules, called as inhibitory rules, are blocking only one decision value (i.e., they have all but one decisions from all possible decisions on their ...
Zbigniew Suraj, Andrzej Skowron, Mikhail Moshkov   +2 more
exaly   +2 more sources

Efficient Modeling of Deterministic Decision Trees for Recognition of Realizable Decision Rules: Bounds on Weighted Depth

Axioms
In this paper, an efficient algorithm for modeling the operation of a DDT (Deterministic Decision Tree) solving the problem of realizability of DRs (Decision Rules) is proposed and analyzed.
Mikhail Moshkov, Kerven Durdymyradov
exaly   +2 more sources

Deterministic and Nondeterministic Decision Trees for Recognition of Properties of Decision Rule Systems

Lecture Notes in Computer Science
This paper considers various problems of recognizing the properties of decision rule systems. Deterministic and nondeterministic decision trees are used as algorithms for solving them.
Mikhail Moshkov, Kerven Durdymyradov
exaly   +2 more sources

Decision Aids for Localized Prostate Cancer Treatment Choice: Systematic Review and Meta-Analysis

Ca-A Cancer Journal for Clinicians, 2015
Arnav Agarwal, Henrikki Santti
exaly